A novel dynamic two-stage controller of battery energy storage system for maximum demand reductions

Demand response with battery energy storage systems (BESS) provides the most flexible peak reduction solution for different markets. One of the major challenges is the optimization of the demand threshold that controls the charging and discharging powers of BESS. To increase its tolerance to day-ahead prediction errors, state-of-art controllers utilize rigid parameters that are determined from long-term historical data. However, long-term historical data may be unavailable at implementation, and rigid parameters cause them unable to adapt to evolving load patterns. To tackle this issue, this article proposes a novel dynamic two-stage maximum demand reduction controller using BESS that incorporates 1-h-ahead load profiles to refine the threshold found based on day-ahead load profile and prevent peak reduction failure if necessary. The dynamic controller needs no rigid parameters and can begin its daily peak reduction with just 30 days of historical data. Compared to the conventional fixed threshold, single-stage, and fuzzy controllers, the proposed two-stage controller achieves up to 6.82% and 306.23% higher in average maximum demand reduction and total maximum demand charge savings, respectively, on two different datasets. The proposed controller also achieves a 0% peak demand reduction failure rate in both datasets, demonstrating its peak demand reduction prevention capability.