@article{SummOyinlolaKhattaketal.2023, author = {Summ, Thorsten and Oyinlola, Muyiwa and Khattak, Sanober and Trinkl, Christoph and Z{\"o}rner, Wilfried}, title = {Statistical analysis of solar thermal collectors in the Solar Keymark Database}, volume = {2024}, pages = {103581}, journal = {Sustainable Energy Technologies and Assessments}, number = {61}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2213-1396}, doi = {https://doi.org/10.1016/j.seta.2023.103581}, year = {2023}, abstract = {Experimental, analytical, or numerical investigations are ordinarily conducted to reveal optimisation potential for solar thermal collectors. At the same time, the 'Solar Keymark Database' contains more than 2,000 test reports from certified laboratories featuring properties including thermal efficiency, dimensions, or optical properties. This dataset offers untapped potential for statistical analyses as an alternative optimisation approach. Hence, this paper aims to provide a) the first statistical findings of solar thermal collector properties listed in the Solar Keymark Database and b) insights into statistical relations between these properties. The key correlations observed from the analysis of flat-plate collectors were between efficiency and both gross height (R = 0.30) and gross area (R = 0.27). We concluded that preferable collector designs may be featured with larger area to height ratios. The analyses of evacuated tube collectors revealed a strong correlation between efficiency and transversal incidence angle modifier (R = -0.65) as a result from different tube spacing. It was noticeable that the quasi-dynamic test method reported significantly higher efficiencies (7.14 percentage points) for evacuated tube collectors, which should be carefully considered for future test procedures. Overall, the statistical analysis was in accordance with conventional bottom-up analyses and revealed insightful dependencies for the present collector data.}, 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{VannahmePatelSchmittetal.2024, author = {Vannahme, Anna and Patel, Dharmik and Schmitt, David and Summ, Thorsten and Trinkl, Christoph and Schrag, Tobias}, title = {Technical and economic analysis of digitally controlled substations in local district heating networks}, volume = {2024}, pages = {133585}, journal = {Energy}, number = {312}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0360-5442}, doi = {https://doi.org/10.1016/j.energy.2024.133585}, year = {2024}, abstract = {Since the 1990s, there has been a noticeable increase in the establishment of local district heating networks in Germany, coinciding with the use of thermal energy from biogas and biomass facilities. Historically, the prioritization of economically efficient heat utilization was subdued due to favorable electricity feed-in tariffs. However, with the expiration of Renewable Energy Sources Act subsidies, operators shifted focus to the operational costs of district heating networks. This study aims to examine the effects of optimizing controllers and valves at district heating substations in single-family homes, utilizing two local district heating networks. The emphasis is on evaluating impacts on operating costs and determining whether the economic and energetic benefits justify implementation. Simulation studies in MATLAB/Simulink Simscape depict both consumers and district heating networks individually, without aggregation. In the most favorable scenario, investing in enhancing substation controllers in single-family homes is projected to yield returns after 13 years. Comprehensive optimization of all substation controls in single-family homes can potentially result in up to 9\% savings in thermal energy demand due to reduced heat losses and a corresponding 9\% reduction in electrical power consumption for the main pump.}, language = {en} } @article{TutunaruBoschGresshakeetal.2023, author = {Tutunaru, Robin and Bosch, Stephan and Greßhake, Lukas and Holzhammer, Uwe}, title = {Ein Konzept f{\"u}r eine GIS-gest{\"u}tzte Visualisierung der spezifischen Anforderungen von regionalen Akteuren der Energiewende an die Landnutzung}, volume = {2023}, journal = {AGIT: Journal f{\"u}r Angewandte Geoinformatik}, number = {9}, publisher = {Wichmann Verlag}, address = {Berlin}, issn = {2509-713X}, doi = {https://doi.org/10.14627/537742005}, pages = {44 -- 49}, year = {2023}, abstract = {F{\"u}r eine nachhaltige Energiewende werden Konzepte ben{\"o}tigt, welche die techno-{\"o}konomische und sozial-{\"o}kologische Komplexit{\"a}t regionaler Standortentscheidungen f{\"u}r erneuerbare Energien (EE) visualisieren k{\"o}nnen. Dabei m{\"o}chten wir die Ergebnisse mittels Geographischer Infor-mationssysteme (GIS) so visualisieren, dass sie von jedem Akteur nachvollzogen werden k{\"o}nnen und einen konstruktiven Austausch zur Wertigkeit bestimmter Fl{\"a}chen zwischen allen Akteuren erlauben.