Optimal energy management of smart building for peak shaving considering multi-energy flexibility measures

Abstract

Multi-energy flexibility measures comprising energy substitution and demand-side management (DSM) can enhance the control of buildings and help them participate in the energy market, obtaining greater profit margins. However, the application of these flexibility measures is also subject to many limitations. For example, DSM is a kind of load redistribution process in which the energy payback constraints associated with comfort or usage demand should be considered. Therefore, this work studies the optimal energy management of a building energy system (BES) considering multi-energy flexibility measures, specifically under the energy payback effect, to better guide the peak shaving strategies. First, energy substitution measures are proposed involving energy conversion and storage modeling. Second, a novel dynamic two-step DSM measure is modeled for the reduction and recovery process. Then, a mixed-integer and linear programming (MILP)-based energy management model is developed to optimize the operation of smart buildings for peak shaving. The case studies demonstrate that 1) a BES can obtain better profit by utilizing multi-energy flexibility measures; 2) optimized multi-load recovery strategies can enhance the flexibility potential of a BES; and 3) a reasonable multi-load recovery mechanism should be established to offset the energy payback effect.