计及风电消纳效益的电力系统源荷协调二层优化模型

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (1102 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract With large-scale wind power access, its stochastic and intermittent increases the regulation pressure of conventional power, and the characteristic of reverse distribution with conventional energy also makes the regulation ability of conventional power constrained by transmission channel, and results in wind power consumptive blocked. This paper uses the high energy load as an important means of wind power consumptive, and combines the optimal scheduling of conventional power with the optimal allocation of high energy load, and establishes a bi-level optimal model with the source-load coordination benefits maximized which including the system operation cost, the adjustment cost of high energy load, and the wind power consumptive benefits. The operation situation of conventional power and the scheduling plan of wind power are calculated by the upper model; and then, the lower model is to determine appropriate high energy load to consume blocked wind power effectively and minimize adjustment cost at the same time with regard to the wind power consumptive blocked caused by lacking of conventional power regulating capacity. According to the difference between the decision variables of upper level model and lower level model, the hybrid intelligent optimization algorithm which combines the improved genetic algorithm with the binary particle swarm algorithm is used to solve this model. The simulation results of actual power grid verified the feasibility and effectiveness of this model.

Key words： Wind Power high energy load source-load coordination consumptive benefits bi-level optimal model hybrid intelligent algorithm

Received: 14 April 2013 Published: 25 May 2015

PACS:

TM614

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Wen Jing
	Liu Wenying
	Xie Chang
	Wang Weizhou

Cite this article:

Wen Jing,Liu Wenying,Xie Chang等. Source-Load Coordination Optimal Model Considering Wind Power Consumptive Benefits Based on Bi-Level Programming[J]. Transactions of China Electrotechnical Society, 2015, 30(8): 247-256.

URL:

