CAJ | 학술논문

自适应聚焦粒子群算法(AFPSO)是根据PSO算法的全局搜索与局部搜索平衡特性,改进得到的一种具有较好全局搜索能力和寻优速度的自适应群体智能优化算法.通过采用AFPSO算法,对电力系统进行无功优化.该方法是以最优控制原理为基础,以网损最小为目标函数,在IEEE 30节点系统上进行测试,通过仿真测试以及不同算法优化结果的对比,表明基于AFPSO算法在算法计算精度、收敛稳定性、寻优时间等方面都具有普遍优势,能有效地应用于电力系统无功优化中,证明了AFPSO算法的有效性和优越性.
자괄응취초입자군산법(AFPSO)시근거PSO산법적전국수색여국부수색평형특성,개진득도적일충구유교호전국수색능력화심우속도적자괄응군체지능우화산법.통과채용AFPSO산법,대전력계통진행무공우화.해방법시이최우공제원리위기출,이망손최소위목표함수,재IEEE 30절점계통상진행측시,통과방진측시이급불동산법우화결과적대비,표명기우AFPSO산법재산법계산정도、수렴은정성、심우시간등방면도구유보편우세,능유효지응용우전력계통무공우화중,증명료AFPSO산법적유효성화우월성.
Adaptive focusing particle swarm optimization (AFPSO) based on the balance characteristic between global search and local search of particle swarm optimization is an adaptive swarm intelligence optimization algorithm with preferable ability of global search and search rate. AFPSO is proposed to optimize the reactive power optimization. Based on optimal control principle, AFPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. The modeling of reactive power optimization is established by taking the minimum network losses as the objective. The simulation results and the comparison results with various optimization algorithms demonstrate that the proposed approach converges to better solutions much faster than the earlier reported approaches and the algorithm can make effectively use in reactive power optimization. Simultaneously, the validity and superiority of AFPSO is proved.