Development and analysis of an energy storage sizing tool for residential deployment

Starke, Michael; Sawyer, Nevin; Dean, Benjamin; Smith, Mitch; Liu, Guodong; Spiers, Dirk; Schultz, Bryan; Harman, Harvey

doi:10.1109/pesgm.2017.8273752

Cited by 3 publications

(1 citation statement)

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“…Several studies have addressed residential BESS sizing, operation, and profitability. In [5], Mixed-Integer Linear Programming is employed for residential BESS system sizing to leverage the financial benefits. In [6], an energy management model based on convex programming is introduced to size the residential BESS with PV to maximize the installation profitability.…”

Section: Introductionmentioning

confidence: 99%

Residential Battery Energy Storage Sizing and Profitability in the Presence of PV and EV

Mohamed

Best

Liu

et al. 2021

2021 IEEE Madrid PowerTech

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Residential battery energy storage systems (BESS) are having an important role in transitioning towards low carbon communities. However, BESS capital cost remains questionable. In this work, an optimization-based BESS sizing algorithm is developed to maximize the customer's profitability by minimizing the electricity import for 162 combinations of demand, solar photovoltaic (PV) and electric vehicle (EV). The sizing algorithm results are utilized in introducing empirical formulas that ease the determination of the near-optimal BESS capacity. The annual savings are quantified for various cases under different tariff rates and the BESS viability is investigated for new installations over the next 10 years. The results show that the residential BESS can be profitable in the UK starting from 2024 without any subsidy for the time of use tariffs.

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Section: Introductionmentioning

confidence: 99%