@article{MehtaZoerner2025, author = {Mehta, Kedar and Z{\"o}rner, Wilfried}, title = {Optimizing Agri-PV System: Systematic Methodology to Assess Key Design Parameters}, volume = {18}, pages = {3877}, journal = {Energies}, number = {14}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en18143877}, year = {2025}, abstract = {Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment.}, language = {en} } @article{MehtaWrightBrownetal.2025, author = {Mehta, Kedar and Wright, Andrew and Brown, Neil and Z{\"o}rner, Wilfried}, title = {Transitioning to Low-Carbon Heating: Decision-Making Approach for Cold Communities}, volume = {9}, pages = {zkaf010}, journal = {Clean Energy}, number = {4}, publisher = {Oxford University Press}, address = {Oxford}, issn = {2515-396X}, doi = {https://doi.org/10.1093/ce/zkaf010}, year = {2025}, abstract = {Selecting a sustainable heat energy supply system for high-altitude, cold-climatic communities in developing countries is essential for both decision-makers and the scientific community. However, no comprehensive guide or framework exists to address this issue and decarbonize cold communities sustainably. This research aims to fill that gap by identifying and developing a methodology for selecting a suitable heat energy supply system, using Kyrgyzstan as a case study. The approach takes into account renewable energy sources, local conditions, and specific criteria necessary for designing a sustainable energy supply. The paper introduces a decision-making framework based on 17 criteria, covering geographical, environmental, economic, technical, and social aspects, derived from the opinions of over 20 experts. This framework serves as a guide for selecting and designing an appropriate heat energy supply system. Five heat supply options are analyzed in Kyrgyzstan's high-altitude, cold rural setting to demonstrate the framework's potential. The analysis reveals that centralized district heating is the most suitable solution, scoring 79\% for system selection. This methodology is partially or fully transferable to regions or countries with similar climates and local circumstances, offering a valuable resource for the development of sustainable heat energy solutions in cold, high-altitude communities.}, language = {en} } @article{MehtaZoerner2025, author = {Mehta, Kedar and Z{\"o}rner, Wilfried}, title = {Crop selection in Agri-PV: international review based strategic decision-making model}, volume = {2025}, pages = {100143}, journal = {Solar Compass}, number = {16}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2772-9400}, doi = {https://doi.org/10.1016/j.solcom.2025.100143}, year = {2025}, abstract = {Agri-Photovoltaics (Agri-PV) is well known for its dual land use, integrating solar energy generation with agricultural production. This not only optimizes land use but also enhances food and energy security. Since Agri-PV is closely linked with crop cultivation, it is not solely about energy generation but also requires careful consideration of crop suitability within Agri-PV installations. Despite its significance, there is limited information available to guide decision-making for crop selection in Agri-PV systems. Selecting suitable crops remains a complex challenge, as factors such as shading tolerance, water requirements, and economic viability vary across different geographical and climatic conditions. This study develops a novel, review-based decision support model for crop selection in Agri-PV systems, synthesizing international research and case studies to provide a structured framework for decision-making. The model is based on 12 main crop typologies and key parameters such as water use, shading adaptability, crop yield/economic potential, and space requirements, derived from 117 research articles and case studies from 25 countries. By leveraging insights from successful international implementations, the model provides a practical framework for policymakers, farmers, and energy planners to enhance the sustainability and efficiency of Agri-PV projects. Findings suggest that crop selection strategies must align with regional climate conditions and PV system design to maximize synergies between energy and food production. High-value crops that require less space and have higher shade tolerance are more suitable for small-scale or decentralized Agri-PV systems. Future research should focus on advanced modeling techniques, AI-driven optimization, and real-world pilot studies to further refine decision-making in Agri-PV deployment. This study contributes to the growing body of knowledge on Agri-PV systems by providing a novel crop suitability matrix for effective decision-making.