A proactive-adaptive monthly peak demand-limiting strategy for buildings with small-scale thermal storages considering load uncertainty

Abstract

Peak demand limiting is an efficient means to reduce the monthly electricity cost in a billing period (typically a month) in cases where peak demand charge is applied. This article presents an online proactive-adaptive peak demand-limiting strategy for buildings with very small-scale thermal energy storages considering load uncertainty in a billing cycle. The proposed strategy involves three major functions, as follows. First, the probabilistic demand profiles are forecast using a building load model. Second, the adaptive optimal monthly limiting threshold is identified using an optimal threshold resetting scheme based on the forecasted probabilistic demand profiles. Third, a proactive-adaptive demand-limiting control scheme is developed to online update the limiting threshold and conduct online limiting control before using up the storage capacity. Real-time tests are conducted, and the results show that this strategy can effectively reduce the monthly peak demand cost for buildings with small-scale thermal storages under load uncertainty.