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1、stri Task 13 Reliability and Performance of Photovoltaic Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 2025 Report IEA-PVPS T13-29:2025 PVPS Task 13 Reliability and Performance of Photovoltaic Systems Dual Land Use for Agriculture an

2、d Solar Power Production:Overview and Performance of Agrivoltaic Systems What is IEA PVPS TCP?The International Energy Agency(IEA),founded in 1974,is an autonomous body within the framework of the Organization for Economic Cooperation and Development(OECD).The Technology Collaboration Programmes(TCP

3、)were created with a belief that the future of energy security and sustainability starts with global collaboration.The programmes are made up of 6.000 experts across government,aca-demia,and industry dedicated to advancing common research and the application of specific energy technologies.The IEA P

4、hotovoltaic Power Systems Programme(IEA PVPS)is one of the TCPs within the IEA and was established in 1993.The mission of the programme is to“enhance the international collaborative efforts which facilitate the role of photovoltaic solar energy as a cornerstone in the transition to sustainable energ

5、y systems.”To achieve this,the programmes participants have undertaken a variety of joint research projects in PV power systems applications.The overall programme is headed by an Executive Committee,comprised of one delegate from each country or organisation member,which designates distinct Tasks,th

6、at may be research projects or activity areas.The IEA PVPS participating members are Australia,Austria,Belgium,Canada,China,Denmark,Enercity SA,European Union,Finland,France,Germany,India,Israel,Italy,Japan,Korea,Malaysia,Morocco,the Netherlands,Norway,Portugal,Solar Energy Research Institute of Sin

7、gapore(SERIS),SolarPower Europe,South Africa,Spain,Sweden,Switzerland,Thailand,Trkiye,United States.Visit us at:www.iea-pvps.org What is IEA PVPS Task 13?Within the framework of IEA PVPS,Task 13 aims to provide support to market actors working to improve the operation,reliability,and quality of PV c

8、omponents and systems.Performance data from PV systems in different climate zones compiled within the project will help provide the basis for estimates of the current situation regarding PV reliability and performance.The general setting of Task 13 provides a common platform to summarize and report

9、on technical aspects affecting the quality,performance,reliability,and lifetime of PV systems in a wide variety of environments and applications.By working together across national boundaries,we can all take advantage of research and experience from each member country and combine and integrate this

10、 knowledge into valuable summaries of best practices and methods for ensuring PV systems perform at their optimum and continue to provide competitive return on investment.IEA PVPS Task 13 has so far managed to create a framework for the calculations of various parameters that can indicate the qualit

11、y of PV components,systems,and applications.The framework is available and can be used by the PV industry which has expressed appreciation towards the results included in the high-quality reports.The IEA PVPS countries participating in Task 13 are Australia,Austria,Belgium,Canada,Chile,China,Denmark

12、,Finland,France,Germany,Israel,Italy,Japan,the Netherlands,Norway,Spain,Sweden,Switzerland,Thailand,the United States of America,and the Solar Energy Research Institute of Singapore.DISCLAIMER The IEA PVPS TCP is organised under the auspices of the International Energy Agency(IEA)but is functionally

13、 and legally autonomous.Views,findings,and publica-tions of the IEA PVPS TCP do not necessarily represent the views or policies of the IEA Secretariat or its individual member countries.COVER PICTURE Agrivoltaics system on apple farming in Gelsdorf/Rhineland-Palatinate,Germany.Fraunhofer ISE ISBN 97

14、8-3-907281-70-3:Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems INTERNATIONAL ENERGY AGE

15、NCY PHOTOVOLTAIC POWER SYSTEMS PROGRAMME IEA PVPS Task 13 Reliability and Performance of Photovoltaic Systems Dual Land Use for Agriculture and Solar Power Pro-duction:Overview and Performance of Agrivoltaic Systems Report IEA-PVPS T13-29:2025 March 2025 ISBN 978-3-907281-70-3 Task 13 Reliability an

16、d Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 4 AUTHORS Main Authors Max Trommsdorff,Fraunhofer Institute for Solar Energy Systems ISE,Freiburg,Ger-many Pietro Elia Campana,Mlardalen University,Vsters,Sweden Jorda

17、n Macknick,National Renewable Energy Laboratory,Golden/Colorado,USA lvaro Fernndez Solas,German Aerospace Center,Institute of Solar Research,Cologne,Germany and Universidad de Jan,Jan,Spain Shiva Gorjian,Fraunhofer Institute for Solar Energy Systems ISE,Freiburg,Germany Ioannis Tsanakas,Alternative

18、Energies and Atomic Energy Commission,Institut Na-tional de lEnergie Solaire,Le Bourget-du-Lac,France Contributing Authors Stefano Amaducci,Universit Cattolica del Sacro Cuore,Piacenza,Italy Franz Baumgartner,Zurich University of Applied Sciences,Winterthur,Switzerland Karl Berger,Austrian Institute

19、 of Technology,Vienna,Austria Javier Diaz Berrade,Centro Nacional de Energas Renovables,Pamplona,Spain Dominika Chudy,University of Applied Sciences and Arts of Southern Switzerland,Manno,Switzerland Iaki Cornago,Centro Nacional de Energas Renovables,Pamplona,Spain Christian Dupraz,French National I

20、nstitute for Agriculture,Food,and Environment,Montpellier,France Eduardo F.Fernndez,Universidad de Jan,Jan,Spain Natalie Hanrieder,German Aerospace Center,Institute of Solar Research,Cologne,Germany Bert Herteleer,Katholieke Universiteit Leuven,Ghent,Belgium Erlend Hustad Honningdalsnes,Department o

21、f Solar Power Systems,Institute for En-ergy Technology,Kjeller,Norway Mike Van Iseghem,lectricit de France,Ecuelles,France Adam R.Jensen,Technical University of Denmark,Kgs.Lyngby,Denmark Jonathan Leloux,LuciSun,Villers-la-Ville,Belgium James McCall,National Renewable Energy Laboratory,Golden/Colora

22、do,USA Ildefonso Muoz,Centro Nacional de Energas Renovables,Pamplona,Spain Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 5 Magnus Moe Nygrd,Department of Solar Power Systems,Institute for Ene

23、rgy Tech-nology,Kjeller,Norway Silvana Ovaitt,National Renewable Energy Laboratory,Golden/Colorado,USA zal zdemir,Fraunhofer Institute for Solar Energy Systems ISE,Freiburg,Germany Alexis Pascaris,National Renewable Energy Laboratory,Golden/Colorado,USA Stephan Schindele,BayWa r.e.,Freiburg,Germany

24、Frederik Schnberger,Fraunhofer Chile Research,Santiago de Chile,Chile Bengt Stridh,Mlardalen University,Vsters,Sweden Jan Vedde,SiCon,Copenhagen,Denmark Editors Max Trommsdorff,Fraunhofer Institute for Solar Energy Systems ISE,Freiburg,Germany Pietro Elia Campana,Mlardalen University,Vsters,Sweden U

25、lrike Jahn,Fraunhofer Center for Silicon Photovoltaics CSP,Halle,Germany Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 6 TABLE OF CONTENTS Acknowledgements.7 List of abbreviations.8 Executive

26、 summary.11 1 Introduction and market overview.13 2 Terminology,classification,and key performance indicators.16 2.1 Terminology,definition,and classification.16 2.2 Key performance indicators of agrivoltaics.23 3 Modelling and simulation.30 3.1 Meteorological data for agrivoltaic system modelling.3

27、1 3.2 Software and methods for irradiance modelling.31 3.3 Tools and approaches for microclimate modelling.33 3.4 Approaches for crop modelling.36 3.5 PV yield modelling.38 3.6 Integrated platforms for irradiance,crop,and energy simulations.39 4 Monitoring.41 4.1 Overview of monitoring parameters fo

28、r agrivoltaic systems.41 4.2 Framework for agrivoltaics databases.44 5 Operation and maintenance.49 5.1 Agrivoltaic facilities maintenance practices.49 5.2 Soiling mitigation and vegetation management.52 5.3 Research and innovation outlook in operation and maintenance.55 6 Legal and socio-economic a

29、spects.57 6.1 Introduction and overview of agrivoltaic scope.57 6.2 Legal frameworks and policies addressing agrivoltaics.57 6.3 Social impacts and perspectives of agrivoltaics.63 6.4 Economic performance.67 6.5 Emerging trends in socio-economic and legal frameworks.72 6.6 Limitations,gaps,and futur

30、e opportunities of socio-economic and legal frameworks.73 Conclusions.75 References.77 Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 7 ACKNOWLEDGEMENTS This report received valuable contribut

31、ions from several IEA PVPS Task 13 members and other international experts.Many thanks to:Hugo Snchez,Anhalt University of Applied Sci-ences,Kthen,for reviewing the full report.This report is supported by the German Federal Ministry for Economic Affairs and Climate Action under contract no.03EE1120B

32、 and the German Federal Ministry of Education and Re-search under contract no.033L244A,the Danish Energy Agency through the Energy Technol-ogy Development and Demonstration Program(EUDP),grant no.134-22016,and the Swedish Energy Agency.This work was partially funded by the European Union under Grant

33、 Agreement No 101138374,as part of the SOLMATE project.The contribution from the United States was led by the National Renewable Energy Laboratory(NREL),which is operated by Alliance for Sustainable Energy,LLC,for the U.S.Department of Energy(DOE)under Contract No.DE-AC36-08GO28308.Funding was provi

34、ded by the DOEs Solar Energy Technologies Office.The views expressed in the article do not necessarily represent the views of the DOE or the U.S.Government.Inclusion and Diversity Statement:One or more of the authors of this paper self-identifies as an underrepresented ethnic minority in science.Tas

35、k 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 8 LIST OF ABBREVIATIONS ADEME Agence de la Transition cologique(French agency for ecological transi-tion)AFNOR Association Franaise de Normalization

36、(French norming organization)APER Acclration de la Production des nergies Renouvelables(French acce-leration law)APSIM Agricultural production systems simulator APV Agrivoltaics AC Alternating current BauGB Baugesetzbuch(German Building Act)BiPV Building integrated photovoltaics BOS Balance of syste

37、m CAP Common agricultural policy CAPEX Capital expenditure CEI Comitato Elettrotecnico Italiano(Italian norming organization)CERES Crop environment resource synthesis(crop model)CFD Computational fluid dynamics CO Carbon dioxide CROPGRO Crop growth(crop model)CWSI Crop water stress index DC Direct c

