LAUSR

Abstract Incorporation of energy storage (ES) with existing power system networks for economic and technical purposes, is on the rise. ES systems are employed for enhancing the operation of power systems through offering several ancillary services; such as frequency and voltage regulation, and operation reserve. Further, ES are used for money-making intent such as energy arbitrage (EA) and lessening utility energy charges such as demand charges. In this paper, a novel algorithm is proposed to reduce the utility charges of global adjustment (GA) for a large customer in the Canadian province, Ontario. The proposed algorithm optimizes the size of the battery storage system (BSS) and its schedules. In the developed algorithm, BSS is optimally deployed to minimize the charges associated with GA and demand charges (DC) for class-A customers in Ontario jurisdiction. Furthermore, BSS is employed for secondary profit-gaining missions such as behind-meter energy arbitrage (EA), demand response (DR). The developed algorithm is tested using real data of a class-A customers in Ontario. Obtained results show the economic feasibility employing BSS for bill reduction using the proposed method. Further, detailed sensitivity studies on several parameters of the developed method are presented showing the performance and potential of the algorithm for making profits.