}, language = {de} } @inproceedings{MastHuemmerHolzhammer2022, author = {Mast, Tanja and H{\"u}mmer, Benedikt and Holzhammer, Uwe}, title = {Smart Markets als marktbasierte Erg{\"a}nzung zum deutschen Engpassmanagement}, booktitle = {17. Symposium Energieinnovation}, subtitle = {Konzeptionierung anhand eines Modellbeispiels}, publisher = {Technische Universit{\"a}t Graz}, address = {Graz}, url = {https://www.tugraz.at/events/eninnov2022/nachlese/download-beitraege/stream-a/\#c318498}, year = {2022}, language = {de} } @article{StoecklHolzhammer2024, author = {St{\"o}ckl, Martin and Holzhammer, Uwe}, title = {Integration von Flexibilit{\"a}t in die Energieversorgung}, volume = {35}, journal = {Ern{\"a}hrung aktuell - der Lebensmittelbrief}, subtitle = {Ein Aspekt zur Erreichung der Klimaziele und zur Stabilisierung der Energiekosten - Fallbeispiel K{\"u}hlhaus}, number = {Mai/Juni}, publisher = {LID}, address = {Lampertheim}, issn = {1866-6787}, pages = {46 -- 47}, year = {2024}, language = {de} } @inproceedings{MastHuemmerHolzhammer2021, author = {Mast, Tanja and H{\"u}mmer, Benedikt and Holzhammer, Uwe}, title = {Potential of Demand Side Management and Biogas Plants in regional market-based Congestion Management}, booktitle = {ENERDAY 15th Conference on Energy Economics and Technology "Creative Destruction? Disruptive innovation in times of Covid and an accelerated energy system transformation": Book of Abstracts}, publisher = {TU Dresden}, address = {Dresden}, url = {https://tu-dresden.de/bu/wirtschaft/bwl/ee2/tagungen/enerday-archives}, pages = {22 -- 23}, year = {2021}, language = {en} } @article{DoepfertChuHamacher2025, author = {Doepfert, Markus and Chu, Jiahe and Hamacher, Thomas}, title = {HAMLET: A modular agent-based Python framework for energy markets and systems}, volume = {2025}, pages = {102346}, journal = {SoftwareX}, number = {32}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-7110}, doi = {https://doi.org/10.1016/j.softx.2025.102346}, year = {2025}, abstract = {HAMLET is an agent-based Python framework designed to model the intricate interactions between energy markets, systems, and stakeholders. Its modular architecture provides a flexible and adaptable platform for analyzing complex energy systems. With numerous pre-built templates for energy system components, HAMLET enables researchers to focus on their area of expertise without the need to develop the surrounding ecosystem from scratch. By integrating market and system dynamics, HAMLET supports diverse applications, including market design optimization, grid management, policy refinement, and energy management system development. HAMLET delivers detailed insights into the technical, economic, and social impacts of new system designs, addressing a critical gap in energy system modeling.}, language = {en} } @article{ChaturvediKumarToftumetal.2025, author = {Chaturvedi, Pushpendra Kr. and Kumar, Nand and Toftum, J{\o}rn and Andersen, Rune Korsholm and Lamba, Ravita and Mehta, Kedar}, title = {Exploring influential parameters affecting residential building energy use: advancing energy efficiency through machine learning}, volume = {27}, journal = {Clean Technologies and Environmental Policy}, number = {11}, publisher = {Springer}, address = {Berlin}, issn = {1618-9558}, doi = {https://doi.org/10.1007/s10098-025-03301-x}, pages = {6975 -- 6996}, year = {2025}, language = {en} } @inproceedings{ReumNataleSchmittetal.2025, author = {Reum, Tobias and Natale, Christian and Schmitt, David and Dongellini, Matteo and Naldi, Claudia and Summ, Thorsten and Morini, Gian Luca and Schrag, Tobias}, title = {Control Strategies for Active Regeneration in a Dual-Source Heat Pump}, booktitle = {Proceedings of the 15th REHVA HVAC World Congress - CLIMA 2025: Volume 1}, editor = {Zilio, Claudio and Busato, Filippo and Mazzarella, Livio and Noro, Marco}, publisher = {Springer}, address = {Cham}, isbn = {978-3-032-06806-4}, doi = {https://doi.org/10.1007/978-3-032-06806-4_55}, pages = {564 -- 574}, year = {2025}, language = {en} } @inproceedings{SchmittReumSummetal.2025, author = {Schmitt, David and Reum, Tobias and Summ, Thorsten and Schrag, Tobias}, title = {Comparison of Heat Pump Modelling Approaches for Predictive Controllers to Optimize the Efficiency of Modulating Air-Source Heat Pumps: A Case Study from South Germany}, booktitle = {Proceedings of the 15th REHVA HVAC World Congress - CLIMA 2025: Volume 1}, editor = {Zilio, Claudio and Busato, Filippo and Mazzarella, Livio and Noro, Marco}, publisher = {Springer}, address = {Cham}, isbn = {978-3-032-06806-4}, doi = {https://doi.org/10.1007/978-3-032-06806-4_59}, pages = {611 -- 620}, year = {2025}, 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{ChaturvediKumarLambaetal.2024, author = {Chaturvedi, Pushpendra Kr. and Kumar, Nand and Lamba, Ravita and Mehta, Kedar}, title = {Multi-objective optimization of glazing and shading configurations for visual, thermal, and energy performance of cooling dominant climatic regions of India}, volume = {27}, journal = {Clean Technologies and Environmental Policy}, number = {9}, publisher = {Springer}, address = {Berlin}, issn = {1618-9558}, doi = {https://doi.org/10.1007/s10098-024-03114-4}, pages = {4909 -- 4932}, year = {2024}, language = {en} } @article{MehtaBetz2025, author = {Mehta, Kedar and Betz, Florian}, title = {Agri-photovoltaics in India: Geospatial suitability for sustainable water-energy-food nexus solutions}, volume = {2026}, pages = {101915}, journal = {Energy for Sustainable Development}, number = {91}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-4669}, doi = {https://doi.org/10.1016/j.esd.2025.101915}, year = {2025}, language = {en} }