38、urrent DHI Diffuse horizontal irradiance DLI Daily light integral DNI Direct normal irradiance DSSAT Decision support system for agrotechnology transfer(crop model)EDF lectricit de France(French multinational electric utility company)EEG Erneuerbare-Energien-Gesetz(German renewable energy sources Ac

39、t)ENEL Ente nazionale per lenergia elettrica(Italys national electricity board)EPC Engineering,procurement,and construction EPIC Environmental policy integrated climate(crop model)EU European Union FAO Food and Agriculture Organization of the United Nations FAOSTAT Food and Agriculture Organization

40、Statistics Office FEM Finite element method FMEA Failure modes and effects analysis GCR Ground cover ratio GECROS Genotype-by-environment interaction on crop growth simulation(crop model)Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overvi

41、ew and Performance of Agrivoltaic Systems 9 GHI Global horizontal irradiance GMPV Ground-mounted photovoltaic systems GW Gigawatt IEA International Energy Agency IRR Internal rate of return kg Kilogram kg/m Kilograms per cubic meter KPI Key performance indicator kW Kilowatt kWh Kilowatt-hour LAI Lea

42、f area index LCOE Levelized cost of electricity LED Light-emitting diode LER Land equivalent ratio LPF Land productivity factor MASE Ministero dellAmbiente e della Sicurezza Energetica(Italian Ministry of Environment and Energy Transition)MOFA Ministry of Agriculture,Forestry and Fisheries(Japan)MWh

43、 Megawatt-hour NDVI Normalized difference vegetation index NPV Net present value NREL National Renewable Energy Laboratory(U.S.)O&M Operations and maintenance OECD Organization for Economic Cooperation and Development OPEX Operating expenses OSCs Organic solar cells PAR Photosynthetically active rad

44、iation PR Performance ratio PV Photovoltaics PVPS Photovoltaic Power Systems Programme R&D Research and development ROI Return on Investment SAM System advisor model SIMPLE Simple generic crop model(crop model)STICS Multidisciplinary simulator for standard crops(crop model)TCP Technology Collaborati

45、on Programme UNI Ente Nazionale Italiano di Unificazione(Italian national standardization body)USA United States of America Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 10 WP Water productiv

46、ity WUE Water use efficiency Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 11 EXECUTIVE SUMMARY Our food and water systems are highly vulnerable to the impacts of projected climate change.At

47、the same time,there is an urgent need to decarbonize the energy sector by rapidly and sustainably expanding photovoltaic(PV)systems.Given the alarming rate of species extinction caused by human activities and the subsequent loss of biodiversity,these challenges under-score the necessity for innovati

48、ve land use concepts to tackle these interconnected crises.Ground-mounted PV(GMPV)systems are one of the most cost-competitive solutions among renewable energy conversion technologies,but with the disadvantage of typically requiring more land per produced kWh compared to other technologies like wind

49、 power,hydropower,or geothermal power 1,2.Moreover,the typically high land lease prices for GMPV systems can be beneficial to single farmers while reducing the available area for agricultural production,leading to societal challenges threatening the acceptance towards the deployment of GMPV and pote

50、ntially leading to restrictive legislations to prevent losses of fertile farmland.Agrivoltaics offers the possibility to simultaneously use land for agriculture production and solar power generation and provides opportunities to think beyond the way we have installed GMPV over the last two decades.T

51、he shading produced by the PV modules can increase the resili-ence of agriculture by protecting crops or animals against the rising number of severe weather events or,in agricultural applications with low intensity,can provide habitats for flora and fauna to mitigate biodiversity losses.Additionally

52、,agrivoltaics can reduce water consumption and provide attractive business models enabling a more sustainable expansion of PV in accord-ance with local stakeholders and the farming sector.Driven by the great diversity of agricultural practices and applications,the ongoing market launch has led to a

53、vast variety of different technological approaches ranging from open systems on permanent and horticulture crops,arable farming,or permanent grassland,to closed systems like PV greenhouses.This report provides a comprehensive overview of the definition of agrivoltaics,its current state of global res

54、earch and development activities,with a focus on open questions regarding tech-nical performance.The presented research activities aim to optimize design through integrated modelling and simulation approaches.Creating a common understanding of agrivoltaics seems key at this early stage of the market

55、 uptake.Though,the diversity of agricultural applications represents a challenge for the defini-tion of agrivoltaics which varies globally,influenced by legislative,historical,and societal fac-tors.More narrow definitions typically focus on productive agriculture(e.g.,food,fiber,dairy),while wider d

56、efinitions also include non-productive agriculture(e.g.,ecosystem services).Countries with a narrower definition like Japan,Germany,and France have also set minimum agricultural production requirements to ensure the agricultural relevance of agrivoltaic sys-tems.In the United States of America,in co

57、ntrast,there is no clear definition of federal level resulting in a rather wide definition that also includes non-productive agriculture activities.While broader definitions encompass a wider variety of technological approaches by also con-sidering systems that are technically and economically like

58、GMPV,this may diminish the agri-cultural relevance,potentially undermining the concept of dual land use.In contrast,narrower definitions often demand more technical adjustments,resulting in higher costs compared to GMPV.For example,overhead systems used in horticulture,which generally offer higher a

59、g-ricultural value,tend to have greater investment costs than interspace systems designed for arable or grassland farming.To meet some countries legal definitions of agrivoltaics,predicting the agricultural perfor-mance based on different agrivoltaics designs represents a crucial task before the ins

60、tallation of a system.While several modelling and simulation approaches have been discussed,only Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 12 very few software or a combination of softwar

61、e is available to clearly address the markets needs.One main challenge is to enable comprehensive models of agrivoltaics that analyse crop relevant factors like light and water availability and the energy performance of the sys-tems.Unlike traditional agriculture or PV systems,monitoring of agrivolt

62、aic systems requires the as-sessment of a much broader range of parameters.This task is especially complex due to the interactions between agricultural and PV-related factors.While a standardized monitoring can help to reduce this complexity,varying research questions and individual local conditions

63、 often demand for adjusted monitoring concepts.This report includes a guide to monitoring parame-ters commonly used to evaluate the overall performance of agrivoltaics systems and their re-spective relevance.Additionally,it provides an overview of existing regional databases of agri-voltaic faciliti

64、es and proposes a framework for the global expansion of these databases to include installations worldwide.Regarding operation and maintenance,this report provides an overview of common practices and challenges focusing on the PV components of agrivoltaic systems.Main identified aspects are soiling

65、and increased damages or corrosivity of PV components due to farming activities and plant protection agents.Due to the few performed R&D works on existing projects and the resulting thin database,many questions remain still open.Future research could explore cus-tom-designed farm equipment that can

66、successfully operate within agrivoltaic facility configu-rations,anti-soiling technologies,integrated irrigation and PV module cleaning technologies,and novel tracking algorithms to reduce O&M costs.The report also addresses legal and socio-economic aspects by summarizing the legal frame-work of six

67、 pioneer countries in Asia,Europe,and North America,highlighting main findings of factors influencing societal acceptance among different stakeholder groups,and providing an overview of the economic performance of agrivoltaic systems.Key drivers identified for suc-cessful project implementation are

68、stakeholder involvement in an early stage,a supportive policy environment and incentive programs,and transparent performance standards.Also,the increasing importance of societal acceptance underpins the need to address existing limita-tions,gaps,and future opportunities of socio-economic and legal f

69、rameworks.Earlier works on agrivoltaics of the IEA PVPS addressed performance indicators and presented a showcase from Germany1.To reach our climate goals,there are strong arguments in favour of using both GMPV systems and agrivoltaics.A primary challenge for policymakers is choosing the appropriate

70、 technolo-gies by aligning local land use goals with national and global PV development goals.In areas where agrivoltaics provides agricultural benefits high enough to justify higher cost,agrivoltaics should generally be preferred.However,regional factors may shift the balance,influencing the value

71、of each approach.Given the wide variety of agrivoltaic technologies and the current limitations in accurately assessing key factors,an interdisciplinary collaboration through exist-ing and future IEA PVPS Tasks would be valuable to address the diverse aspects of agrivolta-ics technology.1 See IEA-PV

72、PS Report T13-15:2021 Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 13 1 INTRODUCTION AND MARKET OVERVIEW Since the early 1960s,the world population has doubled and is projected to reach 9.8

73、billion people by 2050.This rapid growth is expected to intensify the global challenge of food security,one of the most critical sustainable development goals 3.Food security is additionally chal-lenged by climate change with its increasing frequency of droughts and severe weather posing significant

74、 risks to agriculture production 4.At the same time,areas for the installation of GMPV are urgently needed to reduce greenhouse gas emissions and enable the transition to a decarbonized economy 5.While GMPV systems are economically highly competitive with other energy conversion technologies,they ta

75、ke up significantly larger areas of land compared to other renewable energy technologies like wind turbines or fossil energy sources 1,2.This issue is especially relevant in densely populated countries with low availability of fertile agri-cultural regions where compromising on agricultural producti

76、on represents an increasing ob-stacle for PV developers.Effective conservation strategies must be implemented to protect and restore natural habitats,promote sustainable land use,and reduce human-induced pres-sures on ecosystems.Such actions are critical for preserving biodiversity and maintaining e

77、co-system services that are vital for human well-being and the planets health 6.One solution to these challenges is integrating PV into multifunctional land use concepts that allow for agricultural or nature conservation actions while generating electricity 7,8.This way,land can be used more efficie

78、ntly for several purposes while societal acceptance of the expan-sion of PV can be maintained.The idea of agrivoltaics to enable the co-production of agriculture and PV electricity on the same land was first introduced in 1981 by Goetzberger and Zastrow 9.After several years of research and developm

79、ent,the global market for agrivoltaics has experienced significant growth from around 5 Megawatt peak(MWp)in 2012 to an estimated 14 Gigawatt peak(GWp)in 20212 10,11.This progress has been made possible mainly by government support initia-tives,e.g.,in Japan(since 2013),China(around 2014),France(sin

80、ce 2017),the USA(since 2018),Germany(since 2019),and Italy(since 2023,see Figure 1).Figure 1:Timeline of the development of agrivoltaics 22 Agricultural applications and the associated technical approaches differ significantly from country to country.Subsidy programs in Japan have led to more than 4

