考虑时序与储能配合的分布式电源优化配置研究

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (4983 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Based on the typical sequential characteristic of different types of load and distributed generation (DG), considering the environmental cost of different types of pollutants and Energy storage efficiency,a multi-objective optimal allocation model of DG and energy storage equipment is established, which is applied to obtain the minimum annual social cost, annual electricity purchasing cost, annual environmental cost, annual reliability cost and voltage deviation. The model executes collaborative optimization of the location and capacity of DG and energy storage equipment based on the sequential characteristic of load and DG output. Meanwhile, to solve the problems that the NSGA-II algorithm has low initialization diversity, the probability of crossover mutation is constant and the convergence rate is low, the theory of cloud model is integrated into NSGA-II and the improved model is applied to optimize the model, the 1-9 scales method and membership function are combined to evaluate the results of optimization. Last, the model is simulated in IEEE-33 node system, the simulation results show that the model and algorithm can effectively optimize the site and capacity of DG and energy storage equipment.

Key words： energystorage equipment cloud model NSGA-II algorithm sequential characteristic distributed generation

Published: 28 June 2017

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Chen Congwei
	Jiang Xiubo
	Liu Lijun

Cite this article:

Chen Congwei,Jiang Xiubo,Liu Lijun. Study on the Optimization of Distributed Generation Considering the Cooperation of Sequential Characteristic and Energy Storage Equipment[J]. Electrical Engineering, 2017, 18(6): 41-47.

URL:

http://dqjs.cesmedia.cn/EN/Y2017/V18/I6/41

[1] 夏澍, 周明, 李庚银. 分布式电源选址定容的多目标优化算法[J]. 电网技术, 2011, 35(9): 115-121.
[2] 栗然, 马慧卓, 祝晋尧, 等. 分布式电源接入配电网多目标优化规划[J]. 电力自动化设备, 2014, 34(1): 6-13.
[3] 李亮, 唐巍, 白牧可, 等. 考虑时序特性的多目标分布式电源选址定容规划[J]. 电力系统自动化, 2013, 37(3): 58-63, 128.
[4] 张节潭, 程浩忠, 姚良忠, 等. 分布式风电源选址定容规划研究[J]. 中国电机工程学报, 2009, 29(16): 1-7.
[5] 李洪志, 杨俊友, 崔嘉. 考虑网损和电压的多分布式电源最优选址和定容研究[J]. 电气工程学报, 2015, 10(9): 79-86.
[6] 张沈习, 李珂, 程浩忠, 等. 间歇性分布式电源在主动配电网中的优化配置[J]. 电力自动化设备, 2015, 35(11): 45-51.
[7] 苏海锋, 胡梦锦, 梁志瑞. 基于时序特性含储能装置的布式电源规划[J]. 电力自动化设备, 2016, 36(6): 56-70.
[8] Pesaran M, Abdullah A M Z, Khairuddin A, et al. Optimal sizing and siting of distributed generators by a weighted exhaustive search[J]. Electric Power Components and Systems, 2014, 4211.
[9] Guerra G, Juan A. Martinez-Velasco. Optimum allocation of distributed generation in multi-feeder systems using long term evaluation and assuming voltage-dependent loads[J]. Sustainable Energy, Grids and Networks, 2016, 5.
[10] 郭凤鸣. 基于云模型遗传算法的研究[D]. 南京: 南京理工大学, 2013.
[11] 钟清, 余南华, 孙闻, 等. 主动配电网分布式电源规划及经济性分析[J]. 电力系统及其自动化学报, 2014, 26(11): 82-86.
[12] 张建华, 曾博, 张玉莹, 等. 主动配电网规划关键问题与研究展望[J]. 电工技术学报, 2014(2): 13-23.
[13] 沈鑫, 曹敏. 分布式发电接入主动配电网的全局优化与研究[J]. 电气制造, 2015, 10(6): 67-70, 77.
[14] 张燕, 李瑞超. 分析分布式电源入网对配电网供电可靠性的影响[J]. 电子测试, 2016(9): 124, 123.
[15] 李文文. 配电网中分布式电源的优化配置研究[D]. 吉林: 东北电力大学, 2015.
[16] 张跃, 杨汾艳, 曾杰, 等. 主动配电网的分布式电源优化规划方案研究[J]. 电力系统保护与控制, 2015, 8(15): 67-72.