Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing
The integration of renewable energy sources, particularly solar photovoltaics, into household power supply has become increasingly popular due to its potential to reduce energy costs and environmental impact. However, solar power variability and new regulative changes concerning excess solar energy...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/9/2391 |
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| author | Damir Jakus Joško Novaković Josip Vasilj Danijel Jolevski |
| author_facet | Damir Jakus Joško Novaković Josip Vasilj Danijel Jolevski |
| author_sort | Damir Jakus |
| collection | DOAJ |
| description | The integration of renewable energy sources, particularly solar photovoltaics, into household power supply has become increasingly popular due to its potential to reduce energy costs and environmental impact. However, solar power variability and new regulative changes concerning excess solar energy compensation schemes call for effective energy storage management and sizing to ensure a stable and profitable electricity supply. This paper focuses on optimizing residential battery storage systems under different electricity pricing schemes such as time-of-use tariffs, dynamic pricing, and different excess solar energy compensation schemes. The central question addressed is how different pricing mechanisms and compensation strategies for excess solar energy, as well as varying battery storage investment costs, determine the optimal sizing of battery storage systems. A comprehensive mixed-integer linear programming model is developed to analyze these factors, incorporating various financial and operational parameters. The model is applied to a residential case study in Croatia, examining the impact of monthly net metering/billing, 15 min net billing, and dynamic pricing on optimal battery storage sizing and economic viability. |
| format | Article |
| id | doaj-art-73cdc15164fa4d6d91c48d9ecac92d7c |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-73cdc15164fa4d6d91c48d9ecac92d7c2025-08-20T01:50:45ZengMDPI AGEnergies1996-10732025-05-01189239110.3390/en18092391Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity PricingDamir Jakus0Joško Novaković1Josip Vasilj2Danijel Jolevski3Department of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, CroatiaDepartment of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, CroatiaDepartment of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, CroatiaDepartment of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, CroatiaThe integration of renewable energy sources, particularly solar photovoltaics, into household power supply has become increasingly popular due to its potential to reduce energy costs and environmental impact. However, solar power variability and new regulative changes concerning excess solar energy compensation schemes call for effective energy storage management and sizing to ensure a stable and profitable electricity supply. This paper focuses on optimizing residential battery storage systems under different electricity pricing schemes such as time-of-use tariffs, dynamic pricing, and different excess solar energy compensation schemes. The central question addressed is how different pricing mechanisms and compensation strategies for excess solar energy, as well as varying battery storage investment costs, determine the optimal sizing of battery storage systems. A comprehensive mixed-integer linear programming model is developed to analyze these factors, incorporating various financial and operational parameters. The model is applied to a residential case study in Croatia, examining the impact of monthly net metering/billing, 15 min net billing, and dynamic pricing on optimal battery storage sizing and economic viability.https://www.mdpi.com/1996-1073/18/9/2391battery storage sizingtime-of-use tariffdynamic pricingnet meteringnet billingmixed-integer linear programming |
| spellingShingle | Damir Jakus Joško Novaković Josip Vasilj Danijel Jolevski Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing Energies battery storage sizing time-of-use tariff dynamic pricing net metering net billing mixed-integer linear programming |
| title | Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing |
| title_full | Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing |
| title_fullStr | Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing |
| title_full_unstemmed | Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing |
| title_short | Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing |
| title_sort | optimal residential battery storage sizing under tou tariffs and dynamic electricity pricing |
| topic | battery storage sizing time-of-use tariff dynamic pricing net metering net billing mixed-integer linear programming |
| url | https://www.mdpi.com/1996-1073/18/9/2391 |
| work_keys_str_mv | AT damirjakus optimalresidentialbatterystoragesizingundertoutariffsanddynamicelectricitypricing AT joskonovakovic optimalresidentialbatterystoragesizingundertoutariffsanddynamicelectricitypricing AT josipvasilj optimalresidentialbatterystoragesizingundertoutariffsanddynamicelectricitypricing AT danijeljolevski optimalresidentialbatterystoragesizingundertoutariffsanddynamicelectricitypricing |