UC San Diego

Battery Energy Storage Systems (BESS) are often used for demand charge reduction through monthly peak shaving. The effect of two temporal resolutions, 15-min and 1-hour, on peak shaving is compared across a battery ratings space defined by power capacity and energy capacity of the battery. Based on the 15-min load of a particular day, a critical power and critical energy can be defined, yielding a critical point in the power- energy space. A linear program of the system optimizes the peak of the net load and the associated demand charge assuming perfect forecasts. Based on the difference of demand charge (DODC) across the two load profiles at high and low temporal resolution for a real building, the battery rating space is divided into three different regions: optimal region, power-constrained region, and energy-constrained region, which can be identified by the critical power (CP) and critical energy (CE) derived from the load profile. As the conclusion shows, the DODC in the power-constrained and energy-constrained regions is explained by the averaging operation and the load sequence at high resolution. In the power-constrained region of the battery rating space, the difference between the original 15 min peak and the 1 hour average peak persists in the optimized net load until the battery power capacity is sufficiently large. In the energy-constrained region, averaging may change the peak period duration, which depends on the sub-hourly sequence of the original load data. Through artificial load data and reordering of real load data, we demonstrate that the sequence effect causes energy-constrained batteries to underestimate peak shaving and demand charge reduction.