Maximizing the cost-savings for time-of-use and net-metering customers using behind-the-meter energy storage systems

The transformation of today's grid toward smart grid has given the energy storage systems (ESSs) the opportunity to provide more services to the electric grid as well as the end customers. On the grid's side, ESSs can generate revenue streams participating in electricity markets by providing services such as energy arbitrage, frequency regulation or spinning reserves. On the customers' side, ESSs can provide a wide range of applications from on-site back-up power, storage for off-grid renewable systems to solutions for load shifting and peak shaving for commercial/industrial businesses. In this work, we provide an economic analysis of behind-the-meter (BTM) ESSs. A nonlinear optimization problem is formulated to find the optimal operating scheme for ESSs to minimize the energy and demand charges of time-of-use (TOU) customers, or to minimize the energy charge of net-metering (NEM) customers. The problem is then transformed to Linear Programming (LP) problems and formulated using Pyomo optimization modeling language. Case studies are conducted for PG&E's residential and commercial customers in San Francisco.