[{"author":[{"first_name":"Stefan","orcid":"0000-0002-3594-260X","full_name":"Krauter, Stefan","last_name":"Krauter","id":"28836"},{"full_name":"Bendfeld, Jörg","first_name":"Jörg","id":"16148","last_name":"Bendfeld"},{"id":"72391","last_name":"Möller","full_name":"Möller, Marius Claus","first_name":"Marius Claus"}],"publication":"Proceedings of the 49th IEEE Photovoltaic Specialists Conference","department":[{"_id":"53"}],"status":"public","date_created":"2022-07-08T07:52:03Z","abstract":[{"lang":"eng","text":"The market for microinverters is growing, especially in Europe. Driven by the strongly rising prices for electricity, many small photovoltaic energy systems are being installed. Since monitoring for these plants is often quite costly, their yields are often not logged. Since 2014, microinverters have been studied at the University of Paderborn. The investigations are divided into indoor and outdoor tests. In the indoor area conversion efficiencies as a function of load have been measured with high accuracy and ranked according to Euro- and CEC weightings. In the outdoor laboratory, the behavior in the real world is tested. Energy yields have been measured outdoors via identical and calibrated crystalline silicon PV modules. Here, the investigations were carried out with modules of the power of 215 Wp until the year 2020. Because of the increasing module power nowadays, modules with an output of 360 Wp are now being used. To assess the influence of PV module size, two extremes have been investigated: A rather small module with 215 Wp - as it has been used 10 years ago, and a brand-new module (2021) offering 360 Wp. Both types of modules contain 60 solar cells in series connection. Appling the low-power modules, the challenge for the different micro-inverters has been during weak-light conditions, using the high-power modules, some inverters temporarily reach their power limits and yield is reduced. A method using a reference configuration of inverter & module and a linear equation resulting in the actual yield, any module & inverter configuration can be characterized by just the two coefficients."}],"title":"Microinverter testing update using high power modules: Efficiency, yield, and conformity to a new ”estimation formula” for variation of PV panel size","user_id":"16148","year":"2022","citation":{"ieee":"S. Krauter, J. Bendfeld, and M. C. Möller, “Microinverter testing update using high power modules: Efficiency, yield, and conformity to a new ”estimation formula” for variation of PV panel size,” presented at the 49th IEEE Photovoltaic Specialists Conference, Philadelphia, PA, USA, 2022.","short":"S. Krauter, J. Bendfeld, M.C. Möller, in: Proceedings of the 49th IEEE Photovoltaic Specialists Conference, 2022.","mla":"Krauter, Stefan, et al. “Microinverter Testing Update Using High Power Modules: Efficiency, Yield, and Conformity to a New ”estimation Formula” for Variation of PV Panel Size.” Proceedings of the 49th IEEE Photovoltaic Specialists Conference, 2022.","bibtex":"@inproceedings{Krauter_Bendfeld_Möller_2022, title={Microinverter testing update using high power modules: Efficiency, yield, and conformity to a new ”estimation formula” for variation of PV panel size}, booktitle={Proceedings of the 49th IEEE Photovoltaic Specialists Conference}, author={Krauter, Stefan and Bendfeld, Jörg and Möller, Marius Claus}, year={2022} }","chicago":"Krauter, Stefan, Jörg Bendfeld, and Marius Claus Möller. “Microinverter Testing Update Using High Power Modules: Efficiency, Yield, and Conformity to a New ”estimation Formula” for Variation of PV Panel Size.” In Proceedings of the 49th IEEE Photovoltaic Specialists Conference, 2022.","apa":"Krauter, S., Bendfeld, J., & Möller, M. C. (2022). Microinverter testing update using high power modules: Efficiency, yield, and conformity to a new ”estimation formula” for variation of PV panel size. Proceedings of the 49th IEEE Photovoltaic Specialists Conference. 49th IEEE Photovoltaic Specialists Conference, Philadelphia, PA, USA.","ama":"Krauter S, Bendfeld J, Möller MC. Microinverter testing update using high power modules: Efficiency, yield, and conformity to a new ”estimation formula” for variation of PV panel size. In: Proceedings of the 49th IEEE Photovoltaic Specialists Conference. ; 2022."