A capacity optimization method for the battery energy storage system based on historical electricity data of existing buildings

The battery energy storage system (BESS) has attracted increasing attention due to its flexibility and economy. How to determine the optimal capacity of BESS is crucial. This study presents a global battery capacity optimization method for existing buildings based on the historical load, by maximizing the annualized net revenue (ANR). Multiple practical constraints are considered, including the battery degradation, the charging/discharging efficiency and rate, the state of charge, the depth of discharge, and the transformer capacity. Sensitivity analysis is conducted to explore the impact of battery price, depth of discharge, and charging/discharging efficiency on the capacity optimization. To validate the proposed method, two buildings with different load characteristics (peak-preference and off-peak-preference) are selected with monitored yearly sub-hourly loads. Results show that the proposed method can effectively identify the global optimal capacity of the BESS for the buildings. The annual electricity bills can be reduced by 9.2 %, with an IRR of 10.2 % and a payback period of 6.8 years under the current energy market. When the battery price decreases by 50 %, the IRR can be increased by 7.06 % and the payback period can be less than 5.2 years. The practical constraints have important impacts on the capacity of BESS. Without considering them, both the optimal capacity and benefits of the BESS would be overestimated, and affect the investment decision-making. This study provides an effective solution for optimizing the capacity of the battery energy storage systems in existing buildings.