Reducing demand charges and onsite generation variability using behind-the-meter energy storage

Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. Such directive is bringing potential opportunities in deploying behind-the-meter energy storage (BMES) systems for various grid applications. This study quantifies the techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with different penetration of onsite photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines the cost-optimal BMES configuration for reducing peak demands and demand charges and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of the proposed algorithm is evaluated through a 24-hours time sweep simulation performed using data from a smart microgrid testbed at Idaho National Laboratory. The simulation results demonstrated that this research provides a simple and effective solution for peak shaving, demand charge reductions, and onsite photovoltaic variability smoothing.