81、000 small overhead systems tailored for horticulture and arable farming with an average system size of less than 0.1 hectares and often using special thin PV modules to achieve homogeneous light distribu-tion at the crop level 12,13.In contrast,the USA market is mainly driven by large interspace 2 T

82、hese figures follow a narrow definition of agrivoltaics only considering systems with a significantly different design than GMPV.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 14 systems on pe

83、rmanent grassland,focussing on pollinator-friendly grass mixtures,beekeeping,or sheep grazing as extensive agricultural activities 14.This integration allows the systems to be configured as conventional GMPV systems,making them cost-competitive and inde-pendent from government subsidies 1517.An earl

84、ier IEA PVPS report already addressed performance indicators and presented a showcase from Germany,see Chapter 4.5 Perfor-mance indices for parallel agricultural and PV usage and Chapter 5.3 Performance of agri-voltaics systems:a showcase from Germany of report IEA-PVPS T13-15:2021.Figure 2:Some of

85、the different agrivoltaics approaches.a)Top left:Large scale facility in China with moderate higher vertical clearance compared to GMPV,Fraunhofer ISE;b)top right:Agrivoltaics in French viticulture;SunAgri;c)bottom left:Apple farming in Germany,Fraunhofer ISE;d)bottom right:Agrivoltaics with sheep g

86、razing in USA,Lindsay France,Cornell University.A more comprehensive classification of agrivolta-ics can be found in Chapter 2.Due to the wide range of agricultural practices and the resulting variety of integrating PV into agricultural activities or vice versa(see Figure 2),there is no“one-fits-all

87、”approach,and de-fining uniform requirements for agrivoltaics remains challenging.To provide a better overview of the diversity of agrivoltaics,Chapter 2 of this report sheds light on definitions,classifications,and where to draw the line between agrivoltaics and GMPV.Governmental support initiative

88、s typically include legal definitions that set minimum require-ments for the intensity of agricultural land use involved,e.g.,a certain threshold of agricultural yield or a minimum share of land dedicated to farming.To meet such requirements,modelling and simulating the impact of PV systems on agric

89、ultural performance represents a central ex-ercise when designing an agrivoltaic system.To address the rising number of tools and the need to predict agricultural yields in agrivoltaic systems,Chapter 3 provides a comprehensive overview of modelling and simulation approaches for optimizing agrivolta

90、ic system designs.Since agrivoltaics is still in its infancy and most of the existing facilities have only been operat-ing for a few years,Chapter 4 and Chapter 5 address first experiences and open questions of monitoring,operation,and maintenance issues.Both chapters also address first experiences

91、Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 15 and open questions of monitoring and control schemes as well as operation and maintenance issues.Chapter 4 and Chapter 5 also include a summar

92、y of monitoring parameters,a frame-work for agrivoltaics databases,optimized tracking algorithms,and failure modes and effects analysis.Challenges in the market uptake for agrivoltaics include higher levelized cost of electricity(LCOE)compared to GMPV,higher communication efforts for intersectoral c

93、ollaboration,ac-ceptance losses in case of insufficient level of agricultural activities,and regulatory barriers that may arise due to an unclear land status.Chapter 6 provides an overview of legal frame-works in pioneer countries and how they tackle those challenges.It also addresses socio-economic

94、 aspects highlighting opportunities of stakeholder involvement as well as gaps,limi-tations,and emerging trends of socio-economic and legal frameworks.In summary,the global market for agrivoltaics is poised for continued growth as players recognize the economic,en-vironmental,and social benefits of

95、integrating agriculture and solar power conversion.As tech-nology advances and awareness increases,agrivoltaics will likely play an increasingly im-portant role in the transition to more sustainable and resilient energy and agricultural systems worldwide.Task 13 Reliability and Performance of PV Sys

96、tems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 16 2 TERMINOLOGY,CLASSIFICATION,AND KEY PERFOR-MANCE INDICATORS 2.1 Terminology,definition,and classification Given the growing interest and the various open questions and challenges in agri

97、voltaics,con-sistent and precise terminology is a prerequisite for efficient and transparent communication.Various terms have been introduced to describe the concept of agrivoltaics.Promoted by pio-neer Akira Nagashima,since 2003,Japan has used the term solar sharing to refer to agri-voltaics 18.In

98、2011,the term agrivoltaics was introduced by Christian Dupraz et al.in their paper Combining solar photovoltaic panels and food crops for optimizing land use:Towards new agrivoltaic schemes 7.It was the first time a terminology for agrivoltaics was suggested in a peer-review paper.The term agrivolta

99、ics represents a fusion of agriculture and photo-voltaics,symbolizing the combination of agricultural activities with the conversion of solar en-ergy.Since 2011,Chinas regulatory framework has supported agrivoltaics,sometimes refer-ring to it as PV+19.In Germany,the term agrophotovoltaics was introd

100、uced by Fraun-hofer ISE,drawing parallels with established agricultural practices such as agroforestry,agro-fuels,and agroecology 20.Today,the standard term in the German language is“Agri-Photo-voltaik(Agri-PV)”21,22.In Italy,variants such as agrofotovoltaico or agrivoltaico are used 2325,while in F

101、rance,the standard term is“agrivoltasme”26.Figure 3:Terminologies used in publications until May 2024(n=635).While beside agrivoltaics also other terms describe the same concept in the English lan-guage,e.g.,agriphotovoltaic(s)or agrovoltaics,a review of 635 peer-reviewed papers shows a consensus in

102、 science to use the term agrivoltaics(see Figure 3).Looking at the de-velopment of the terms used over time,as shown in Figure 4,before 2020,it was not clear whether agrophotovoltaics or agrivoltaics were used more often.Since then,though,the growing scientific community has aligned increasingly wit

103、h a clear majority of 85%of papers published in the first five months of 2024 using the term agrivoltaics(n=68).Regarding spelling and grammar,agrivoltaics is generally not regarded as a proper noun and is therefore not capitalized.Analogous to photovoltaics,agrivoltaics is a singular term,and the a

104、djective form is agrivoltaic.Standard abbreviations are AV,AVS(for agrivoltaic systems),APV,or agriPV(both for agriphotovoltaics),with the latter appearing in different spelling variants(Agri-PV,agri-PV,AgriPV),see for instance Chatzipanagi et al.27.In this report,we use agrivolta-ics in the text an

105、dwhere neededthe abbreviation APV in graphs or tables.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 17 Figure 4:Terminology used in scientific publications per year.The number of publica-tion

106、s mirrors the growing interest in the technology and the trend to use agrivoltaics as the standard term.While all these terms and abbreviations can be considered synonyms,their respective regional backgrounds might indicate slightly different concepts.Regarding the definition of agrivoltaics,next to

107、 clear terminology,creating a shared under-standing of agrivoltaics represents a crucial task in harnessing its full potential.This necessity is particularly underpinned by the high number of involved stakeholders,the novelty of the technology,and the great diversity of agriculture that results in a

108、 wide range of agrivoltaics concepts and applications.Also,the need to adjust the legal framework to overcome legal barriers identified in several countries 20 highlights the importance of setting criteria defining agrivoltaics in its different variants.Such criteria,which should be at least partial

109、ly measurable and verifiable,reduce ambiguities and pave the way for implementing agrivoltaics policy frame-works by guiding policymakers on differentiating agrivoltaics from GMPV and implementing control and sanctioning mechanisms.Similarly,for farmers,industry stakeholders,and re-searchers,a commo

110、n understanding supports the adoption of agrivoltaics on a broader scale by increasing transparency,improving communication,facilitating cross-study comparisons,and identifying and promoting best practices.The baseline of an agrivoltaics definition is the colocation of agriculture and PV power produ

111、c-tion 7,9,22,28.While earlier concepts of agrivoltaics understood colocation as a dual land use on two layers,i.e.,high elevated PV modules with agriculture activity below,for some years,a more comprehensive definition also considers concepts that use the space between PV modules installed on groun

112、d level from 29(see Figure 5).Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 18 Figure 5:(a)Overhead agrivoltaic system with fixed modules.(b)Interspace agrivoltaic system with fixed modules a

113、nd sheep grazing.Illustrations from Bir-Varga et al.29.This distinction between overhead and interspace systems suggests that a common under-standing of agrivoltaics should include both narrower and broader definitions.This would facil-itate the identification of trends in cost,land use efficiency,t

114、echnical designs,or other aspects related to the different system approaches or application areas.To ensure the co-locating character,it may be useful to set a limit in the spatial distribution of the land parcels for interspace systems.One possible requirement could be significant inter-actions bet

115、ween the agricultural and the PV areas 14.If the agricultural and the PV land parcels are too far from each other so that no significant interactions exist,it seems not plau-sible to consider such systems as agrivoltaics.However,a concrete quantification of the allowed spatial distribution depends o

116、n several fac-tors,e.g.,the kind of agricultural activity and the local land structure.This example already indicates that whether a project can be considered agrivoltaics or not is ultimately decided on the project level.Beyond the colocating character of a project,the two involved land use activit

117、ies,agriculture,and PV power production,must be clarified and specified.While the definition of PV power generation is generally less challenging than that of agriculture activities,the fusion of agri-culture and photovoltaics represented in the term agrivoltaics implies that solar energy projects o

118、nly qualify as agrivoltaics if they include PV technologies.However,solar energy projects such as solar thermal or concentrated solar power exhibit several aspects that could justify considering them as agrivoltaics.Notably,the constructive design and the general visual appearance of larger solar th

119、ermal projects can be very similar to agrivoltaic systems.Even though the relevance of those projects is still minor,not considering them might restrict their access to existing legal frameworks for agrivoltaics,hence curtailing their future potential of(a)(b)Task 13 Reliability and Performance of P

120、V Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 19 combining them with agricultural land uses.This example might support a broader understand-ing of agrivoltaics concerning the solar energy technologies employed.Regarding agriculture

121、,the wide range of land use forms suggests specifying in more detail which agricultural activities qualify as such in the light of agrivoltaics.One definition criterion frequently used for defining agrivoltaics is the solar sharing character,implying a simultaneous involvement of photosynthesis and