}, language = {en} } @article{RoueguiBellabairElAslietal.2025, author = {Rouegui, Meryem and Bellabair, Hind and El Asli, Abdelghani and Amar, Amine and Z{\"o}rner, Wilfried and Rachidi, Fouad and Lghoul, Rachid}, title = {Bio-Methanization of Sheep Manure and Beet Waste in the Meknes-F{\`e}s Region, Morocco: Effects of Pretreatment and Machine Learning Applications for Biochemical Methane Potential Prediction}, volume = {10}, pages = {213}, journal = {Recycling}, number = {6}, publisher = {MDPI}, address = {Basel}, issn = {2313-4321}, doi = {https://doi.org/10.3390/recycling10060213}, year = {2025}, abstract = {Sheep manure and beet waste (the uneatable leaf part of the beet) are promising feedstock for biogas production due to their abundance and organic richness. However, their high lignocellulosic content reduces anaerobic digestibility and controls methane yield. This study investigates the effect of various pretreatment strategies, namely physical, thermal, and combined physical-thermal methods, on the Biochemical Methane Potential (BMP) of sheep manure and beet waste. Batch anaerobic digestion experiments were conducted under mesophilic conditions, with BMP values recorded for each treatment. The highest BMP for sheep manure, 125 Nml CH4/g VS, was achieved using combined physical and thermal pretreatment. This approach enhanced methane production by 16\%, 25\%, and 60\% compared to physical pretreatment (PP) alone, thermal pretreatment (TP) alone, and no pretreatment, respectively, while the one BMP for beet waste is 80 Nml CH4/g VS and obtained with thermal pretreatment. To predict BMP outcomes, three machine learning approaches are applied, namely Linear Regression (LM), Random Forest Regression (RFR), and Gradient Boosting Machine (GBM), using digestion time (N days), total solids (Ts), volatile solids (Vs), pretreatment type, and biomass type. The variance analysis confirmed that the interaction between pretreatment and biomass type significantly improved model performance. While diagnostic checks revealed non-linear patterns limiting the linear model, ensemble methods achieved stronger results. The RFR model explained 79.5\% of the variance with a Root Mean Square Error (RMSE) of about 15.7, whereas the GBM model achieved the lowest RMSE of 5.05. GBM captures complex non-linear interactions. In addition, variable importance analyses identified digestion time, solid content, and pretreatment as the most influential factors for methane yield, with the combined chemical and physical pretreatment producing the highest biogas outputs. These findings underscore the potential of advanced machine learning models, particularly GBM (Gradient Boosting Machine), for optimizing anaerobic digestion strategies and maximizing biogas recovery from sheep manure and beet waste.}, language = {en} } @article{MehtaJainZoerner2025, author = {Mehta, Kedar and Jain, Rushabh Bansilal and Z{\"o}rner, Wilfried}, title = {Agrivoltaics Around the World: Potential, Technology, Crops and Policies to Address the Energy-Agriculture Nexus for Sustainable and Climate-Resilient Land Use}, volume = {18}, pages = {6417}, journal = {Energies}, number = {24}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en18246417}, year = {2025}, abstract = {The urgent pursuit of climate-resilient agriculture and clean energy systems, central to the Energy-Agriculture Nexus and the UN Sustainable Development Goals, has accelerated global interest in agrivoltaic (Agri-PV) technologies. This paper presents a global systematic review and meta-analysis of 160 peer-reviewed studies, structured through a five-stage thematic synthesis: (1) mapping global and regional Agri-PV deployment and potential, (2) analyzing system design and modeling methodologies, (3) evaluating crop suitability under partial shading, (4) reviewing enabling policies and regulatory frameworks, and (5) assessing techno-economic feasibility and investment barriers. Results reveal that Europe and Asia lead Agri-PV development, driven by incentive-based policies and national tenders, while limited regulatory clarity and high capital costs constrain wider adoption. Despite technological progress, no integrated model fully captures the coupled energy, water, and crop dynamics essential for holistic assessment. Strengthening economic valuation, policy coherence, and standardized modeling approaches will be critical to scale Agri-PV systems as a cornerstone of sustainable and climate-resilient land use.}, language = {en} } @article{MehtaLwakatareZoerneretal.2025, author = {Mehta, Kedar and Lwakatare, Bertha and Z{\"o}rner, Wilfried and Ehrenwirth, Mathias}, title = {Mini-grid performance in Sub-Saharan Africa: case studies from Tsumkwe and Gam, Namibia}, volume = {12}, pages = {30}, journal = {Sustainable Energy Research}, number = {1}, publisher = {SpringerOpen}, address = {Singapore}, issn = {2731-9237}, doi = {https://doi.org/10.1186/s40807-025-00174-y}, year = {2025}, abstract = {This paper investigates the performance analysis and operational challenges of mini-grids in Sub-Saharan Africa, focusing on the Tsumkwe and Gam mini-grids, the only officially recognized mini-grids in Namibia. The study addresses a critical gap in understanding mini-grid efficiency, technical difficulties, and future potential. The key research questions focus on assessing mini-grid performance, identifying technical and operational challenges, quantifying the relationship between electricity demand and supply, and providing recommendations for enhancing rural electrification through mini-grids. These insights are crucial for evaluating the effectiveness of mini-grids in the African context and understanding their role in advancing rural electrification. By using a mixed-method approach, the research combines quantitative and qualitative data to offer a comprehensive analysis of these two mini-grid systems of Namibia. The data collected from 2017 to 2022 include metrics on energy supply, consumption, photovoltaic generation, community load, and meteorological conditions. Qualitative insights were gathered through field visits, surveys, and