An Empirical Approach to Optimize Nonlinear Problems of Domestic Energy Management Systems
References
- 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).
- 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).
- REN21. Renewables 2020 global status report. 2020. [Online]. [Accessed: 09.03.2023]. Available: https://www.ren21.net/reports/global-status-report/
- 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-1003.02615
- 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.2022.3216298
- 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.pdf
- 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/en14175459
- 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/en15082866
- 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.
- 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.2020.02.004
- 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/s00502-016-0447-1
- 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.2019.04.039
- 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.2014.02.066
- 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.2014.03.047
- 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.2015.2467190
- 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.2019.114465
- 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.2018.03.154
- 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.2020.106971
- 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/en10070835
- 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.2018.09.185
- 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.2020.115106
- 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.2017.03.119
- 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_10
- 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.2019.01.112
- 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/en12153023
- 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.2020.3047527
- 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.2023.109183
- 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.2019.06.007
- Cottle R. Linear and nonlinear optimization, 1st ed., ser. International Series in Operations Research & Management Science. Springer-Verlag New York, 2017.
- Durea M., Strugariu R. An Introduction to Nonlinear Optimization Theory. De Gruyter Open Poland 2014. [Online]. [Accessed: 09.03.2023]. Available: https://doi.org/10.2478/9783110426045
- 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.2020.114708
- Li K., Tseng K. J. Energy efficiency of lithium-ion battery used as energy storage devices in microgrid. IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society. 2015. https://doi.org/10.1109/IECON.2015.7392923
- 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_17
- 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.2020.109792
- 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.2014.03.045
- European Power Exchange. [Online]. [Accessed: 09.03.2023]. Available: https://www.epexspot.com/en
Language: English
Page range: 299 - 313
Submitted on: Mar 31, 2023
Accepted on: Jun 12, 2023
Published on: Jul 11, 2023
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year
Keywords:
Related subjects:
© 2023 Fernando Carreras, Harald Kirchsteiger, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.