摘要
以系统有功网损最小为目标,建立了一种电力系统无功优化数学模型,并提出了一种基于量子差分进化算法的电力系统无功优化方法。该算法采用量子计算中的并行、坍缩等特性,增强了对解空间的遍历能力;同时在传统选择策略的基础上加入了量子计算的概率表达特性,有效地避免了算法的早熟现象。对IEEE-30节点测试系统进行仿真分析,并将优化结果与传统差分进化算法和粒子群优化算法进行对比分析,结果表明量子差分进化算法在解决系统无功优化问题上更科学、更有效。
A reactive power optimization model is established to realize the lowest active power loss of power system, and a quantum differential evolution （QDE） algorithm is proposed to solve the model. The algorithm takes advantage of parallel and collapse properties of the quantum calculation theory, owning better ergodic ability for the solution space. At the same time, possibility expression property of quantum bit in traditional selection strategy is considered which makes it easier to avoid premature phenomenon. The reactive power optimization for IEEE 30-bus system is performed by using traditional differential evolution algorithm, particle swarm optimization algorithm and quantum differential evolution algorithm. The comparison analysis of three algorithms shows that the quantum differential evolution algorithm is more scientific and efficient in dealing with reactive power optimization.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2013年第17期39-43,共5页
Power System Protection and Control
关键词
无功优化
电压控制
量子差分进化算法
reactive power optimization
voltage control
quantum differential evolution algorithm
