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Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing

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  • Damir Jakus

    (Department of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, Croatia)

  • Joško Novaković

    (Department of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, Croatia)

  • Josip Vasilj

    (Department of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, Croatia)

  • Danijel Jolevski

    (Department of Power Engineering, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split—FESB, Ruđera Boškovića 32, 21000 Split, Croatia)

Abstract

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.

Suggested Citation

  • Damir Jakus & Joško Novaković & Josip Vasilj & Danijel Jolevski, 2025. "Optimal Residential Battery Storage Sizing Under ToU Tariffs and Dynamic Electricity Pricing," Energies, MDPI, vol. 18(9), pages 1-24, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:9:p:2391-:d:1650744
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    References listed on IDEAS

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    1. World Bank, 2020. "Economic Analysis of Battery Energy Storage Systems," World Bank Publications - Reports 33971, The World Bank Group.
    2. Nottrott, A. & Kleissl, J. & Washom, B., 2013. "Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems," Renewable Energy, Elsevier, vol. 55(C), pages 230-240.
    3. Gitizadeh, Mohsen & Fakharzadegan, Hamid, 2014. "Battery capacity determination with respect to optimized energy dispatch schedule in grid-connected photovoltaic (PV) systems," Energy, Elsevier, vol. 65(C), pages 665-674.
    4. Khalilpour, Rajab & Vassallo, Anthony, 2016. "Planning and operation scheduling of PV-battery systems: A novel methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 194-208.
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