},"type":"conference","language":[{"iso":"eng"}],"date_updated":"2022-07-11T06:58:40Z","_id":"32334","conference":{"end_date":"2022-06-10","location":"Philadelphia, PA, USA","start_date":"2022-06-05","name":"49th IEEE Photovoltaic Specialists Conference"}},{"date_created":"2022-07-08T07:49:53Z","status":"public","publication":"Proceedings of the 49th IEEE Photovoltaic Specialists Conference","department":[{"_id":"53"}],"author":[{"full_name":"Möller, Marius Claus","first_name":"Marius Claus","id":"72391","last_name":"Möller"},{"last_name":"Krauter","id":"28836","first_name":"Stefan","orcid":"0000-0002-3594-260X","full_name":"Krauter, Stefan"}],"user_id":"16148","title":"Model of a Self-Sufficient PV Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization ","abstract":[{"lang":"eng","text":"This paper provides a hybrid energy system model created in Matlab/Simulink which is based on photovoltaics as its main energy source. The model includes a hybrid energy storage which consists of a short-term lithium-ion battery and hydrogen as long-term storage to ensure autonomy even during periods of low PV production (e.g., in winter). The sectors heat and electricity are coupled by using the waste-heat generated by production and reconversion of hydrogen through an electrolyser respectively a fuel cell. A heat pump has been considered to cover the residual heat demand (for well insulated homes). Within this paper a model of the space heating system as well as the hot water heating system is presented. The model is designed for the simulation and analysis of a whole year energy flow by using a time series of loads, weather and heat profiles as input. Moreover, results of the energy balance within the energy system by simulation of a complete year by varying the orientation (elevation and azimuth) of the PV system and the component sizing, such as the lithium-ion battery capacity, are presented. It turned out that a high amount of heating energy can be saved by using the waste heat generated by the electrolyser and the fuel cell. The model is well suited for the analysis of the effects of different component dimensionings in a hydrogen-based energy system via the overall energy balance within the residential sector."}],"language":[{"iso":"eng"}],"citation":{"ieee":"M. C. Möller and S. Krauter, “Model of a Self-Sufficient PV Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization ,” in Proceedings of the 49th IEEE Photovoltaic Specialists Conference, Philadelphia, PA, USA, 2022.","short":"M.C. Möller, S. Krauter, in: IEEE (Ed.), Proceedings of the 49th IEEE Photovoltaic Specialists Conference, 2022.","bibtex":"@inproceedings{Möller_Krauter_2022, title={Model of a Self-Sufficient PV Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization }, booktitle={Proceedings of the 49th IEEE Photovoltaic Specialists Conference}, author={Möller, Marius Claus and Krauter, Stefan}, editor={IEEE}, year={2022} }","mla":"Möller, Marius Claus, and Stefan Krauter. “Model of a Self-Sufficient PV Home Using a Hybrid Storage System Based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization .” Proceedings of the 49th IEEE Photovoltaic Specialists Conference, edited by IEEE, 2022.","ama":"Möller MC, Krauter S. Model of a Self-Sufficient PV Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization . In: IEEE, ed. Proceedings of the 49th IEEE Photovoltaic Specialists Conference. ; 2022.","apa":"Möller, M. C., & Krauter, S. (2022). Model of a Self-Sufficient PV Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization . In IEEE (Ed.), Proceedings of the 49th IEEE Photovoltaic Specialists Conference.","chicago":"Möller, Marius Claus, and Stefan Krauter. “Model of a Self-Sufficient PV Home Using a Hybrid Storage System Based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization .” In Proceedings of the 49th IEEE Photovoltaic Specialists Conference, edited by IEEE, 2022."