基于改进粒子群算法的风电火电联合调度方法

Combined Scheduling Method of Wind-Thermal Power Based on Improved Particle Swarm Optimization Algorithm

针对电力系统风电并网中出现的随机波动性与不确定性问题,建立风-火联合调度数学模型,并提出一种改进粒子群算法对该模型进行求解,以提高电力系统运行的经济性和可靠性。改进粒子群算法(Improved Particle Swarm Optimization,IPSO)从添加粒子速度自适应和添加位移更新自适应两方面对基本粒子算法(PSO)进行改进。仿真结果验证了IPSO具有更高的精度和更快的收敛速度。采用IPSO对10机组算例模型进行优化计算,计算结果验证了所建模型的正确性和所提改进算法的有效性。

In order to solve the problems of stochastic volatility and uncertainty in wind power system connected to the power system,a mathematical model of combine scheduling of wind-thermal power is established.A new improved particle swarm optimization algorithm (IPSO) is proposed to solve the mathematical model to improve the economics and reliability of power system operation.The proposed IPSO improves the basic particle swarm optimization (PSO) from two important aspects of adding adaptive particle velocity and adding adaptive displacement updating.Comparing with basic particle swarm optimization,the simulation results demonstrate that the proposed IPSO has higher accuracy and faster convergence speed.The optimization calculation of example model of 10 units is carried out by using IPSO.The calculation results verify the correctness of the mathematical mode and the effectiveness of the improved algorithm.