Peak Load Shaving in Virtual Power Plants Utilizing Mixed Integer Linear Programming

This paper proposes a virtual power plant (VPP) peak load shaving control strategy that takes into account both safety and economic factors, aiming to reduce operational costs for the power system. By employing mixed integer linear programming (MILP), the strategy minimizes energy and demand charges, effectively shaving peak load demands. It optimizes embedded energy resources (EERs), including distributed energy storage (DES) and renewable energy sources (RES), to decrease load during peak times. Additionally, demand response (DR) is utilized during peak periods to limit the use of consumers' electric water heaters (EWH), heat pumps (HP), and baseboard heater (BBH). The results demonstrate that the proposed control strategy can shave up to three daily load peaks, meeting the requirements for safety and reliability while enhancing the economic benefits for power companies and consumers.