},"type":"conference","year":"2022","corporate_editor":["IEEE"],"conference":{"start_date":"2022-06-05","name":"49th IEEE Photovoltaic Specialists Conference","location":"Philadelphia, PA, USA","end_date":"2022-06-10"},"date_updated":"2022-07-11T06:59:25Z","_id":"32333"},{"citation":{"bibtex":"@article{Möller_Krauter_2022, title={Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion Battery and Hydrogen}, volume={15 (6), 2201}, DOI={10.3390/en15062201}, journal={Energies / Special Issue “Sustainable Energy Concepts for Energy Transition”}, publisher={MDPI / Basel, Switzerland}, author={Möller, Marius Claus and Krauter, Stefan}, year={2022} }","mla":"Möller, Marius Claus, and Stefan Krauter. “Hybrid Energy System Model in Matlab/Simulink Based on Solar Energy, Lithium-Ion Battery and Hydrogen.” Energies / Special Issue “Sustainable Energy Concepts for Energy Transition,” vol. 15 (6), 2201, MDPI / Basel, Switzerland, 2022, doi:10.3390/en15062201.","ieee":"M. C. Möller and S. Krauter, “Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion Battery and Hydrogen,” Energies / Special Issue “Sustainable Energy Concepts for Energy Transition,” vol. 15 (6), 2201, 2022, doi: 10.3390/en15062201.","chicago":"Möller, Marius Claus, and Stefan Krauter. “Hybrid Energy System Model in Matlab/Simulink Based on Solar Energy, Lithium-Ion Battery and Hydrogen.” Energies / Special Issue “Sustainable Energy Concepts for Energy Transition” 15 (6), 2201 (2022). https://doi.org/10.3390/en15062201.","apa":"Möller, M. C., & Krauter, S. (2022). Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion Battery and Hydrogen. Energies / Special Issue “Sustainable Energy Concepts for Energy Transition,” 15 (6), 2201. https://doi.org/10.3390/en15062201","ama":"Möller MC, Krauter S. Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion Battery and Hydrogen. Energies / Special Issue “Sustainable Energy Concepts for Energy Transition.” 2022;15 (6), 2201. doi:10.3390/en15062201","short":"M.C. Möller, S. Krauter, Energies / Special Issue “Sustainable Energy Concepts for Energy Transition” 15 (6), 2201 (2022)."},"type":"journal_article","year":"2022","language":[{"iso":"eng"}],"date_updated":"2022-07-11T07:03:34Z","_id":"30262","doi":"10.3390/en15062201","department":[{"_id":"53"}],"publication":"Energies / Special Issue \"Sustainable Energy Concepts for Energy Transition\"","author":[{"full_name":"Möller, Marius Claus","first_name":"Marius Claus","id":"72391","last_name":"Möller"},{"orcid":"0000-0002-3594-260X","full_name":"Krauter, Stefan","first_name":"Stefan","id":"28836","last_name":"Krauter"}],"publisher":"MDPI / Basel, Switzerland","quality_controlled":"1","publication_status":"published","publication_identifier":{"issn":["1996-1073"]},"volume":"15 (6), 2201","date_created":"2022-03-11T09:56:32Z","status":"public","abstract":[{"lang":"eng","text":"In this paper, a model of a hybrid, hydrogen-based energy system for a household which includes the heating sector is presended. With such an energy system it's possible to enable energy autarky over a whole year based on solar energy. The scope of this study was to present a verified hybrid energy system model created in Simulink which can be used to prospectively size future similar energy systems where hydrogen in combination with a li-ion battery shall be used as energy storage type."}],"title":"Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion Battery and Hydrogen","user_id":"16148"},{"_id":"34155","date_updated":"2022-11-29T10:00:44Z","conference":{"name":"8th World Conference on Photovoltaik Energy Conversion","start_date":"2022-09-26","location":"Milano / Italy","end_date":"2022-09-30"},"language":[{"iso":"eng"}],"year":"2022","type":"conference","citation":{"ieee":"S. Krauter and J. Bendfeld, “Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types,” presented at the 8th World Conference on Photovoltaik Energy Conversion, Milano / Italy, 2022.","short":"S. Krauter, J. Bendfeld, in: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion, 2022.","bibtex":"@inproceedings{Krauter_Bendfeld_2022, title={Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types}, booktitle={Proceedings of the 8th World Conference on Photovoltaik Energy Conversion}, author={Krauter, Stefan and Bendfeld, Jörg}, year={2022} }","mla":"Krauter, Stefan, and Jörg Bendfeld. “Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for Any PV Panel Size at Different Microinverter Types.” Proceedings of the 8th World Conference on Photovoltaik Energy Conversion, 2022.","apa":"Krauter, S., & Bendfeld, J. (2022). Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types. Proceedings of the 8th World Conference on Photovoltaik Energy Conversion. 8th World Conference on Photovoltaik Energy Conversion, Milano / Italy.","ama":"Krauter S, Bendfeld J. Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types. In: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion. ; 2022.","chicago":"Krauter, Stefan, and Jörg Bendfeld. “Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for Any PV Panel Size at Different Microinverter Types.” In Proceedings of the 8th World Conference on Photovoltaik Energy Conversion, 2022."},"user_id":"16148","title":"Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types","status":"public","date_created":"2022-11-29T09:55:14Z","author":[{"last_name":"Krauter","id":"28836","first_name":"Stefan","full_name":"Krauter, Stefan","orcid":"0000-0002-3594-260X"},{"first_name":"Jörg","full_name":"Bendfeld, Jörg","last_name":"Bendfeld","id":"16148"}],"department":[{"_id":"53"}],"publication":"Proceedings of the 8th World Conference on Photovoltaik Energy Conversion"},{"language":[{"iso":"eng"}],"type":"conference","citation":{"apa":"Kakande, J. N., Philipo, G. H., & Krauter, S. (2022). Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER. Proceedings of the 8th World Conference on Photovoltaik Energy Conversion. 8th World Conference on Photovoltaik Energy Conversion, Milano / Italy.","ama":"Kakande JN, Philipo GH, Krauter S. Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER. In: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion. ; 2022.","chicago":"Kakande, Josephine Nakato, Godiana Hagile Philipo, and Stefan Krauter. “Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER.” In Proceedings of the 8th World Conference on Photovoltaik Energy Conversion, 2022.","bibtex":"@inproceedings{Kakande_Philipo_Krauter_2022, title={Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER}, booktitle={Proceedings of the 8th World Conference on Photovoltaik Energy Conversion}, author={Kakande, Josephine Nakato and Philipo, Godiana Hagile and Krauter, Stefan}, year={2022} }","mla":"Kakande, Josephine Nakato, et al. “Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER.” Proceedings of the 8th World Conference on Photovoltaik Energy Conversion, 2022.","short":"J.N. Kakande, G.H. Philipo, S. Krauter, in: Proceedings of the 8th World Conference on Photovoltaik Energy Conversion, 2022.","ieee":"J. N. Kakande, G. H. Philipo, and S. Krauter, “Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER,” presented at the 8th World Conference on Photovoltaik Energy Conversion, Milano / Italy, 2022."},"year":"2022","conference":{"end_date":"2022-09-30","name":"8th World Conference on Photovoltaik Energy Conversion","start_date":"2022-09-26","location":"Milano / Italy"},"date_updated":"2022-11-29T10:03:30Z","_id":"34156","date_created":"2022-11-29T10:03:24Z","status":"public","department":[{"_id":"53"}],"publication":"Proceedings of the 8th World Conference on Photovoltaik Energy Conversion","author":[{"id":"88649","last_name":"Kakande","full_name":"Kakande, Josephine Nakato","first_name":"Josephine Nakato"},{"last_name":"Philipo","full_name":"Philipo, Godiana Hagile","first_name":"Godiana Hagile"},{"last_name":"Krauter","id":"28836","first_name":"Stefan","full_name":"Krauter, Stefan","orcid":"0000-0002-3594-260X"}],"user_id":"16148","title":"Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER"},{"intvolume":" 15","_id":"32403","article_number":"5215","issue":"14","type":"journal_article","year":"2022","citation":{"bibtex":"@article{Philipo_Kakande_Krauter_2022, title={Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping}, volume={15}, DOI={10.3390/en15145215}, number={145215}, journal={Energies}, publisher={MDPI AG}, author={Philipo, Godiana Hagile and Kakande, Josephine Nakato and Krauter, Stefan}, year={2022} }","mla":"Philipo, Godiana Hagile, et al. “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.” Energies, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:10.3390/en15145215.","ama":"Philipo GH, Kakande JN, Krauter S. Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. Energies. 