122、PV 14,22.Following this criterion,PV rooftops on barns or staples cannot be considered agrivoltaics.The same holds for the indoor cultivation of mush-rooms.Despite the Japanese origin of the term solar sharing,the Japanese regulation consid-ers mushroom cultivation an agrivoltaic activity 13.This cr

123、iterion needs to be further clarified in animal husbandry.Marketable products like meat,milk,or eggs are only indirectly the result of photosynthetic processes.Even more ambiguous,supplementary fodder sources can reduce the relevance of the involved photosynthesis in the area to a neglectable level,

124、e.g.,in the case of poultry raising.In intensive livestock farming,no feed can grow on the land due to the animals high stocking density.In aquaculture applications,the situation is similar.Although the cultivation of aquatic plants,such as algae or lotus,directly involves photosynthesis,the product

125、ion of aquatic animals like fish,crustaceans,and molluscs relies on photosynthetic processes only indirectly and only when algae contribute to their feed composition 30.In animal husbandryboth on land and in water bodiesthough,complying with the solar sharing character might not only be limited to p

126、hotosynthetic processes since,arguably,sunlight is also relevant for the animals for orien-tation,well-being,and health.Similarly,agrivoltaic systems that focus on biodiversity enhancement or beekeeping directly or indirectly depend on photosynthetic processes.Some biodiversity-enhancing measures,li

127、ke the establishment of stone walls or wetland habitats,might even reduce the overall level of photosynthetic processes in the area compared to a GMPV on permanent grassland.On the other hand,the ultraviolet light spectra could be important for pollinators to orient themselves and identify flowers.W

128、hile showing several differences to open agrivoltaic systems,PV green-houses clearly meet the solar sharing criterion.Other indoor farming methods with opaque building envelopes that involve photosynthetic processes powered by artificial lighting,such as vertical farming,represent another ambiguous

129、application as the sunlight is not instantly shared.Here,an additional requirement for qualifying as an agrivoltaic could be that on-site electricity powers artificial lighting.Accordingly,the solar sharing criterion,which involves photosynthesis and PV,is fully met only in plant cultivation,while a

130、pplications of animal husbandry,aquaculture,biodiversity-promoting measures,or vertical farming comply with it only partially or not at all.Another definition criterion for agrivoltaics is primarily agricultural land use 21.However,de-termining whether the land is used primarily for agriculture or P

131、V is not easy.Indicators for primary land use can be the respective political land use goals,the administrative and actual status of the land,the intensity of agricultural land use,and the degree of involvement of agri-cultural stakeholders 14,20,31,32.While the administrative and the actual land st

132、atus should ideally reflect the respective political land use goals of an area,in practice,there is often a gap between both,e.g.,when political goals change more swiftly than the administrative status adjusts.In agrivoltaics,political land use goals seem particularly relevant concerning conflicting

133、 environmental protection goals and agricultural productivity.Following the definition criteria of the simultaneous involvement of photosynthesis and PV,agrivoltaics,in a narrow understanding,focuses on productive agri-cultural activities,e.g.,food,fibre,or feed production.If an agricultural areas p

134、olitical goal or Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 20 administrative status focuses on environmental protection,non-productive agricultural activi-ties,e.g.,the increase of soil o

135、rganic matter,biodiversity,and other ecosystem services,might arguably represent a primary agricultural land use.If land use goals are not sufficiently defined by policy or administrative status,they might be derived from previous land use activities.Sup-pose the area is not officially classified as

136、 agricultural land from a legal point of view,it seems impossible to fulfil the definition criterion of primary agricultural land use even if the land is used for agriculture.In this case,the first step is to acknowledge the agricultural status of the land formally.If an area is classified as agricu

137、ltural land,the most common method to ensure its primary agricultural use is to verify whether the agricultural activity is sufficiently intense 24,3133.There are generally two approaches to verifying the level of agricultural activity:first,setting criteria for the intensity of the agricultural act

138、ivity;second,restricting the intensity of PV land use.The reasoning for disregarding PV intensity is that as long as the integration of PV sys-tems does not significantly impede the primary agricultural use of the land,the original char-acter of the land use remains unchanged.Additionally,this appro

139、ach ensures that technical innovations are not curbed,allowing for both high agricultural and high PV intensity 20.Typ-ical parameters for ensuring a sufficient intensity of agriculture are the level of agricultural yield,the share of the area under agricultural cultivation,or the economic value of

140、the agricultural activity 31,32,34,35.Within open applications on plant cultivation,overhead systems on permanent and horticulture crops typically show the highest intensity of agriculture measured by those parameters 36,37.To quantify the intensity of agricultural activity,the former land use or co

141、mparable agricultural cultivation can serve as a reference.However,determining the primary land use out of two collocating activities might also consider the relation of both activities.The definition of primary land use is implicit in several legislations that additionally restrict the intensity of

142、 PV land use 25,31,32,38 A potential reason for limiting PV intensity,especially in applications on arable land,is the competition for sunlight and space,which creates a trade-off between agricultural and PV land use.This competition occurs when the shading from PV modules restricts plant growth 36,

143、or when the installation of PV components hinders the use of machinery.Another argument is thatespecially in ecovoltaics or applications with animal husbandrythe respective revenue shares incentivize favouring a higher installed PV capacity over agricultural performance,marginalizing the agri-cultur

144、al activity in the design phase 20.An overview of revenue shares of different agrivoltaics applications is illustrated in Figure 17 in Section 6.4.2.Typical parameters to restrict the inten-sity of the PV land use are the level of shading or the PV module ground cover ratio(GCR),which is discussed i

145、n Table 3 of Section 2.2.2 20,39.While compliance with such parameters is relatively easy to control,they might lead to higher costs without considering the specific needs of the respective agricultural applications 20,40.Finally,the involvement of agricultural stakeholders can also contribute to th

146、e primary agricultural land use character of agrivoltaic projects.One example of how this can be specified comes from the French Agency for Eco-logical Transition(ADEME),which suggests the participation of an active farmer to ensure that agricultural perspectives are sufficiently considered,e.g.in t

147、erms of financial decision-making 32.Further definition criteria are increased land use efficiency,synergies,and interactions be-tween agriculture and PV power production 14,20,31,32.Closely related to the collocating character discussed above,land use efficiency is typically measured by the land eq

148、uivalent ratio(LER).Unlike the primary agricultural land use criterion,the LER always considers elec-trical yield.For non-productive agrivoltaics,the calculation of the LER is challenging and seems only meaningful when considering the efficiency of a land area in providing ecosystem ser-vices.Notabl

149、y,a minimum intensity level of the PV land use plays no or only a minor role in Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 21 defining agrivoltaics in most legislations1.Table 1 of Section

150、 2.2.2 presents more details of the LER.The degree of synergies and interactions reflects the level of integration between the two land use activities.While interactions can include adverse effects,synergies refer to interactions where at least one of the activities benefits.Accordingly,synergies ar

151、e a subset of interactions.Although synergies and interactions often contribute directly to land use efficiency,quantifying them can be challenging.This challenge is due to the need to account for and compare a potentially high number of parameters and site-specific effects that manifest in various

152、areas or dimensions.Dual land use applications that do not sufficiently meet the definition criteria of agrivoltaics can be summarized under the term agrisolar 28.This term is sometimes used to refer to a broader range of solar power technologies within an agricultural context.It represents a broad

153、definition of agrivoltaics,encompassing,for example,PV installations on opaque buildings and solar energy projects that do not involve PV technologies.Figure 6 illustrates a hierarchy of narrower and broader definitions of agrivoltaics,summarizing the discussion above.Systems and applications are ra

154、nked based on the extent to which they meet the four main criteria:(i)land use efficiency,(ii)photosynthetic processes,(iii)intensity of agricultural activity,and(iv)the synergies and interactions involved.Another ranking could happen by using other criteria or considering local factors like climate

155、 or soil quality.Figure 6:Definition hierarchy of agrivoltaics.Systems and applications are ranked after their level of fulfilling the four main definition criteria.The level of fulfillment can vary depending on the specific crops or other factors of the respective systems and appli-cations.This is

156、represented by triangles of distinct colors.Fraunhofer ISE To structure the manifold variants of narrower or broader definitions for agrivoltaics,a classifi-cation of the respective technical approaches and agricultural applications helps to gain a bet-ter overview of the diversity of agrivoltaics.T

157、he first attempt to classify different agrivoltaic systems dates to a work by Lasta and Konrad in 2018 41.Later revisions of this work,carried 1 Italy represents an exception with a required installed PV capacity of at least 70%compared to average GMPV 35.Task 13 Reliability and Performance of PV Sy

158、stems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 22 out by Willockx et al.42 also consider common approaches with tracked or non-tracked in-stalled PV modules.Figure 7 illustrates a revised version of a more recent classification in Tromm

159、sdorff et al.43and Gorjian et al.97 that distinguishes between open and closed sys-tems and identifying hybrid forms also considering extensive agriculture and indoor farming as broader definitions of agrivoltaic systems.The authors classified agrivoltaics by system type(closed or open),structure ty

160、pe(overhead PV,interspace PV),module tilt(non-tracking,sin-gle-axis tracking,dual-axis tracking)and application type(permanent grassland,arable,horti-culture,aquaculture).Ma Lu et al.44 added a further layer to the classification to reflect the transparency of the PV modules deployed in agrivoltaic

161、applications with three subcategories:opaque,semi-transparent,and transparent.Figure 7:Classification of agrivoltaic systems according to Trommsdorff et al.43 based on the original version of Gorjian et al.97.Green boxes represent open agri-voltaic systems,blue boxes represent closed systems,and gre

162、en-blue boxes indicate that these applications can be either open or closed systems.GMPV projects sited on land that is typically unsuited for agricultural production-such as contaminated land or areas with low fertility-are likely to be more readily accepted by local stakeholders.These sites are pa

163、rticularly suitable for low-intensive agrivoltaic systems that aim to enhance biodiversity and improve the ecological value of the land.If low soil fertility is the result of degraded soils suffering from low water availability,agrivoltaics could enable soil fertility to be restored by reducing evap

164、otranspiration,increasing soil moisture,and thus in-creasing carbon fixation.While previously tilled and intensively used agricultural land is usually well suited for overhead or interspace agrivoltaics projects focusing on agricultural production,from an ecological point of view,those areas represe

165、nt a remarkably high potential for improv-ing local biodiversity.In contrast,greenfield sites that have not been used in the past for human use and that show a high ecological value should instead not be considered for the develop-ment of either agrivoltaics or GMPV to not exacerbate the ongoing ant

