摘要
由于粒子群优化算法在优化计算中存在早熟收敛,易陷入局部最优且搜索精度不高等缺点,在现有粒子群优化算法的基础上融合模拟退火算法对其进行改进,得到改进后的模拟退火粒子群优化算法,并将其应用到风光互补发电系统混合储能单元容量的优化配置中。优化结果表明,在满足负荷用电的前提下,该算法可有效降低储能单元的投资成本和运行费用,从而证明了算法的正确性。
For the purpose to solve the problem that the standard PSO has disadvantages such as earliness, easily trapped in local best and low searching precision, the improved simulated annealing particle swarm optimization （SAPSO） algorithm were proposed based on particle swarm optimization algorithm that fusing simulated annealing algorithm, and which is applied to capacity optimization of hybrid energy storage units in wind/solar generation system. The optimization results showed that the algorithm can effectively reduce improve ment of the investment and operation cost of hybrid storage unit under the prerequisite for satisfying the load demand, and the correctness and validity of the proposed algorithm was demonstrated.
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2015年第3期756-762,共7页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(61105063)
关键词
风光互补发电系统
混合储能
蓄电池
超级电容器
容量优化
模拟退火粒子群优化算法
wind/solar generating system
hybrid energy storage
battery
uhracapacitor
capacity optimization
simulated annealing particle swarm optimization （SAPSO） algorithm
