求解电力库模式下竞价管理问题的改进粒子群算法

提出了一种新的用于求解电力库模式下竞价管理问题的改进粒子群算法，改善了基本粒子群优化算法收敛精度不高且易陷入局部极值的缺点。每个粒子的速度和位置的更新不仅考虑了自身个体极值和全局极值的信息，还考虑了其他粒子所包含的信息，并通过改变惯性权重保持了群体的多样性。通过收敛性分析可知，该算法能较好地收敛到最优解。算例结果表明本文提出的算法比其他算法更具有优越性。

A Modified Particle Swarm Optimization Algorithm for Bidding Management in Power Pool Environment

A modified particle swarm optimization (MPSO) algorithm for bidding management in power pool environment is presented, it remedies the defects in basic particle swarm optimization (PSO) such as low convergence accuracy and easy to fall in with premature convergence. In the renewal of each particle’s speed and position not only the information of its own individual extremum and global extremum are considered, but also the information of other particles. By means of changing inertia weight the diversity of the particle swarm can be retained. The results of convergence analysis show that the modified algorithm can converge to optimal solution. Results of calculation examples show that the solution of MPSO algorithm possesses more advantages than other algorithms.