Fuzzy Optimal Dispatch of Wind Power Consumption Considering Demand Response

doi:10.3969/j.issn.1000－7229.2017.04.017

Abstract

Abstract: ABSTRACT： With the rapid development of smart grid, the demand response （DR） into the scheduling process to coordinate the output of wind power and thermal power units is a current research focus. Firstly, this paper utilizes DRs optimization function for the load curve and its equivalent function for the system reserve capacity to develop the time of use （TOU） pricing and the capacity cost model of interruptible load. Secondly, aiming at the uncertainties of wind power output, this paper adopts credibility measure theory to establish its fuzzy representation; then, introduces the wind power output uncertainty into the rotating reserve fuzzy constraint and presents the economic dispatch model based on fuzzy chance-constrained programming with considering DR. Finally, this paper solves the model by the improved gravity search algorithm. The example analysis results show the effectiveness of the proposed model in dealing with the uncertainty of wind power and reducing the running cost of the system.

Key words: KEYWORDS： , wind farm, demand response （DR）, fuzzy chance-constrained programming （FCCP）, economic dispatch, gravity search algorithm

CLC Number:

TM 73
TM 614

YI Chen，REN Jianwen，QI Jianwen. Fuzzy Optimal Dispatch of Wind Power Consumption Considering Demand Response

[J]. Electric Power Construction, 2017, 38(4): 127-.

References

［1］刘吉臻，王海东，李明扬.含风电的电力系统机组组合问题研究综述［J］.电力建设，2014，35（12）：38-45.

LIU Jizhen， WANG Haidong， LI Mingyang.Review on unit commitment of power systems with wind power integration［J］.Electric Power Construction，2014，35（12）：38-45.

［2］陈国恩，宗鹏鹏，朱伟，等.计及可再生能源与负荷互补特性的储能随机调度［J］.电力建设，2015，36（6）：27-33.

CHEN Guoen，ZONG Pengpeng，ZHU Wei，et al.Stochastic dispatching of energy storage devices considering complementarity between renewable energy and load［J］.Electric Power Construction，2015，36（6）：27-33.

［3］GUNJI T，SUGAYA Y，OMACHI S.A practical method for realizing large-scale and flexible demand response［C］//2013 IEEE PES Innovative Smart Grid Technologies （ISGT）.Washington：IEEE，2013：1-6.

［4］刘旭，杨德友，孟涛，等.计及需求响应的含风电场日前两阶段动态环境经济调度［J］.电力建设，2016，37（9）：146-154.

LIU Xu，YANG Deyou，MENG Tao，et al.Day-ahead two-stage dynamic economic emission dispatching in wind power integrated system incorporating demand response［J］.Electric Power Construction，2016，37（9）：146-154.

［5］鞠立伟，秦超，吴鸿亮，等.计及多类型需求响应的风电消纳随机优化调度模型［J］.电网技术，2015，39（7）：1839-1846.

JU Liwei，QIN Chao，WU Hongliang，et al.Wind power accommodation stochastic optimization model with multi-type demand response［J］.Power System Technology，2015，39（7）：1839-1846.

［6］崔强，王秀丽，曾平良，等.调峰约束下考虑风电消纳的多目标尖峰电价决策模型［J］.中国电机工程学报，2015，35（11）：2662-2669.

CUI Qiang，WANG Xiuli，ZENG Pingliang，et al.Multi-objective decision model of critical peak pricing considering capability of wind power accommodation subject to peak regulation［J］.Proceedings of the CSEE，2015，35（11）：2662-2669.

［7］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.

［8］杨楠，刘涤尘，董开松，等.考虑柔性负荷补偿/激励机制的风电供需侧一体化随机调度方法［J］.电力自动化设备，2015，35（2）：15-20，27.

YANG Nan，LIU Dichen，DONG Kaisong，et al.Integrated random scheduling for supply and demand sides of wind power system considering flexible load compensation/incentives［J］.Electric Power Automation Equipment，2015，35（2）：15-20，27.

［9］刘文颖，文晶，谢昶，等.考虑风电消纳的电力系统源荷协调多目标优化方法［J］.中国电机工程学报，2015，35（5）：1079-1088.

LIU Wenying，WEN Jing，XIE Chang，et al.Multi-objective optimal method considering wind power accommodation based on source-load coordination［J］.Proceedings of the CSEE，2015，35（5）：1079-1088.

［10］鞠立伟，于超，谭忠富.计及需求响应的风电储能两阶段调度优化模型及求解算法［J］.电网技术，2015，39（5）：1287-1293.

JU Liwei，YU Chao，TAN Zhongfu.A two-stage scheduling optimization model and corresponding solving algorithm for power grid containing wind farm and energy storage system considering demand response［J］.Power System Technology，2015，39（5）：1287-1293.

［11］CHENG Y，ZHAI N.Evaluation of TOU price based on responses of customer［C］//2010 IEEE International Conference on Industrial Engineering and Engineering Management （IEEM）.Xiamen, China：IEEE，2010：1977-1981.

［12］胡福年，汤玉东，邹云.需求侧实行峰谷分时电价策略的影响分析［J］.电工技术学报，2007，22（4）：168-174.

HU Funian，TANG Yudong，ZOU Yun.Analysis of impacts of TOU price strategy［J］.Transactions of China Electrotechnical Society，2007，22（4）：168-174.

［13］刘宝碇，赵瑞清，王纲.不确定规划及应用［M］.北京：清华大学出版社，2003：138-145.

LIU Baoding, ZHAO Ruiqing, WANG Gang. Uncertainity programming with application［M］. Beijing: Tsinghua University Press, 2003:138-145.

［14］南晓强，李群湛，赵元哲，等.计及风电预测可信度的经济调度及辅助决策方法［J］.电力系统自动化，2013，37（19）：61-67.

NAN Xiaoqiang，LI Qunzhan，ZHAO Yuanzhe，et al.An economic dispatch and decision making method based on credibility of wind power forecasting［J］.Automation of Electric Power Systems，2013，37（19）：61-67.

［15］艾欣，刘晓.基于可信性理论的含风电场电力系统动态经济调度［J］.中国电机工程学报，2011，31（增刊）：12-18.

AI Xin，LIU Xiao.Dynamic economic dispatch for wind farms integrated power system based on credibility theory［J］.Proceedings of the CSEE，2011，31（Supplement）：12-18.

［16］赵波，曹一家.电力系统机组组合问题的改进粒子群优化算法［J］.电网技术，2004，28（21）：6-10.

ZHAO Bo，CAO Yijia.An improved particle swarm optimization algorithm for power system unit commitment［J］.Power System Technology，2004，28（21）：6-10.

［17］ RASHEDI E, NEZAMABADI-POUR H, SARYYAZDI S. GSA: a gravitational search algorithm［J］. Information Sciences, 2009, 179（13）: 2232-2248.

［18］盛四清，孙晓霞.利用风蓄联合削峰的电力系统经济调度［J］.电网技术，2014，38（9）：2484-2489.

SHENG Siqing，SUN Xiaoxia.An economic dispatching strategy of peak load shifting by wind farm and pumped storage plant［J］.Power System Technology，2014，38（9）：2484-2489.

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