interviews with mini-grid operators, allowing for a thorough examination of community perspectives, operational issues, and technical performance. The findings reveal that the Tsumkwe mini-grid has seen a decline in efficiency due to maintenance problems and battery overheating, while the Gam mini-grid, initially oversized, now struggles with increased demand and new connections. This study provides the first detailed technical insights, identifies consumer archetypes, and evaluates the energy dynamics of mini-grids in Namibia. Recommendations include improved maintenance protocols, advanced battery management, and enhanced data monitoring. By analyzing Tsumkwe and Gam, this paper offers valuable lessons for mini-grid development in Sub-Saharan Africa, stressing the need for continuous evaluation and strategic improvements to achieve sustainable rural electrification.}, language = {en} } @article{NgetunyBaldaufZoerner2025, author = {Ngetuny, Joshua Kiplagat and Baldauf, Tobias and Z{\"o}rner, Wilfried}, title = {Optimizing Feedstock Selection for Sustainable Small-Scale Biogas Systems Using the Analytic Hierarchy Process}, volume = {18}, pages = {1739}, journal = {Energies}, number = {7}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en18071739}, year = {2025}, abstract = {Small-scale biogas systems can play a pivotal role in sustainable energy provision, particularly in developing countries. However, their dependence on livestock manure as the only feedstock poses challenges to their adoption and long-term viability. This often leads to insufficient biogas production and plant abandonment. This study proposes co-digestion of livestock manure with other farm residues to enhance the technical sustainability of small-scale biogas systems by ensuring adequate and consistent biogas production throughout the plant's lifespan, minimizing the risks associated with reliance on a single feedstock. A novel feedstock selection approach is developed using the Analytic Hierarchy Process (AHP), a multicriteria decision-making method, to prioritize feedstocks based on adequacy, supply consistency, and logistical ease. AHP is chosen due to its capability to handle both quantitative and qualitative evaluation criteria. This approach is applied to the F{\`e}s-Mekn{\`e}s region of Morocco, which offers abundant livestock and crop residues alongside product utilization pathways. The prioritization and ranking of the potential feedstocks identified in the region reveals cattle manure as the top-ranked feedstock due to its consistent supply and ease of collection, followed by straw, valued for its storability and nutrient stability. Sheep, horse, and chicken manure ranked third, fourth, and fifth, respectively, while household food waste and fruit and vegetable residues, limited by seasonality and perishability, were ranked lower. Based on these findings, co-digestion of cattle manure and straw is proposed as a sustainable strategy for small-scale biogas plants in F{\`e}s-Mekn{\`e}s, addressing feedstock shortages, enhancing biogas production, and reducing plant abandonment. This approach strengthens technical sustainability and promotes the broader adoption of biogas technologies in developing countries.}, language = {en} } @article{NgetunyHsaineMabroukietal.2025, author = {Ngetuny, Joshua Kiplagat and Hsaine, Jalal and Mabrouki, Abdelaalim and Rachidi, Fouad and El Asli, Abdelghani and Z{\"o}rner, Wilfried}, title = {Assessment of agricultural residues for small-scale biogas plants and adoption drivers: a case study of the F{\`e}s-Mekn{\`e}s region in Morocco}, volume = {15}, journal = {Biomass Conversion and Biorefinery}, number = {22}, publisher = {Springer}, address = {Berlin}, issn = {2190-6815}, doi = {https://doi.org/10.1007/s13399-024-06443-y}, pages = {29207 -- 29223}, year = {2025}, abstract = {Small-scale biogas systems hold promise as reliable renewable energy sources in developing nations; however, adequate and consistent supply of feedstock remains a challenge. Agricultural residue, due to their lack of competition with food crops for resources, is touted as a dependable feedstock choice. This article therefore examines agricultural residues as potential biogas plant feedstocks in the F{\`e}s-Mekn{\`e}s region of Morocco, using a structured farm survey to evaluate livestock types, crop varieties, and residue utilization. Additionally, the study explores the challenges and drivers influencing biogas technology adoption in Morocco. Findings indicate a predominance of small-scale farms with livestock (averaging 11 cattle, 45 sheep, and 20 chicken) and mainly subsistence crop production, making these farms suitable candidates for small-scale biogas plants. Key barriers to adoption include a lack of awareness about the technology, along with technical and financial constraints. However, raising awareness, establishing demonstration plants, and offering financial and non-financial incentives are identified as potential drivers of adoption. This research provides a foundation for implementing biogas technologies in the case study area and other developing nations, guiding researchers and governmental and non-governmental organizations in disseminating small-scale biogas systems as a reliable energy source and a method for converting agricultural residues into sustainable energy (biogas) and fertilizer. Graphical Abstract}, language = {en} }