基于量子粒子群算法的风火打捆容量及直流落点优化配置  

Optimal Configuration of Wind & Coal Power Capacity and DC Placement Based on Quantum PSO Algorithm

作　　者：王智冬[1] 刘连光[1] 刘自发[1] 王帅[2] 由子昂 

机构地区：[1]华北电力大学电气与电子工程学院,北京市昌平区102206 [2]国网北京经济技术研究院,北京市昌平区102209

出　　处：《中国电机工程学报》2014年第13期2055-2062,共8页Proceedings of the CSEE

摘　　要：针对如何根据调峰容量等约束条件,优化风电、火电容量配置及送电落点问题,以风电外送输电工程建设投资、输电损耗和弃风电量损失为优化目标函数,提出以功率平衡、风电变化速率与火电调节速度匹配为约束条件,基于量子粒子群优化算法研究直流外送落点及风火打捆容量的优化配置问题。量子粒子群优化算法采用量子理论中的叠加态特性和概率表达特性,潜在地增加了粒子群算法中种群的空间分布多样性和全局寻优能力。运用量子粒子群优化算法以及构建的优化模型,以解决我国风电跨区消纳为目的,对某实际规划区域的风火容量进行优化配置,证明了所提模型和方法科学、有效。To deal with the problems of optimal configuration of wind ＆ coal combined transmission, capacity allocation and high voltage DC （HVDC） location with the constraints of power system security and peak load regulating capacity, a comprehensively optimal objective function was established in this paper. The proposed model includes the HVDC construction Costs, operation losses and costs of wind power curtailment. Moreover, the constraints include power balance, changing rate of wind power and coal power ramp rate An algorithm of quantum particle swarm optimization （QPSO） was put forward to solve the objective function. The algorithm uses the advantages of probability expression and superposition state, which potentially improve the optimal ability. Besides, mutation operation of QPSO was useful for maintaining the diversity of population. The analysis results prove that the proposed model and algorithm are scientific and effective.

关 键 词：风火打捆 容量分配 直流落点 量子粒子群算法 调峰容量 

分 类 号：TM715[电气工程—电力系统及自动化]