http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2015/V30/I8/247

[1] 白建华, 辛颂旭, 贾德香, 等. 中国风电开发消纳及输送相关重大问题研究[J]. 电网与清洁能源, 2010, 26(1): 14-17. Bai Jianhua, Xin Songxu, Jia Dexiang, et al. Study of major questions of wind power digestion and trans- mission in China[J]. Power System and Clean Energy, 2010, 26(1): 14-17.
[2] 侯婷婷, 娄素华, 吴耀武, 等. 含大型风电场的电力系统调峰运行特性分析[J]. 电工技术学报, 2013, 28(5): 105-111. Hou Tingting, Lou Suhua, Wu Yaowu, et al. Analysis on peak load regulation operation characteristics of power system integrated with large-scale wind power [J]. Transactions of China Electrotechnical Society, 2013, 28(5): 105-111.
[3] 肖创英, 汪宁渤, 丁坤, 等. 甘肃酒泉风电功率调节方式的研究[J]. 中国电机工程学报, 2010, 30(10): 1-7. Xiao Chuangying, Wang Ningbo, Ding Kun, et al. System power regulation scheme for Jiuquan wind power base[J]. Proceedings of the CSEE, 2010, 30(10): 1-7.
[4] 姚明涛, 胡兆光, 张宁, 等. 工业负荷提供辅助服务的多智能体响应模拟[J]. 中国电机工程学报, 2014, 34(25): 4219-4226. Yao Mingtao, Hu Zhaoguang, Zhang Ning, et al. Multi-agent response simulation of industrial loads for ancillary services[J]. Proceedings of the CSEE, 2014, 34(25): 4219-4226.
[5] 姚建国, 杨胜春, 王珂, 等. 智能电网“源—网—荷”互动运行控制概念及研究框架[J]. 电力系统自动化, 2012, 36(2): 1-6. Yao Jianguo, Yang Shengchun, Wang Ke, et al. Concept and research framework of smart grid “source-grid- load” interactive operation and control[J]. Automation of Electric Power Systems, 2012, 36(2): 1-6.
[6] 马林东, 葛智平, 张世才, 等. 基于高耗能企业参与电网内风电消纳的主动调峰技术[J]. 电力建设, 2013, 34(10): 102-106. Ma Lindong, Ge Zhiping, Zhang Shicai, et al. Active peaking technology based on high energy-consumption enterprise participating in wind power accommodation in power grid[J]. Electric Power Construction, 2013, 34(10): 102-106.
[7] Bashash S, Fathy H K. Modeling and control of aggregate air conditioning loads for robust renewable power management[J]. IEEE Transactions on Control Systems Technology, 2013, 21(4): 1318-1327.
[8] Junji Kondoh. Direct Load Control for Wind Power Integration[C]. IEEE Power & Energy Society General Meeting, Detroit, USA, 2011.
[9] Teleke S, Baran M E, Huang A Q. Control strategies for battery energy storage for wind farm dispatching [J]. IEEE Transactions on Energy Conversion, 2009, 24(03): 725-732.
[10] Zakariazadeh A, Alinezhad L, Jadid S. Optimum simultaneous clearing of energy and spinning reserve markets with high penetration of wind power[C]. Power and Energy Engineering Conference(APPEEC), Chengdu, China, 2010.
[11] Weihao Hu, Chi Su, Zhe Chen, et al. Optimal opera- tion of plug-in electric vehicles in power systems with high wind power penetrations[J]. IEEE Transactions on Sustainable Energy, 4(3): 577-585.
[12] H Zhong, L Xie, Q Xia. Coupon incentive-based demand response: Theory and case study[J]. IEEE Transactions on Power System, 2013, 28(2): 1266-1276.
[13] 杨楠, 王波, 刘涤尘, 等. 考虑柔性负荷调峰的大规模风电随机优化调度方法[J]. 电工技术学报, 2013, 28(11): 231-238. Yang Nan, Wang Bo, Liu Dichen, et al. Large-scale wind power stochastic optimization scheduling method considering flexible load peaking[J]. Transactions of China Electrotechnical Society, 2013, 28(11): 231-238.
[14] 丰佳, 周芸菲. 浙江省典型用电行业负荷特性和可中断能力分析[J]. 电力需求侧管理, 2011, 13(4): 48-53. Feng Jia, Zhou Yunfei. The analysis of typical load characteristic and the ability of interruptible load of the electrical customer in Zhejiang province[J]. Power DSM, 2011, 13(4): 48-53.
[15] 郭金明, 李欣然, 邓威, 等. 基于2层规划的间歇性分布式电源及无功补偿综合优化配置[J]. 中国电机工程学报, 2013, 33(28): 25-33. Guo Jinming, Li Xinran, Deng Wei, et al. Com- prehensive optimal allocation of intermittent distri- buted generation and reactive power compensation based on bilevel planning[J]. Proceedings of the CSEE, 2013, 33(28): 25-33.
