Coordinated Multi-Time Scale Optimal Control of Building Energy Systems for Demand Response Considering Forecast Uncertainties

As an economical way to address the great challenge from increasing renewable energy generation of intermittent nature, demand response is attracting increasing attention recently. Predictive scheduling is widely used to optimize energy dispatch of building energy systems for demand response, since it can minimize cost considering time-varying electricity price. However, it probably cannot satisfy energy demands and achieve optimized demand response in actual operation due to forecast uncertainties. In this study, a coordinated multi-time scale optimal control strategy is therefore proposed to optimize energy dispatch between building energy systems for demand response considering forecast uncertainties. The control strategy coordinates a stochastic scheduling scheme and a real-time optimal control scheme using coordinating control variables. The selection of coordinating control variables is comprehensively analyzed. The optimal start time of scheduling optimization horizon is identified. Forecast uncertainties are quantified based on real meteorological data. The proposed control strategy was tested and evaluated on the energy system of the Zero Carbon Building in Hong Kong. Results show that it is essential and beneficial to consider forecast uncertainties and coordinate stochastic scheduling with real-time optimal control to ensure satisfaction of energy demands and minimization of energy cost in actual operation when providing demand response.