Energy Management in Smart Building by a Multi-Objective Optimization Model and Pascoletti-Serafini Scalarization Approach

Generally, energy management in smart buildings is formulated by mixed-integer linear programming, with different optimization goals. The most targeted goals are the minimization of electricity consumption cost, value from external power grid, and peak load smoothing. All these objectives desirable a building, however, related works, just one mentioned considered investigated. In this work, authors aim to consider two via multi-objective framework. regard, mixed-binary programming presented minimize total cost collective residential buildings, considering scheduling charging/discharging process for electric vehicles battery storage system. Then, Pascoletti-Serafini scalarization approach used obtain Pareto front solutions model. final, performance proposed model analyzed reported simulating under scenarios. results show that building has been reduced 35.56% 45.52% reduction.