166、hropogenic biodiversity crisis.Several terms were introduced to specify agrivoltaics applications in more detail,e.g.,cropvol-taics,fruitvoltaics,cowvoltaics,chickenvoltaics,or ecovoltaics.Such specifications are chal-lenged when agricultural activity might change during the operation of the systems

167、.To a lower extent,this might however also be the case for the general classes illustrated in Figure 7.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 23 2.2 Key performance indicators of agriv

168、oltaics To ensure high quality in agrivoltaics project development,minimize risks for both farmers and PV developers,and provide a comprehensive report on the agricultural concept within the project,it is essential to establish clear key performance indicators(KPIs).These KPIs serve as critical benc

169、hmarks to guide project success,streamline processes,and provide transparency throughout the projects lifecycle.Furthermore,policymakers also need guidance on how agrivoltaics projects can be differentiated from GMPV,not only legally,but also by control mechanisms that can be evaluated and benchmark

170、ed.A reduction in ambiguity increases the probability of the introduction of a holistic agrivoltaics policy framework on a national level.Key metrics of agrivoltaic systems could be classified into yield,cost,and design metrics.2.2.1 Yield and cost KPIs Table 1 lists yield KPIs distinguishing electr

171、ical,agricultural,and combined yields.Table 2 presents cost KPIs also considering environmental impact.Table 1:Yield KPIs of agrivoltaic systems.Electrical yield KPIs Parameter Explanation Performance Ratio(PR)The PR is given by the ratio between the actual annual electrical energy yield and the the

172、oretical annual energy yield.Specific yield The electrical yield as electricity produced per nominal power is key in sev-eral financial analyses typically indicated as kWh/kWp.Energy yield per area Represents the ratio between the energy conversion and the total land area of the system over a period

173、.It provides insights into the final electrical yield of different agrivoltaic configurations by allowing direct comparison between distinct systems 42.Agricultural yield KPIs Parameter Explanation Agricultural yield per area Represents the ratio between the agricultural output and the total land ar

174、ea of the system over a period.The typical agricultural outputs are fresh bio-mass and dry biomass 42.The amount of biomass can be measured through different approaches:(i)using hand-collected samples across var-ious small plots,(ii)employing remote sensing techniques like Normalized Difference Vege

175、tation Index(NDVI)from drones,and(iii)using harvesting machines that record harvest yields over extensive areas.The agricultural yield is typically averaged over multiple seasons.Environmental yield KPIs Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power

176、Production:Overview and Performance of Agrivoltaic Systems 24 Parameter Explanation CO2 capturing CO2 captured due to the growth of the crops.Financial yield KPIs Parameter Explanation Annual finan-cial return Measures the percentage change in an investments value over a year,reflecting income and c

177、apital gains or losses.It shows the profit or loss earned relative to the initial investment.For agrivoltaics,the annual return typically includes income from selling electricity and agricultural products.Return on in-vestment(ROI)Ratio between net income and investment.In agrivoltaics,this typicall

178、y re-fers to the income generated by electricity and agricultural sales over the operation period of the facility divided by agricultural and electrical invest-ments.Combined yield KPIs Parameter Explanation Land Equiva-lent Ratio(LER)Indicator that can be used to calculate the land use efficiency i

179、n agrivoltaic systems.It represents the sum of the relative agricultural yield and the rel-ative PV energy conversion.The relative agricultural yield is the ratio be-tween the yield of the agrivoltaic system and the yield of a traditional mono-cropping system.The relative PV energy production is cal

180、culated as the ratio between the energy converted per area in the agrivoltaic system and the energy converted per area in a traditional GMPV.An LER1 indicates that the agrivoltaic system provides a gain versus separate PV and agri-cultural activities occupying the same land area 7.Land Produc-tivity

181、 Factor(LPF)Evaluates the productivity of agrivoltaic systems by considering the sum of the relative yields of energy conversion and the accumulated PAR reaching the crops 45.Water Produc-tivity(WP)Represents the ratio between the agricultural plant/biomass production and the total amount of water c

182、onsumed by the crops(actual evapotran-spiration),expressed in kg/m 46.Plant transpiration is the process that allows crops to regulate their temperature and is strongly linked to the pho-tosynthesis process.The combination of both soil evaporation and plant transpiration is called evapotranspiration

183、.The higher the value of WP,the more effective water is used for agricultural production.At the plant pro-duction system level,a decrease in consumed water can be directly trans-lated to water savings,and an increase in productivity can be attributed to improved management practices that address the

184、 specific plant physiology of the crops 47.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 25 Water Use Ef-ficiency(WUE)Unlike other efficiency indicators,WUE is not a dimensionless ratio but r

185、epresents the product/gross water available or applied(rain+irrigation).It should only be used on plot or field level as a measure of localized effi-ciency.However,it does not allow allocation of what the water is used for or where it went.The methodology is easier to use than those of WP as it is n

186、ot required to calculate actual evapotranspiration 48,49.Table 2:Cost KPIs of agrivoltaic systems.Environmental costs KPIs Parameter Explanation Relative mate-rial consump-tion Materials used(e.g.,metal,concrete)for the mounting structure,per kWp PV nominal power.Carbon foot-print of the mounting st

187、ructure Represents the carbon emissions associated with the production of elec-tricity from agrivoltaic systems from the point of view of the mounting struc-ture.Typically,in agrivoltaic facilities,the mounting structure needs to be adapted to the crops and the agricultural management.In some cases,

188、this implies the use of more kg of steel per kWp,which can increase the carbon footprint when compared against traditional GMPV 50.Financial cost and levelized costs KPIs Parameter Explanation Levelized Cost of Electricity(LCOE)Index used to quantify the cost of producing a kWh of electricity throug

189、h an agrivoltaic installation 51.It is typically employed to compare different en-ergy conversion technologies.Also,it can be utilized to economically as-sess various agrivoltaic configurations and technologies 52.The LCOE does not consider agricultural production.Net Present Value(NPV)Expresses the

190、 profitability of an investment and is calculated as the differ-ence between the net present value of cash inflows and cash outflows.Its value is positive if the investment returns a profit over a defined period 53.Capital expenditure(CAPEX)Refers to the initial costs associated with establishing an

191、 agrivoltaic sys-tem.This type of CAPEX involves a wide range of investments that are necessary for both the energy and agricultural aspects of the system,often requiring more complex infrastructure than either sector alone.Operating expenses(OPEX)Refer to the ongoing costs required to run and maint

192、ain an agrivoltaic sys-tem.Unlike CAPEX,which covers initial investments in long-term assets,OPEX focuses on the day-to-day operational expenses necessary to keep the system functioning efficiently.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Produc

193、tion:Overview and Performance of Agrivoltaic Systems 26 2.2.2 Key design metrics Local environmental and climatic conditions,crops,farming systems,and socioeconomics in-fluence the design of an agrivoltaic system.In general,the layout of the system configuration needs to be optimized to allow suffic

194、ient sunlight to reach the underlying crops.The layout depends on the amount of solar irradiation at the location and the shade tolerance of the target crops.In an area receiving high solar irradiation(and PAR),a denser PV module layout would be possible when growing shade-tolerant crops compared to

195、 an agrivoltaic system at higher latitudes and with less shade-tolerant crops underneath 21.The same applies to water-stressed regions where the limiting factor for plant growth is water instead of sunlight.For interspace PV,the pitch distance(row-to-row spacing)needs to be set at a distance that al

196、lows agricultural activity to be adequately conducted.The system design should ensure that any machinery used can pass unobstructed through the rows,avoiding damage to the PV infra-structure.For overhead systems,the height of the PV modules that will facilitate farming un-derneath depends on the pla

197、nned crops and cultivation methods.Taller crops and mechanized farming will need a taller PV module mounting structure than shorter,hand-picked crops.Even where large agricultural machinery is not used,PV modules might need to be placed high enough to avoid a negative impact on plant growth 30.Besid

198、es the agricultural considera-tions,the vertical clearance of overhead systems are crucial economic and technical factors(i.e.,wind load)also affecting social acceptance(i.e.,system aesthetics)and environmental impacts.The orientation of PV modules affects how much sunlight they receive,as well as h

199、ow dust and dirt accumulate on them(see Chapter 5.2.1).Also,the orientation can influence the bal-ance between solar energy conversion and agricultural production throughout the day or year.For example,vertically installed bifacial PV modules facing east and west primarily generate electricity in th

200、e morning and evening.This design leaves midday sunlight fully available for crop photosynthesis.Generally,fixed tilt PV systems are oriented towards the equator to opti-mize sun exposure,facing south in the northern hemisphere and north in the southern hemi-sphere.However,this equator-facing orient

201、ation results in an uneven distribution of sunlight to the crops below the PV modules.Adjusting the orientation to either northwest,northeast,or east-west further improves light distribution below the PV modules and enhance homogeneity 57.Regarding shifts of the production focus within a year,higher

202、 tilt angles in an equator-facing fixed-tilt PV system can increase electricity production during winter while providing more sunlight for crops during summer.Different PV module technologies can be used for agrivoltaics.Higher efficiency and lower weight must be balanced with the PV module price,as

203、 is the case for all PV installations.The competitive price of bifacial PV modules,combined with the higher energy yield through in-creased height and higher rate of reflection of sunlight make the application in overhead agri-voltaics more attractive.In vertical agrivoltaics systems,using bifacial

204、PV modules with high rear side efficiencies is key to maintain the overall efficiency of the system.Semi-transparent PV modules with a higher rate of transparency than conventional opaque PV modules can provide more sunlight for the crops.From an economic perspective,high market value crops can rath

205、er justify the use of more expensive semi-transparent PV modules to increase the light distribution to the area below.However,this needs to be assessed on a case-by-case basis,with the overall site economics determining the eventual selection of module technolo-gies.Table 3 presents the main design

206、metrics used for agrivoltaic systems.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 27 Table 3:Key design metrics of agrivoltaic systems.Agrivoltaic system design metrics Parameter Explanation

207、 Nominal power Power of PV modules at standard test conditions with additional infor-mation of alternating current(AC)nominal power of the inverter or batter-ies capacity used.Irradiation Annual global horizontal solar irradiation.Orientation Including tilt and surface azimuth angles of the PV modul

