A novel energy management system for optimal energy and flexibility scheduling of residential buildings: a case study in HSB Living Lab

The future distribution system needs more flexibility to handle the peak power demand arising from the electrification of heating and transportation. This paper proposes a novel energy management system (EMS) for residential buildings to optimize their electric and heat consumptions while offering flexibility in response to the requirements of the Distribution System Operator (DSO). The aim of the proposed EMS is to minimize the energy and peak power costs while simultaneously maximizing the revenue from offering flexibility. This is achieved through the optimal scheduling of battery energy storage charging and discharging as well as the efficient utilization of the heat pump. To cope with forecasting uncertainties, a rolling horizon-based algorithm with uncertainty modelling based on the chance constraint method is incorporated. The performance of the proposed EMS is investigated by simulating the daily operation of a real residential building. The case studies indicate that the scheduled flexibility can be successfully dispatched even in the presence of forecasting uncertainties, causing 6% reduction in the payment cost of the building