[16] 张璐, 唐巍, 丛鹏伟, 等. 基于机会约束规划和二层规划的配电网广义电源优化配置[J]. 电力系统自动化, 2014, 38(5): 50-58. Zhang Lu, Tang Wei, Cong Pengwei, et al. Optimal configuration of generalized power sources in distribu- tion network based on chance constrained programming and bi-level programming[J]. Automation of Electric Power Systems, 2014, 38(5): 50-58.
[17] 向月, 刘俊勇, 魏震波, 等. 考虑可再生能源出力不确定性的微电网能量优化鲁棒模型[J]. 中国电机工程学报, 2014, 34(19): 3063-3072. Xiang Yue, Liu Junyong, Wei Zhenbo, et al. Robust model of microgrid energy optimization with uncertain renewable energy sources[J]. Proceedings of the CSEE, 2014, 34(19): 3063-3072.
[18] 雷宇, 杨明, 韩学山. 基于场景分析的含风电系统机组组合的两阶段随机优化[J]. 电力系统保护与控制, 2012, 40(23): 58-67. Lei Yu, Yang Ming, Han Xueshan. A two-stage stochastic optimization of unit commitment conside- ring wind power based on scenario analysis[J]. Power System Protection and Control, 2012, 40(23): 58-67.
[19] 陈建华, 吴文传, 张伯明, 等. 风电受限态下的大电网有功实时控制模型与策略[J]. 中国电机工程学报, 2012, 32(28): 1-6. Chen Jianhua, Wu Wenchuan, Zhang Boming, et al. An active power real-time control method for large power grid under wind power curtailment[J]. Procee- dings of the CSEE, 2012, 32(28): 1-6.
[20] 王彩霞, 乔颖, 鲁宗相. 考虑风电效益的风火互济系统旋转备用确定方式[J]. 电力系统自动化, 2012, 36(4): 16-21. Wang Caixia, Qiao Ying, Lu Zongxiang. A method for determination of spinning reserve in wind-thermal power systems considering wind power benefits[J]. Automation of Electric Power Systems, 2012, 36(4): 16-21.
[21] 李海英, 李渝曾, 张少华. 可中断负荷参与输电阻塞管理的模型与算法[J]. 电力系统自动化, 2006, 30(10): 17-21. Li Haiying, Li Yuzeng, Zhang Shaohua. Model and algorithm of transmission congestion management based on interruptible load[J]. Automation of Electric Power Systems, 2006, 30(10): 17-21.
[22] 严干贵, 冯晓东, 李军徽, 等. 用于松弛调峰瓶颈的储能系统容量配置方法[J]. 中国电机工程学报, 2012, 32(28): 27-35. Yan Gangui, Feng Xiaodong, Li Junhui, et al. Opti- mization of energy storage system capacity for relaxing peak load regulation bottlenecks[J]. Proceedings of the CSEE, 2012, 32(28): 27-35.
[23] 毛伟明, 周明, 李庚银. 多时段下计及可中断负荷的电网输电阻塞管理[J]. 电网技术, 2008, 32(4): 72-77. Mao Weiming, Zhou Ming, Li Gengyin. Multi-period power transmission congestion management considering interruptible loads[J]. Power System Technology, 2008, 32(4): 72-77.
[24] 孙力勇, 张焰, 蒋传文. 基于矩阵实数编码遗传算
法求解大规模机组组合问题[J]. 中国电机工程学报, 2006, 26(2): 82-87.
25 Sun Liyong, Zhang Yan, Jiang Chuanwen. A solution to the unit commitment problem based on matrix real-coded genetic algorithm[J]. Proceedings of the CSEE, 2006, 26(2): 82-87.
[25] 所丽, 唐巍, 白牧, 等. 可考虑削峰填谷的配电网集中型充电站选址定容规划[J]. 中国电机工程学报, 2014, 34(7): 1052-1060. Suo Li, Tang Wei, Bai Muke, et al. Locating and sizing of centralized charging stations in distribution network considering load shifting[J]. Proceedings of the CSEE, 2014, 34(7): 1052-1060.
[26] 曾丹, 姚建国, 杨胜春, 等. 应对风电消纳中基于安全约束的价格型需求响应优化调度建模[J]. 中国电机工程学报, 2014, 11(34): 5571-5578. Zeng Dan, Yao Jianguo, Yang Shengchun, et al. Opti- mization dispatch modeling for price-based demand response considering security constraints to accom- modate the wind power[J]. Proceedings of the CSEE, 2014, 11(34): 5571-5578.
[27] 江岳文, 陈冲, 温步瀛. 含风电场的电力系统机组组合问题随机模拟粒子群算法[J]. 电工技术学报, 2009, 24(6): 129-137. Jiang Yuewen, Chen Chong, Wen Buying. Particle swarm research of stochastic simulation for unit com- mitment in wind farms integrated power system[J]. Transactions of China Electrotechnical Society, 2009, 24(6): 129-137.
[28] 王倩倩, 赵彩虹, 马成飞, 等. 基于二进制粒子群算法的可中断负荷优化调度[J]. 南京师范大学学报(工程技术版), 2011, 11(2): 19-25. Wang Qianqian, Zhao Caihong, Ma Chengfei, et al. Scheduling of interruptible load based on binary particle swarm optimization[J]. Journal of Nanjing Normal Universiy(Engineering and Technology Edition), 2011, 11(2): 19-25.