多目标免疫克隆算法在多类型分布式电源规划中的应用

发布时间：2018-06-05 15:30

本文选题：分布式电源 + 多目标免疫克隆算法　；参考：《长沙理工大学》2014年硕士论文

【摘要】：分布式电源由于其具有发电方式灵活、建设周期短、污染排放少等优点得到了迅速发展。然而,随着分布式电源大量接入配电网,其接入位置和容量对电力系统的网络损耗、电压分布、可靠性和系统保护都产生了很大的影响,因此,研究如何更合理地规划分布式电源对实现配网系统安全经济运行具有重要意义。论文首先阐述了分布式发电的研究意义和发展状况,在综述了分布式电源规划研究现状的基础上,对多种分布式发电技术及其对配电网的影响进行了较详细的分析；针对风力发电和光伏发电出力不稳定以及负荷波动的特点,提出了考虑其时序特性的分布式电源规划模型；在研究了多种分布式电源出力特性的基础上,采用储能装置平滑风电和光伏发电出力的波动；进而建立了兼顾系统运行经济性和稳定性以及环境因素的多目标规划模型；采用多目标免疫克隆算法进行模型求解,该算法采用整体克隆非支配抗体、非一致性变异和删除帕累托(Pareto)前端密集解的策略来保证收敛速度和解的均匀性与宽广性；通过三个经典的测试函数,运用三个性能指标对算法进行评价,同时与改进非劣分层遗传算法和改进强度帕累托进化算法两种经典多目标算法进行比较,验证多目标免疫克隆算法的优越性。采用IEEE33节点的配电网系统进行算例仿真分析,将多目标免疫克隆算法与改进非劣分层遗传算法的求解结果进行比较分析,验证了多目标免疫克隆算法求解分布式电源规划模型的有效性。论文所建的规划模型考虑了多种分布式电源出力与负荷的不稳定性,使得规划结果更接近于实际,具有一定的实用价值与指导意义。
[Abstract]:Because of its advantages of flexible power generation mode, short construction period and less pollution emission, distributed power generation has been developed rapidly. However, with a large number of distributed power sources connected to the distribution network, its access position and capacity have a great impact on the network loss, voltage distribution, reliability and system protection of the power system. It is very important to study how to plan the distributed power supply more reasonably to realize the safe and economical operation of distribution network system. Firstly, the research significance and development status of distributed generation are described in this paper. On the basis of summarizing the present situation of distributed generation planning, various distributed generation technologies and their effects on distribution network are analyzed in detail. According to the characteristics of instability and load fluctuation of wind power generation and photovoltaic power generation, a distributed power generation planning model considering its timing characteristics is proposed. The energy storage device is used to smooth the fluctuation of wind power and photovoltaic power generation, and then a multi-objective programming model considering the economic and stability of the system as well as environmental factors is established, and the multi-objective immune clone algorithm is used to solve the model. The algorithm adopts the strategy of global cloning of non-dominant antibodies, inconsistency mutation and deletion of Pareto-Pareto front-end dense solutions to ensure convergence speed and uniformity and broadness, and through three classical test functions, Three performance indexes are used to evaluate the algorithm, and compared with the improved non-inferior hierarchical genetic algorithm and the improved strength Pareto evolutionary algorithm, the superiority of the multi-objective immune clone algorithm is verified. The simulation analysis of distribution network system with IEEE 33 node is carried out, and the results of multi-objective immune clone algorithm and improved non-inferior hierarchical genetic algorithm are compared and analyzed. The effectiveness of the multi-objective immune clone algorithm for solving the distributed power planning model is verified. The planning model proposed in this paper takes into account the instability of the output and load of various distributed power sources, which makes the planning results closer to the actual situation, and has certain practical value and guiding significance.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM715

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