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Adoption of battery energy storage systems for behind-the-meters applicationoffers valuable benefits for demand charge management as well as increasingPV-utilization. The key point is that while the benefit/cost ratio for a singleapplication may not be favorable for economic benefits of storage systems,stacked services can provide multiple revenue streams for the same investment.Under this framework, we propose a model predictive controller to reduce demandcharge cost and enhance PV-utilization level simultaneously. Different loadpatterns have been considered in this study and results are compared to theconventional rule-based controller. The results verified that the proposedcontroller provides satisfactory performance by improving the PV-utilizationrate between 60% to 80% without significant changes in demand charge (DC)saving. Furthermore, our results suggest that batteries can be used forstacking multiple services to improve their benefits. Quantitative analysis forPV-utilization as a function of battery size and prediction time window hasalso been carried out.

Model Predictive BESS Control for Demand Charge Management and PV-Utilization Improvement