基于改进粒子群算法考虑阀点效应的经济负荷最优分配

经济分配对于电力系统节能至关重要,是电网中一类典型的优化问题,基于传统的粒子群算法的优化方法由于仅考虑速度与位置参数,易导致局部最优。针对电力系统的有功经济分配,考虑发电机组的阀点效应,提出一种改进型粒子群算法。通过引进视角参数,使粒子的移动状态受到视角的制约,改善传统算法粒子容易早熟而陷入局部最优的缺陷,降低搜索随机性并提高优化精度’仿真结论表明,带有视角参数的改进粒子群算法有更高效的全局搜索能力和更可靠的最优解,为发电机有功经济分配问题提供一种有效的新算法。

Optimal distribution of economic loads based on the improved particle swarm optimization considering valve-point effects

Economic distribution(ED)is a typical optimization problem of power grid and it is also very important for power system energy saving.However,the optimization method based on the traditional particle swarm algorithm only considers speed and position parameters,which easily leads to local optimiza tion.Under this background,taking into account the valve-point effeet of generators,an improved particle swarm algorithm is proposed for the active power distribution of power systems.The perspective parameter is introduced,and then the moving state of particle is decided by the new high-dimensional parameters.The proposed algorithm can avoid the local optimal,reduce the search randomness and improve the optimization accuracy.Simulation results shows that the improved particle swarm algorithm with viewing angle parameters has a more fficient global search capability and a more reliable optimal solu-tion,which provides an effective new algorithm for the power system economic distribution problem.