208、es for fixed tilt systems or tracker torque tube azimuth for tracked systems.The orienta-tion of PV modules influences the balance between solar energy conver-sion and agricultural production throughout the day or year.Ground Cover Ratio(GCR)The GCR is usually defined as the ratio of the PV module a

209、rea to the total land area utilized by the agrivoltaic system 42,55.The definition of both the PV module area and the total land area can be specified in different ways,e.g.,with or without considering the headland.The GCR is a central parameter to consider as it influences the level of total irradi

210、ation on the crops.However,as the orientation and,accordingly,also the area shel-tered by PV modules are not considered in the standard definition of the GCR,the actual implication parameter might be somewhat misleading.Alternatively,hence,the GCR can be calculated by the projected covered area from

211、 abovethis way really indicating the share of the covered area.For tilted PV modules,accordingly,the projected GRC is always smaller than the GCR calculated in the usual way.Pitch distance The distance between PV module rows.The larger the pitch distance,the higher the irradiation(i.e.,the lower the

212、 shading)at crop and ground level.Usually,also light heterogeneity on ground level increases with larger pitch distances which can be challenging particularly in industrialized ar-able farming systems where homogeneous ripening of crops is key 42,55,56.Furthermore,the planting distance of crops and

213、the planned ma-chine employment play an important role in determining a suitable pitch distance 56.Vertical clear-ance The vertical clearance indicates the distance between ground level and the lowest point of PV module rows mainly used for overhead systems.Crop height and size of agricultural machi

214、nery are primary factors in de-termining the vertical clearance.The vertical clearance of the system in-fluences the material requirement of the racking and,hence,the CAPEX of a system and is directly correlated with light homogeneity 5658.PV module technology Various PV module technologies can be u

215、sed,each with trade-offs in ef-ficiency,weight,and cost.Bifacial PV modules become the standard be-ing particularly attractive for overhead or vertical systems due to their higher energy yield from increased height and sunlight reflection.Semi-transparent PV modules,which allow more sunlight to reac

216、h crops,are Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 28 rather used for high-value crops,though their higher cost must be justified by the specific economics of the site.System tech-nolo

217、gy In the literature,distinct PV systems have been explored:the mechanical tracker system and the fixed system.In the mechanical tracker system,PV modules are installed on a single or dual-axis rotational mechanical system,allowing for the adjustment of PV module positions.This adapta-bility ensures

218、 that the sunlight requirements of plants can be promptly met with appropriate tracking strategies.The tracker system offers significant flexibility,effectively mitigating the detrimental effects of shading on crops,particularly in unfavourable weather conditions when irradiation levels are low.More

219、 details on bifa-cial tracking systems can be found in the report of Subtask 2.3 59.Mounting structure Concrete foundations in agrivoltaics pose challenges by creating perma-nent structures that affect crop growth and reduce cultivable land 56.Alternatives like screw piles are preferable,as they min

220、imize soil disturb-ance,preserve soil health,and allow easier removal,while the choice of mounting structure also depends on local wind conditions 57,60.Water distribu-tion Indicates the uniformity of water,particularly rainfall,distributed across the ground level of an agrivoltaic system.The config

221、uration of the PV sys-tem plays a pivotal role in determining how rain is redistributed on the soil surface 61.Widespread acceptance of agrivoltaics may be jeopardized if too much metal and concrete encroach on agricultural land to construct the PV systems.The ecological claim of reducing greenhouse

222、 gases through PV electricity can be diminished if the CO footprint of the mounting structure is of the same order of magnitude as that of typical PV modules.At the same time,it is evident that the costs of the PV module structure,especially for the overhead systems,are proportional to the amount of

223、 metal and are typically higher than the classic PV module.It is therefore recommended to use the simple KPI kg metal per kWp PV nominal power as a com-parative aid for comparing various agrivoltaics concepts.In the still very young agrivoltaics sector,not many such system comparisons are currently

224、possible.Nevertheless,the first ver-tical agrivoltaic systems could be compared with the overhead system from Heggelbach for illustration purposes and placed in relation to the technically related PV carport systems in terms of the supporting structure,as shown in Table 4.Task 13 Reliability and Per

225、formance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 29 Table 4:Amount of steel used in the PV mounting structure could exceed the CO2 footprint of a regular PV module of about 30g CO2/kWh 206.PV Configu-ration APV System Ann

226、ual MWh/ha Steel in-tensity kg/kWp Carbon emissions per energy con-verted gCO2/kWh Height at top edge2.8 m 4100 kWp system by Next2Sun in Donaueschingen,Aasen,Baden-Wrttemberg,Germany 343 40-70 5-9 Overhead height 2-4 m System by Insolight in Conthey,Switzerland(http:/in-solight.ch)60-80 8-10 Overhe

227、ad height 5 m System of Fraunhofer ISE,Heggelbach,Germany 248 284 36*Estimate:2.5kg CO2 per kg of galvanized steel In a future circular economy,recycled steel,which some PV module suppliers already offer as green steel,will be used with a CO2 footprint reduced by about a third.However,even then,the

228、total costs of such green steel agrivoltaics facilities could only be cost-effective if the amount of metal per kWp of PV power is again minimized.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic System

229、s 30 3 MODELLING AND SIMULATION Before installation,the fundamental steps for evaluating the profitability and projected perfor-mance of an agrivoltaic system are the simulation and optimization of the system design.Agri-voltaic systems are unique in their challenge to assess how the microclimate pr

230、oduced by the PV modules affects crop growth and,to a lesser extent,how the microclimate and crop growth affect PV production.Several software platforms or algorithms exist for modelling PV system yield,crop yield,and microclimate.However,the combination of these modelling needs makes agrivoltaic mo

231、delling unique.The lack of an end-to-end agrivoltaics modelling tool simultane-ously simulating PV power output and crop yield highlights a significant area where further research and development are needed.Moreover,with the development of the agrivoltaics sector,many governments have found it neces

232、sary to revise or develop laws,standards,and guidelines for the PV and agricultural sectors.Some regulatory frameworks set specific design parameters which might include:(i)ratio of agricultural areas reserved for conventional agri-culture 25;(ii)ratio of the total land area occupied by the agrivolt

233、aic system 25;(iii)maximal reduction in irradiance received by the crops 62,and(iv)required minimum crop yield relative to conventional agriculture.Thus,it is imperative to consider both the PV production and crop yield in a holistic manner to ensure that a proposed agrivoltaic system is both cost-e

234、ffective and in line with regulations.Modelling of agrivoltaic systems is a scientific challenge.A diagram of the workflow for simu-lating agrivoltaic systems is depicted in Figure 8.Scientific challenges arise because crop pro-duction under shading conditions(i.e.,shading cast by the PV modules and

235、 related supporting structures on the crops)is a relatively new area of research,both for experimentalists and modelers.Few research studies have been conducted on the effects of shadings produced by PV systems while the literature is more comprehensive on the effects of shading netsmate-rials used

236、to cover crops and provide partial shadeon crop yield but for a relatively small set of crops 63,64.From a PV perspective,the scientific challenge is to understand how the microclimate produced by the agrivoltaic system affects(i)the albedo underneath the PV sys-tem,(ii)the shading scene,and(iii)the

237、 temperature conditions of the solar cells and thus their efficiency.Given the market trend for bifacial PV modules,estimating solar irradiance distribu-tion at ground level becomes fundamental for assessing the irradiance incident on the rear side of the PV modules and,thus,the overall PV electrici

238、ty production.In this context,crop selection becomes important because the rear irradiance depends on the albedo,which de-pends on the crop type and phenological phases.Standard PV system modelling procedures using fixed or limited albedo variation over time and space can thus miscalculate the rear

239、irra-diance and,thus,PV yield.Crop management practices can also affect soiling and thus PV yield performances.These are also market challenges because profitability is a fundamental issue independent of the business models adopted for the specific agrivoltaic project 39,43 Actors involved in the pr

240、oject are advised to carefully assess the profitability of the project prior to installation.Additionally,an unconvincing report on the crop yield performance could result in the project failing to secure the benefits and privileges outlined in the legal framework sum-marized in Section 6.2.Task 13

241、Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 31 Figure 8:Simplified workflow for agrivoltaic systems simulation.3.1 Meteorological data for agrivoltaic system modelling Modelling agrivoltaic install

242、ations at various stages of development and operation demands information on the meteorological conditions at the site of interest for estimating crop growth and PV yield.For example,long-term historical data are necessary for site selection during feasibility studies.Similarly,in the project design

243、 phase,meteorological data is used to predict PV power output and crop yield for facility design and financing.Moreover,comparison be-tween model output and performance indicators measured in real-time can enable perfor-mance evaluation and enhanced operation of the agrivoltaic system.However,onsite

244、 measurements are often unavailable in the design phase of agrivoltaic sys-tems.Typical meteorological year data is sometimes used for prospecting sites for conven-tional PV systems.Such data files contain 8760 hourly irradiance values,wind speed and di-rection,temperature,relative humidity,and baro

245、metric pressure,representing the typical con-ditions at a particular location over an extended period.Accurate datasets are essential for optimizing the design of the PV system in terms of power output.For agrivoltaic systems,multi-year datasets are advantageous since they also capture interannual v

246、ariability.Considering more data is imperative to ensure a safe design,such as accounting for high wind loads.Further,higher temporally resolved data should be used because it is crucial for studying the effects of shading on crops.Satellite or reanalysis data are valuable alternatives when ground m

247、easurements are unavailable.However,it is crucial to utilize datasets validated through ground measurements conducted on or near the site to reduce yield uncertainty.The“Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications:Fourth Edition”65 of the I

248、EA PVPS Task 16 gives a comprehensive overview of all aspects of solar irradiance as well as other meteorological parameters relevant for PV applications.The handbook also includes agrivoltaics relevant parameters related to crops,such as photosynthetically active radiation(PAR),soil moisture,and hu

249、midity.3.2 Software and methods for irradiance modelling Irradiance modelling is a crucial aspect of agrivoltaic systems design and optimization,as it directly impacts both crop growth and PV module energy yields.In conventional PV systems,solar irradiation on the PV array is maximized to achieve th

250、e highest energy output while en-suring a safe system design and allowing for efficient O&M of the PV system.However,in Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 32 agrivoltaic systems,th

