Optimization Scheduling of Multi-Energy System Dispatch Considering Integrated Energy Storage

随着风电、光伏等可再生能源的快速发展，其装机容量持续增长。由于这类能源出力的随机性和波动性强，对电网的安全稳定运行构成了挑战，使得电力系统的调度难度显著增加。尽管蓄电池技术在多能源系统中具有重要作用，但其充放电容量有限、使用寿命较短以及投资成本较高，制约了其在能源系统中的大规模应用，影响了系统的经济性和运行灵活性。为了解决以上问题，文章将综合储能引入多能源系统中，建立了基于多能量存储的多能源系统调度模型，并采用多目标粒子群算法(MOPSO)求解。通过仿真结果验证了本文提出的储能设施的能量输入和输出以及可再生能源输出的协调优化模型具有良好的经济效益和大规模利用可再生能源的能力。With the rapid development of renewable energy sources such as wind and solar power, their installed capacity continues to grow. However, the inherent randomness and volatility of these energy outputs pose significant challenges to the safe and stable operation of the power grid, substantially increasing the difficulty of power system dispatching. Although battery storage technology plays a crucial role in multi-energy systems, its limited charge-discharge capacity, shorter lifespan, and high investment costs restrict its large-scale application in energy systems, thereby impacting the system’s economic efficiency and operational flexibility. To address these issues, this paper introduces integrated energy storage into the multi-energy system, establishing a multi-energy system dispatching model based on multi-energy storage. The model is solved using a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Simulation results demonstrate that the proposed coordinated optimization model for energy input and output of storage facilities and renewable energy output exhibits good economic benefits and the capability to enable large-scale utilization of renewable energy.