This work is licensed under the Creative Commons Attribution 4.0 International License.
Luderer G., Bartels F., Blesl M., Burkhardt A., Edenhofer O., Fahl U., Gillich A., Herbst A., Hufendiek K., Kaiser M., Kittel L., Koller F., Kost C., Pietzcker R., Rehfeldt M. Deutschland auf dem Weg aus der Gaskrise – Wie sich Klimaschutz und Energiesouveränität vereinen lassen. Ariadne. Kopernikus Projekte. (Germany on its way out of the gas crisis – How climate protection and energy sovereignty can be combined. Ariadne. Copernicus Projects) Die Zukunft unserer Energie 2022. [Online]. [Accessed: 09.03.2023]. Available: https://ariadneprojekt.de/publikation/deutschland-auf-dem-weg-aus-der-gaskrise/ (In German).Search in Google Scholar
BMK. Innovative Energietechnologien in Österreich Marktentwicklung 2021. (Innovative energy technologies in Austria market development 2021). Bundesministerium Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie, Tech. Rep., 2021. (In German).Search in Google Scholar
REN21. Renewables 2020 global status report. 2020. [Online]. [Accessed: 09.03.2023]. Available: https://www.ren21.net/reports/global-status-report/Search in Google Scholar
Ulbig A., Borsche T. S., Andersson G. Impact of Low Rotational Inertia on Power System Stability and Operation. IFAC Proceedings Volumes 2014:47(3):7290–7297. https://doi.org/10.3182/20140824-6-ZA-1003.02615Search in Google Scholar
Veichtlbauer A., Praschl C., Gaisberger L., Steinmaurer G., Strasser T. Toward an Effective Community Energy Management by Using a Cluster Storage. IEEE Access 2022:10:112286–112306. https://doi.org/10.1109/ACCESS.2022.3216298Search in Google Scholar
International Renewable Energy Agency (IRENA). Time-of-use-tariffs. 2019. [Online]. [Accessed: 09.03.2023]. Available: https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2019/Feb/IRENA_Innovation_ToU_tariffs_2019.pdfSearch in Google Scholar
Battula A. R., Vuddanti S., Salkuti S. R. Review of Energy Management System Approaches in Microgrids. Energies 2021:14(17):5459. https://doi.org/10.3390/en14175459Search in Google Scholar
Gomes I., Bot K., Ruano M. G., Ruano A. Recent Techniques Used in Home Energy Management Systems: A Review. Energies 2022:15(8):2866. https://doi.org/10.3390/en15082866Search in Google Scholar
Balakrishnan R., Geetha V. Review on home energy management system. Materials Today: Proceedings 2021:47(1):144–150. https://doi.org/10.1016/j.matpr.2021.04.029.Search in Google Scholar
Groß A., Wittwer C., Diehl M. Stochastic model predictive control of photovoltaic battery systems using a probabilistic forecast model. European Journal of Control 2020:56:254–264. https://doi.org/10.1016/j.ejcon.2020.02.004Search in Google Scholar
Kirchsteiger H., Rechberger P., Steinmaurer G. Cost-optimal control of photovoltaic systems with battery storage under variable electricity tariffs. Elektrotechnik und Informationstechnik 2016:133:371–380. https://doi.org/10.1007/s00502-016-0447-1Search in Google Scholar
Bernasconi G., Brofferio S., Cristaldi L. Cash flow prediction optimization using dynamic programming for a residential photovoltaic system with storage battery. Solar Energy 2019:186:233–246. https://doi.org/10.1016/j.solener.2019.04.039Search in Google Scholar
Li J., Danzer M. A. Optimal charge control strategies for stationary photovoltaic battery systems. Journal of Power Sources 2014:258:365–373. https://doi.org/10.1016/j.jpowsour.2014.02.066Search in Google Scholar
Rampinelli G., Krenzinger A., Romero F. C. Mathematical models for efficiency of inverters used in grid connected photovoltaic systems. Renewable and Sustainable Energy Reviews 2014:34:578–587. https://doi.org/10.1016/j.rser.2014.03.047Search in Google Scholar
Wang Y., Lin X., Pedram M. A near optimal model-based control algorithm for households equipped with residential photovoltaic power generation and energy storage systems. IEEE Transactions on Sustainable Energy 2016:7(1):77–86. https://doi.org/10.1109/TSTE.2015.2467190Search in Google Scholar
DiOrio N., Denholm P., Hobbs W. B. A model for evaluating the configuration and dispatch of pv plus battery power plants. Applied Energy 2020:262:114465. https://doi.org/10.1016/j.apenergy.2019.114465Search in Google Scholar
Litjens G., Worrell E., van Sark W. Assessment of forecasting methods on performance of photovoltaic-battery systems. Applied Energy 2018:221:358–373. https://doi.org/10.1016/j.apenergy.2018.03.154Search in Google Scholar
Mosa M. A., Ali A. Energy management system of low voltage dc microgrid using mixed-integer nonlinear programing and a global optimization technique. Electric Power Systems Research 2021:192:106971. https://doi.org/10.1016/j.epsr.2020.106971Search in Google Scholar