251、e irradiance distribution must also be optimized to promote crop growth and allow efficient maintenance and harvest of the crops.To study the distribution of irradiance between crops and PV modules,research has focused on aspects such as decomposition models that decompose global horizontal irradian

252、ce(GHI)or PAR into beam horizontal irradi-ance(BHI)and diffuse horizontal irradiance(DHI)or relative PAR components 61,62,trans-position models that transpose GHI,BHI,and DHI into irradiance received to the plane of array 66,67,and how the shading scene affects the irradiance reaching the PV modules

253、 and crops through view-factor analysis or ray-tracing techniques 68.Most decomposition and transpo-sition models were originally developed for conventional PV systems applications 6668.However,it is important to revisit these models from an agrivoltaic perspective since the crops influence availabl

254、e irradiance in terms of ground albedo that depends on the state and type of the crop 69.Some decomposition models have been modified to estimate the PAR and the photosynthetic photon flux density(PPFD)in agrivoltaic installations 6971.Ma Lu et al.69 assessed the performance of seven stand-alone mod

255、els to predict the PAR with measure-ments recorded in three different Swedish locations.The best-performing models were Yang2 and Starke,showing a normalized root mean square error of 25.1%(Yang2)and 28.6%(Starke).Yajima et al.70 developed a mathematical model for assessing PPFD under PV modules by

256、relying on an all-climate solar spectrum model able to simulate the solar spectrum both in clear-sky conditions and in overcast conditions.The model was validated with PPFD measurements for various days with different weather conditions and under different PV tilt angles and in general showed rather

257、 good performances with most of the standard residuals comprised between-6 and-3.Building on such models,various approaches and tools have been developed to specifically calculate the irradiance reaching the ground in agrivoltaic systems.Amaducci et al.72 devel-oped a software platform in Scilab to

258、investigate the solar irradiation distribution at crop level by discretizing the ground with a mesh and calculating shading by PV modules using a Boolean approach,where unshaded areas receive GHI,and shaded areas receive only DHI.Similar methods were implemented by Campana et al.67 with Agri-OptiCE

259、in Matlab,Trommsdorff et al.57 for overhead agrivoltaic systems,and Zainali et al.73 for benchmark-ing three different agrivoltaic configurations.Zainali et al.73 compared the results against two commercial software tools(PVsyst and SketchUp).Campana et al.74 improved the shading analysis of Agri-Op

260、tiCE by using a view factor approach considering PV module reflections on the ground.Katsikogiannis et al.75 used the Radiance-based daylighting sim-ulation tool Daysim to calculate ground-level irradiance for a fixed bifacial agrivoltaic array,while Prakash et al.76 analyzed PAR distribution using

261、Autodesk Revit.Wang et al.77 developed an in-house tool to model the different irradiance components.They validated the tool against measurements from an agrivoltaic installation in the USA and found that their tool overestimated the global irradiance but underestimated the diffuse component.Bruhwyl

262、er et l.78 deployed the ray casting algorithm from PyVista library to compute irradiation on ground in a vertical agrivoltaic system.Spatial,and computational fluid dynamics(CFD)models customized to simulate the irradiance and the PAR distribution in agrivoltaic systems have been developed and valid

263、ated.Tahir et al.79 explored the spatial PAR heterogeneity under different agrivoltaic configurations and validated the models results by using field measurements from an agrivoltaic system in the USA 80.Zainali et al.55 used a CFD model to map the global irradiance at ground level.They validated th

264、e results against actual field measurements taken in an agrivoltaic system in Sweden.They found that the model slightly underestimated the irradiance.Bruhwyler et al.81 developed the Python Agrivoltaic Simulation Environment(PASE 1.0),where irradiance on the ground for a vertical agrivoltaic system

265、was simulated and validated.Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 33 When assessing irradiance for plant growth,several key questions arise regarding how to best represent plants in 3

266、D modelling and define ground-level crop growth zones.Plant shapes can be modelled using either simple shapes,which approximate the outer boundaries of the crops,or more intricate shapes,which attempt to replicate the geometry of plant organs faithfully and leaves in detail.Complex geometries attemp

267、t to realistically represent the shape of crops,fa-cilitating the utilization of more intricate models used to evaluate crop photosynthesis and providing reasonable estimates of the 3D optical porosity.However,such approaches demand significantly higher computational resources due to the required sp

268、atial resolution and the num-ber of points where irradiance must be assessed.It also restricts the use of simpler agronomic models developed based on a preliminary evaluation of the irradiance incident on the external canopy envelope.In contrast,using basic shapes that depict the external envelope o

269、f crops reduces computa-tional complexity,facilitating the direct utilization of parametric models that assess photosyn-thesis in the canopy based on the solar irradiation reaching its outer envelope.When employ-ing these straightforward models,optical properties,including optical porosity,cannot be

270、 di-rectly modeled and must be incorporated through a parametric model attached to the objects texture.In some agrivoltaic modelling tools such as LuSim,experience has favored the use of basic geometric shapes alongside parameterized optical properties 82.The right trade-offs between model complexit

271、y and accuracy remain to be evaluated and validated.So far,only Willockx et al.83 have validated their in-house developed 3D light simulation tool,capable of evaluating the light distribution below PV canopies at the crop level of an agrivoltaic system in Belgium.They validated the simulations again

272、st field PAR measurements with a 8%agree-ment between monthly measured and modelled shading levels.Similarly,irradiance modelling for PV modules in agrivoltaic systems requires specialized tools and methods to account for the unique factors present in these systems.A few different tools exist that a

273、ccount for some of the irradiation-specific changes.The tool bifacial_radiance is a peer-reviewed open-source Python wrapper based on the ray-tracing software Radiance de-veloped and maintained by the National Renewable Energy Laboratory(NREL)84.The pro-gram enables sub-hourly simulations with custo

274、mized tracking algorithms,and modelling of detailed 3D scenes for the PV and plant systems.Another example is the commercial SPADE tool that estimates irradiation on PV modules and crops 85.3.3 Tools and approaches for microclimate modelling The presence of the PV modules in an agrivoltaic system af

275、fects crops microclimate and grow-ing conditions 86.Plant development is closely connected to the crop temperature,resulting from the energy balance at the ground and the plant itself.The energy budget at the ground is described by the following equation 87:Equation 1:Rn-H-E-G=0 where Rn is the net

276、irradiance(W/m2),H and E are the sensible and latent heat fluxes(W/m2),and G is the rate of heat storage in the vegetation and soil(W/m2),respectively.The contribu-tion of the incoming and reflected shortwave irradiance and the incoming and outgoing longwave irradiance give the net irradiance Rn.The

277、 sensible heat flux H corresponds to the convective heat exchanges between the air and the crop.The latent heat flux E corresponds to the energy released through soil evaporation and plant transpiration.Equation 1 can be used to show how changes induced in the microclimate by the presence of the agr

278、ivoltaic system might affect how the crops grow underneath the system.For example,shading caused by PV modules directly affects the incoming shortwave and longwave Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of A

279、grivoltaic Systems 34 irradiance,Rn.Shading might cause a reduction in the canopy and ground temperatures,and thus,the sensible H,latent E,and rate of heat storage in the vegetation and soil G.Moreover,if the PV modules and supporting structure induce a significant change in the ambient temper-ature

280、 or wind speed,the agrivoltaic systems can also affect the aerodynamic resistance of the crop.This will,in turn,affect the latent heat flux,E,which can also be affected through changes in the stomatal resistance(plant breathing resistance)caused by shading.The main critical physical phenomena and th

281、eir interaction with an agrivoltaic system are highlighted in Figure 9.Figure 9:Diagram of the main physical phenomena within an agrivoltaic system and how they interact 88.Colour code:red(irradiance);blue(evapotranspiration);black(displacement of air,sensible heat);brown(heat conduction in the soil

282、).Note that rele-vant weather phenomena,like rain,or energy removal by electric cables,are not shown here.The presence of the PV modules might also change the distribution of rainwater,affecting soil moisture and its distribution and,in extreme cases,leading to soil erosion when rain concen-trates 6

283、1.On the other hand,agrivoltaic systems,especially those equipped with water har-vesting techniques and solar trackers,can mitigate soil erosion and protect crops during ex-treme rainfall or hailing.The microclimate produced by these systems can enhance growing conditions for crops,depending on thei

284、r shade tolerance and the surrounding weather and climate.In hot and dry climates,the shading provided by agrivoltaic systems can reduce stress related to high temperatures and water scarcity 72,89.In areas exposed to strong winds,these systems can protect against the adverse effects of wind on crop

285、s,such as enhanced evapotranspiration and soil erosion.Agrivoltaic systems also enable the deployment of water harvesting techniques to redirect rainwater,reducing the risk of aeration stress in the crops.With the ongoing climate change,it is expected that the frequency and intensity of extreme weat

286、her phenomena,e.g.,drought and floods,will increase.Thus,the microclimate generated by agrivoltaic systems might provide security against crop failures.Moreover,research studies have shown that the microclimate produced by agrivoltaic systems can lead to lower interan-nual variation in crop yield 72

287、.One of the research and market gaps in the agrivoltaics sector Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 35 is the lack of specialized microclimate modelling tools for agrivoltaic system

288、s,despite several tools developed in research studies being available for microclimate simulations in different applications 9094.Several works are available in literature on microclimate modelling and control under PV green-houses 95,96,defined as closed agrivoltaic systems 97.However,only some stu

289、dies are available for microclimate modelling under open agrivoltaic systems.Although open and closed agrivoltaic systems can share methodologies,approaches,and tools for the estimation of microclimate,microclimate modelling under a greenhouse is a relatively more straightfor-ward task for two main

290、reasons:(i)greenhouses are a closed environment,and(ii)in most of the cases the microclimate is a controlled parameter 98.While solar irradiance is one of the main parameters affecting the microclimate underneath agrivoltaic systems,as presented in Section 3.2,other key parameters need to be modelle

291、d.Elamri et al.61 developed a 2D model,AVrain,written in the R programming language to depict rain distribution under agrivoltaic systems.The program considers the effect of wind speed and direction,the speed and size of the raindrops,and agrivoltaic system geometry on the rain distribution.Rain dis

292、tribution is essential for accurately simulating soil moisture distri-bution and how this affects crop water-related stresses.Zainali et al.55 used a computational fluid dynamic(CFD)approach to calculate solar irradiance,wind speed,soil,and air tempera-ture in an experimental agrivoltaic system in S

