Generation and Load Integrated Optimal Scheduling Incorporating Distributed Energy Storage and Adjustable Load

The rapid development of renewable energy and adjustable load has brought challenges to the safety and economic operation of power system. In this paper, we propose a generation and load integrated optimal scheduling strategy. The power generation side considers the wind-photovoltaic hybrid power system with battery energy storage system. The user side considers electric vehicles and the adjustable load such as transferable load and interruptible load to participate in scheduling. A scheduling strategy model is established to optimize both the benefits of power generation side and the user side. The multi-objective particle swarm optimization algorithm is used to solve the model. Simulation results based on historical data of a particular region (105.0 degrees E, 35.4 degrees N) show the feasibility of the proposed optimal scheduling strategy.