Hesse H. C., Martins R., Musilek P., Naumann M., Truong C. N., Jossen A. Economic optimization of component sizing for residential battery storage systems. Energies 2017:10(7):835. https://doi.org/10.3390/en10070835Search in Google Scholar
Cardoso G., Brouhard T., DeForest N., Wang D., Heleno M., Kotzur L. Battery aging in multi-energy microgrid design using mixed integer linear programming. Applied Energy 2018:231:1059–1069. https://doi.org/10.1016/j.apenergy.2018.09.185Search in Google Scholar
Zhang Y., Ma T., Elia Campana P., Yamaguchi Y., Dai Y. A techno-economic sizing method for grid-connected household photovoltaic battery systems. Applied Energy 2020:269:115106. https://doi.org/10.1016/j.apenergy.2020.115106Search in Google Scholar
Das B. K., Al-Abdeli Y. M., Kothapalli G. Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers. Applied Energy 2017:196:18–33. https://doi.org/10.1016/j.apenergy.2017.03.119Search in Google Scholar
Ried S., Schmiegel A. U., Munzke N. Efficient operation of modular grid-connected battery inverters for res integration. In Advances in Energy System Optimization Bertsch V., Ardone A., Suriyah M., Fichtner W., Leibfried T., Heuveline V. Eds. Cham: Springer International Publishing, 2020. https://doi.org/10.1007/978-3-030-32157-4_10Search in Google Scholar
Reimuth A., Prasch M., Locherer V., Danner M., Mauser W. Influence of different battery 14 charging strategies on residual grid power flows and self-consumption rates at regional scale. Applied Energy 2019:238:572–581. https://doi.org/10.1016/j.apenergy.2019.01.112Search in Google Scholar
Cho I. H., Lee P. Y., Kim J. H. Analysis of the effect of the variable charging current control method on cycle life of li-ion batteries. Energies 2019:12(15):3023. https://doi.org/10.3390/en12153023Search in Google Scholar
Biroon R. A., Abdollahi Z., Hadidi R. Inverter’s nonlinear efficiency and demand-side management challenges. IEEE Power Electronics Magazine 2021:8(1):49–54. https://doi.org/10.1109/MPEL.2020.3047527Search in Google Scholar
Carreras F., Kirchsteiger H. An iterative linear programming approach to optimize costs in distributed energy systems by considering nonlinear battery inverter efficiencies. Electric Power Systems Research 2023:218:109183. https://doi.org/10.1016/j.epsr.2023.109183Search in Google Scholar
Azuatalam D., Paridari K., Ma Y., Förstl M., Chapman A. C., Verbiˇca G. Energy Management of small-scale pvbattery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation. Renewable and Sustainable Energy Reviews 2019:112:555–570. https://doi.org/10.1016/j.rser.2019.06.007Search in Google Scholar
Cottle R. Linear and nonlinear optimization, 1st ed., ser. International Series in Operations Research & Management Science. Springer-Verlag New York, 2017.Search in Google Scholar
Durea M., Strugariu R. An Introduction to Nonlinear Optimization Theory. De Gruyter Open Poland 2014. [Online]. [Accessed: 09.03.2023]. Available: https://doi.org/10.2478/9783110426045Search in Google Scholar
Feng J., Hou S., Yu L., Dimov N., Zheng P., Wang C. Optimization of photovoltaic battery swapping station based on weather/trafficforecasts and speed variable charging. Applied Energy 2020:264:114708. https://doi.org/10.1016/j.apenergy.2020.114708Search in Google Scholar
Li K., Tseng K. J. Energy efficiency of lithium-ion battery used as energy storage devices in microgrid. IECON 2015 - 41stAnnual Conference of the IEEE Industrial Electronics Society. 2015. https://doi.org/10.1109/IECON.2015.7392923Search in Google Scholar
Gerwig C. Short term load forecasting for residential buildings – an extensive literature review. In Neves-Silva, R., Jain, L., Howlett, R. (eds) Intelligent Decision Technologies. IDT 2017. Smart Innovation, Systems and Technologies, vol. 39. Springer, 2015. https://doi.org/10.1007/978-3-319-19857-6_17Search in Google Scholar
Ahmed R., Sreeram V., Mishra Y., Arif M. A review and evaluation of the state-of-the-art in pv solar power forecasting: Techniques and optimization. Renewable and Sustainable Energy Reviews 2020:124:109792. https://doi.org/10.1016/j.rser.2020.109792Search in Google Scholar
Masa-Bote D., Castillo-Cagigal M., Matallanas E., Caamaño-Martín E., Gutiérrez A., Monasterio-Huelín F., Jiménez-Leube J. Improving photovoltaics grid integration through short time forecasting and self-consumption. Applied Energy 2014:125:103–113. https://doi.org/10.1016/j.apenergy.2014.03.045Search in Google Scholar
European Power Exchange. [Online]. [Accessed: 09.03.2023]. Available: https://www.epexspot.com/enSearch in Google Scholar