基于改进粒子群算法的多能微网多目标优化调度

为实现多能微网内部能源的灵活调用，减轻系统碳排放压力，文中提出了一种基于改进粒子群(particle swarm optimization, PSO)算法的多能微网多目标优化调度方法。建立了冷热电气多能微网模型，分析系统能源耦合机理并对设备进行数学建模；以微网运行成本与环境成本最小为目标，构建多能微网多目标优化调度模型；提出一种改进PSO算法，通过调整主要参数的迭代规则，并采用自适应粒子寻优策略加快收敛速度，提升寻优效果；仿真结果表明：与传统方法相比，所提基于改进PSO算法的多目标优化调度方法能够有效提升算法收敛速度、降低系统综合成本，兼顾其运行的经济性与环境友好性。

Multi-objective optimal dispatch for multi-energy microgrid based on improved particle swarm optimization algorithm

In order to flexible deployment of internal energy in the multi-energy microgrid, and reduce its carbon emission pressure, this paper proposes a multi-objective optimal dispatch method for multi-energy microgrid based on improved PSO algorithm. Firstly, a multi-energy microgrid model is established. Based on this model, the coupling mechanism between various energy sources is analyzed and the mathematical models of system equipment are established. Secondly, with the goal of minimizing the operating cost and environmental cost of the microgrid, the multi-objective optimization scheduling model is constructed. Then, an improved PSO algorithm is proposed. This algorithm can accelerate convergence speed and improve optimization performance by adjusting the iteration rules of the main parameters and adopting the adaptive particle optimization strategy. Finally, simulation results verify that compared with the conventional methods, the proposed multi-objective optimal dispatch method based on improved PSO algorithm can effectively accelerate algorithm convergence speed, reduce the overall cost of the system, and balance its operational economy and environmental friendliness.