293、weden.The 3D model of the agrivoltaic system was built in Solidworks CAD,whereas the CFD simulations were performed in Solidworks Flow Simulation.CFD tools are key modelling tools that enable investigations into how the presence of the agrivoltaic systems structure influences the wind speed and dire

294、ction.Simi-larly,Williams et al.99 adopted a CFD approach to assess the effects of agrivoltaic system configurations on the cooling of the PV modules considering albedo,evapotranspiration,and module height.The authors calculated that an overhead agrivoltaic system with soybeans could lead to an oper

295、ating temperature of the PV modules of 10 C lower than GMPV 0.5 m elevated from the bare soil.Simulations were carried out in ANSYS Fluent.Despite the growing number of models dedicated to simulating various microclimatic parame-ters within agrivoltaic systems in recent years,there remains a signifi

296、cant need for validation studies to assess their accuracy.Only a limited number of studies have validated simulations of air temperature and relative humidity against actual measurements in either open or closed agrivoltaic installations 100102.Table 5 summarizes some of the approaches deployed to s

297、imulate microclimatic parameters in agrivoltaic systems.Table 5:Approaches for microclimate modelling in agrivoltaic systems.Software Microclimate variable Reference GHI/PAR ST ET WS/WD P Scilab 72 Matlab 74 Autodesk Autodesk Revit Analysis 76 Solidworks CAD and Solidworks Flow Simula-tion 73 Task 1

298、3 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 36 Code_saturne 103 ANSYS Fluent 99 R software 61 Python 81 GHI:global horizontal irradiance;PAR:photosynthetically active radiation;ST:soil tempera-tu

299、re;ET:evapotranspiration;WS:wind speed;WD:wind direction;P:precipitation.3.4 Approaches for crop modelling The growth of a crop is a very complex phenomenon that depends on the interaction of many factors.Crop models are mathematical equations representing the processes occurring within the plant an

300、d the interactions between the plant and its environment.Crop models can provide quantitative information about the major processes involved in plant growth and development and are essential for estimating the final state of total biomass or harvestable yield.The importance of applying crop modellin

301、g to agrivoltaics research is clearly demonstrated by the fact that,among the first scientific publications regarding crop production in agrivoltaic sys-tems,most were entirely,or at least partly,based on the results of crop modelling 7,72,104,105.Crop modelling provides scientists and researchers w

302、ith practical operational tools and methods to understand how the complex system of weather-soil-plant interactions is affected by conditions imposed by the agrivoltaic system on the microclimate and growing conditions of the crops.First,it is essential to distinguish between empirical and mechanist

303、ic crop models 106.While a mechanistic growth model describes the performance of a crop based on the knowledge of the processes that are taking place in its growth and development,an empirical model de-scribes the plants behavior based directly on observations at the plant level.So far,most of the m

304、odels used in agrivoltaics adopt an empirical approach for the processes that are most affected by shading,i.e.,photosynthesis,leaf structure,and especially the specific leaf area.Using a model based on daily irradiation use efficiency for photosynthesis might not lead to sufficiently accurate resul

305、ts 107.Because photosynthesis and transpiration responses to en-vironmental variables are strongly nonlinear,photosynthesis and transpiration should be first evaluated at the leaf level on a short time scale and then extended to the canopy level daily.This modelling approach requires a mechanistic a

306、pproach.However,it should be clear that,at certain stages,all models adopt empirical solutions.A variety of different crop models have been used in agrivoltaics research.The SIMPLE crop model 108 was adopted in a simulation study to find optimal solutions for different configura-tions of agrivoltaic

307、 systems 49.The SIMPLE crop model is designed to simplify crop model-ling to basic components.The model is well-validated and uses simple parameters,enabling straightforward and fast implementation.Biomass accumulation is based on a radiation use efficiency approach and implements empirical solution

308、s to consider water and temperature effects 107.Within the SIMPLE simulation framework,irradiation values are computed with a light-based simulation.The irradiation values are then passed to the crop model that calculates crop yield outputs in both reference full light and agrivoltaics conditions.An

309、other study on a simple modelling approach to crop growth was conducted by Campana et al.67,who used the Environmental Policy Integrated Climate(EPIC)model.The validation of the EPIC model simulations against actual seasonal potato and oats crop yield data from an agrivoltaic system in Sweden showed

310、 that the model tended to overestimate the Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:Overview and Performance of Agrivoltaic Systems 37 measurements if a previous calibration was not conducted.Although EPIC also uses empirical relation

311、ships to simulate potential growth,it contains several modules to account for different thermal and nutritional stresses.The solution of optimized configurations of agrivoltaic facilities may include the need to ensure,in the long term,agronomic and economic value using multiple crops and management

312、 op-tions.For this kind of multi-objective requirement,platforms that can simulate different crops with different crop models are very effective.An example of this is given in the work of Ko et al.109,who simulated rice,barley,and soybean using three crop models(CERES-rice,CERES-barley,CROPGRO-soybe

313、an)implemented in the DSSAT package.The level of pro-cess details varies greatly,and,in many cases,users may select among model options,allow-ing the user to assess how different assumptions affect the simulations.The authors utilized field trial data to calibrate and validate the models.Subsequentl

314、y,a geospatial crop simulation modelling system incorporating these crop models was employed to simulate regional varia-tions in crop yield under different solar irradiation reduction scenarios.Another crop model used for agrivoltaics studies is STICS,which relies on well-known rela-tionships and si

315、mplifications of existing models.Using STICS,Dinesh and Pearce 110 esti-mated the effect of shading on lettuce yield with two densities of PV modules.They showed that the model output can be used to support predictions for the economic evaluation of an agrivoltaic system.Under severe shading conditi

316、ons,the STICS model overestimates wheat production 7,111.In both studies,the authors concluded that the overestimation of wheat production was related to an incorrect estimation of the leaf area index(LAI).One crop model that offers interesting possibilities for simulating cropping systems in agrivo

317、lta-ics conditions is the Agricultural Production Systems Simulator(APSIM).This is a comprehen-sive model developed to simulate biophysical processes in agricultural systems,particularly as it relates to the economic and ecological outcomes of management practices in the face of climate risk.To date

318、,it has been used for agrivoltaics simulations in two different studies.First,Mamum et al.112 employed it to simulate pasture production under three different agrivoltaic configurations,i.e.,fixed-tilt,single-axis tracking,and dual-axis tracking.However,not many details were provided by the authors,

319、as they only reported that there is a module in APSIM to adjust irradiation with respect to full light.Second,Hau 113 directly employed the APSIM-Oryza model to estimate rices grain yield and total biomass under an agrivoltaic installation in Japan.The comparison against actual measurements demonstr

320、ated the adequate perfor-mance of the model with almost perfect matches between the modelled and the observed values(coefficient of determination values higher than 0.95).An interesting feature of APSIM for agrivoltaics studies is the simulation of crop phenology considering the effect of photoper-i

321、od.The model includes a so-called photoperiod sensitivity parameter,which determines the rate at which crop development progresses in response to changes in daylength.The manip-ulation of this parameter couldeven at the empirical levelbe exploited to simulate genetic differences to daylength of diff

322、erent cultivars of the same crop when grown in agrivoltaic sys-tems 109.A crop model with a high level of mechanistic relations is GECROS,which was adopted by Amaducci et al.72 in a simulation study on maize grown under different agrivoltaic systems and water management strategies.The model is parti

323、cularly suitable for agrivoltaics modelling for the capability of hourly simulations to capture temporal radiative patterns of intermittent shade.The GECROS model 114 was developed to overcome the inherent weakness of the approach based on dividing crop production into potential,water-limited or N-l

324、imited levels.GECROS can capture elementary traits of genotype-specific responses to the environment based on quantitative descriptions of complex traits related to crop phenology,root system Task 13 Reliability and Performance of PV Systems Dual Land Use for Agriculture and Solar Power Production:O

325、verview and Performance of Agrivoltaic Systems 38 development,photosynthesis and stomatal conductance,and stay-green traits.Therefore,the model is suitable for analyzing several physiological processes in response to environmental stresses,including stressors caused by limited irradiation,which is t

326、he most important aspect in agrivoltaics modelling.Using a modified version of GECROS,Potenza et al.115 estimated the grain yield of soybeans under different shading levels in an open agrivoltaic system in Italy.After validating the results against actual measurements,they found that the model tende

327、d to underestimate yield with increasing shade,with a maximum root mean square error of 16.5%for a 27%shading level.A way to improve the simulation of crop growth in agrivoltaic systems is to use modelling so-lutions to capture the reciprocal influences of the factors:available irradiation,canopy de

328、vel-opment,biomass accumulation,and available soil water.The interdependence of these factors indicates that the lower the energy the system receives,the lower the biomass accumulated,but there is a decrease in water demand due to lower evapotranspiration.The capacity to simulate the effect of irrad

329、iation on canopy development,particularly the changes caused by shade on leaf morphology,would be a desirable feature.At present,this is only available in sophisticated crop models,e.g.,GECROS.In agrivoltaics studies,the overall scope of the work must guide the implementation of a new model or the c

330、hoice of an existing one.Empirically based models can comprehensively esti-mate crop yield in an agrivoltaic system.By contrast,mechanistic crop models are needed to study how different assumptions affect the soil-plant-atmosphere or ontogenetic effects caused by the shading scene.3.5 PV yield model

331、ling PV yield modelling in agrivoltaic systems builds upon the modelling of irradiance and microcli-matic factors discussed in previous subchapters to predict the electrical energy output.So far,commercial actors have broadly used conventional PV modelling tools such as PVsyst or the System Advisor

332、Model(SAM)with minor adaptations to model energy yields in agrivoltaic sys-tems 113.However,these tools have limitations in addressing the additional effects on en-ergy yields caused by the agrivoltaic design and the presence of crops.To model the conversion of irradiation on PV modules to electrica

333、l energy output in research,many approaches with varying complexity are used.Simpler efficiency models,like PVWatts 116,have been employed.Amaducci et al.72 assumed a fixed system conversion efficiency of 14%,while Riaz et al.45 implemented system conversion efficiencies of 19%for the front side and 16%for the rear side of bifacial PV surfaces.Willockx et al.83 employed the PVWatts model to simula