Electricity Cost Optimization for Large Loads through Energy Storage and Renewable Energy

Demand charge contributes to a significant portion of the electric bill for large electric loads. Shaving peak demand and adopting optimal demand management strategies can reduce this cost significantly. This paper deals with an optimization problem to reduce the electricity cost for a bulk load with the help of energy storage and renewable energy. An optimal demand control strategy is developed based on the formulated problem that aims to minimize the total electricity cost. The optimization problem was solved using the MATLAB based modeling system CVX. The system considered here is a real system that is situated in University of California, Riverside. Available renewable energy (solar) prediction data and lithium iron phosphate battery data has been used for the simulation purpose. Two different strategies, battery only strategy and battery with solar strategy, are tested with the proposed strategy. The results are validated with National Renewable Energy Laboratory (NREL) developed System Advisor Model (SAM). The results show that 14.5-15.4% peak reduction is possible which leads to a monthly savings of $6,410 to $38,820.