2022;15(14). doi:10.3390/en15145215","apa":"Philipo, G. H., Kakande, J. N., & Krauter, S. (2022). Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. Energies, 15(14), Article 5215. https://doi.org/10.3390/en15145215","chicago":"Philipo, Godiana Hagile, Josephine Nakato Kakande, and Stefan Krauter. “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.” Energies 15, no. 14 (2022). https://doi.org/10.3390/en15145215.","ieee":"G. H. Philipo, J. N. Kakande, and S. Krauter, “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping,” Energies, vol. 15, no. 14, Art. no. 5215, 2022, doi: 10.3390/en15145215.","short":"G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022)."},"abstract":[{"text":"Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.","lang":"eng"}],"user_id":"16148","author":[{"full_name":"Philipo, Godiana Hagile","first_name":"Godiana Hagile","last_name":"Philipo"},{"first_name":"Josephine Nakato","full_name":"Kakande, Josephine Nakato","last_name":"Kakande","id":"88649"},{"last_name":"Krauter","id":"28836","first_name":"Stefan","full_name":"Krauter, Stefan","orcid":"0000-0002-3594-260X"}],"publisher":"MDPI AG","keyword":["Energy (miscellaneous)","Energy Engineering and Power Technology","Renewable Energy","Sustainability and the Environment","Electrical and Electronic Engineering","Control and Optimization","Engineering (miscellaneous)","Building and Construction"],"publication":"Energies","volume":15,"status":"public","date_created":"2022-07-20T11:46:09Z","date_updated":"2023-10-11T08:26:43Z","doi":"10.3390/en15145215","language":[{"iso":"eng"}],"title":"Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping","department":[{"_id":"53"}],"publication_identifier":{"issn":["1996-1073"]},"publication_status":"published"},{"user_id":"16148","abstract":[{"text":"Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.","lang":"eng"}],"volume":15,"status":"public","date_created":"2023-10-11T08:13:13Z","author":[{"first_name":"Godiana Hagile","full_name":"Philipo, Godiana Hagile","last_name":"Philipo"},{"id":"88649","last_name":"Kakande","full_name":"Kakande, Josephine Nakato","first_name":"Josephine Nakato"},{"first_name":"Stefan","orcid":"0000-0002-3594-260X","full_name":"Krauter, Stefan","last_name":"Krauter","id":"28836"}],"publisher":"MDPI AG","publication":"Energies","keyword":["Energy (miscellaneous)","Energy Engineering and Power Technology","Renewable Energy","Sustainability and the Environment","Electrical and Electronic Engineering","Control and Optimization","Engineering (miscellaneous)","Building and Construction"],"article_number":"5215","issue":"14","intvolume":" 15","_id":"47961","type":"journal_article","year":"2022","citation":{"apa":"Philipo, G. H., Kakande, J. N., & Krauter, S. (2022). Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. Energies, 15(14), Article 5215. https://doi.org/10.3390/en15145215","ama":"Philipo GH, Kakande JN, Krauter S. Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. Energies. 2022;15(14). doi:10.3390/en15145215","chicago":"Philipo, Godiana Hagile, Josephine Nakato Kakande, and Stefan Krauter. “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.” Energies 15, no. 14 (2022). https://doi.org/10.3390/en15145215.","bibtex":"@article{Philipo_Kakande_Krauter_2022, title={Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping}, volume={15}, DOI={10.3390/en15145215}, number={145215}, journal={Energies}, publisher={MDPI AG}, author={Philipo, Godiana Hagile and Kakande, Josephine Nakato and Krauter, Stefan}, year={2022} }","mla":"Philipo, Godiana Hagile, et al. “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.” Energies, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:10.3390/en15145215.","short":"G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022).","ieee":"G. H. Philipo, J. N. Kakande, and S. Krauter, “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping,” Energies, vol. 15, no. 14, Art. no. 5215, 2022, doi: 10.3390/en15145215."},"title":"Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping","publication_status":"published","publication_identifier":{"issn":["1996-1073"]},"department":[{"_id":"53"}],"doi":"10.3390/en15145215","date_updated":"2023-10-11T08:14:06Z","language":[{"iso":"eng"}]}]