基于改进粒子群优化算法的微电网优化调度研究

Research on Optimal Scheduling of Microgrid Considering Environmental Factors

优化微电网中各个机组的出力是微电网优化调度中的重要课题。在考虑经济效益、环境效益、主网与微电网交互成本的基础上,构建了包含光伏、风机、柴油发电机、蓄电池的微电网优化调度模型。针对基本粒子群优化算法(PSO)在求解微电网优化调度问题易陷入局部最优、收敛速度慢等问题,提出基于黑洞机制和蝴蝶因子的粒子群优化算法(IRBHPSO-BOA)。通过MATLAB 2016a进行对比实验,结果表明IRBHPSO-BOA可以克服基本PSO、RBHPSO易早熟、陷入局部最优的缺点。将IRBHPSO-BOA用于解决微电网优化调度问题,结果表明IRBHPSO-BOA的求解效果和求解速度都优于其他两种算法,进一步验证了IRBHPSO-BOA的有效性。

Optimizing the output of each unit in the microgrid is an important issue in the optimization and scheduling of microgrid.On the basis of considering economic benefits,environmental benefits,and the interaction cost between main grid and microgrid,a microgrid optimal scheduling model including photovoltaic,wind turbines,diesel generators,and storage batteries is constructed.In view of the fact that the basic particle swarm optimization(PSO)algorithm is easy to fall into local optimization and slow convergence in solving the microgrid optimization scheduling problem,a particle swarm optimization algorithm based on black hole mechanism and butterfly factor(IRBHPSO-BOA)is proposed.MATLAB 2016a is employed to conduct a comparison experiment,and the results show that IRBHPSO-BOA can be used to overcome the shortcomings of basic PSO and RBHPSO,which are precocious and fall into local optimality.IRBHPSO-BOA is used to solve the optimization scheduling problem of microgrid,and the results show that IRBHPSO-BOA is better than the other two algorithms in both efficiency and speed,which further verifies the validity of IRBHPSO-BOA.