考虑风电和负荷不确定冷热电联供微网日前经济调度

doi:10.11930/j.issn.1004-9649.201907123

中国电力 ›› 2020, Vol. 53 ›› Issue (8): 50-59.DOI: 10.11930/j.issn.1004-9649.201907123

• 综合能源配用电关键技术专栏 • 上一篇下一篇

考虑风电和负荷不确定冷热电联供微网日前经济调度

王长浩, 刘洋, 许立雄

四川大学电气工程学院，四川成都 610065

收稿日期:2019-07-15 修回日期:2019-10-21 发布日期:2020-08-05
作者简介:王长浩(1993-),男,硕士研究生,从事能源互联网经济运行研究,E-mail:1627783530@qq.com;刘洋(1982-),男,博士,副教授,从事能源互联网经济运行、电力数据精细化分析、新能源及储能优化配置研究,E-mail:yang.liu@scu.edu.cn;许立雄(1982-),男,通信作者,博士,讲师,从事电力系统稳定与控制研究,E-mail:xulixiong@scu.edu.cn
基金资助:
四川省科技厅重点研发计划资助项目(2019YFG0152)

Day-Ahead Economic Dispatch for a Combined Cooling, Heat and Power Microgrid System Considering Wind Power and Load Uncertainty

WANG Changhao, LIU Yang, XU Lixiong

College of Electrical Engineering, Sichuan University, Chengdu 610065, China

Received:2019-07-15 Revised:2019-10-21 Published:2020-08-05
Supported by:
This work is supported by Key Research and Development Projects of SCST (No.2019YFG0152)

摘要/Abstract

摘要： 以含多种分布式电源的冷热电联供（combined cooling heating and power, CCHP）微网为研究对象，考虑风电出力和冷热电负荷不确定对微网运行的影响，区分源荷不确定各自的特点，建立考虑风电和负荷不确定的CCHP微网两阶段鲁棒随机调度模型。虽然风电预测精度较低，但其波动范围易于测量，可以使用鲁棒优化方法处理风电不确定；负荷预测精度较高且有较强波动规律，使用随机优化方法处理负荷不确定。首先通过随机抽样形成多个负荷场景并削减，得到多个典型冷热电负荷场景；然后以最小化各场景的调度成本加权平均值为决策目标制定日前调度方案，该方案使用两阶段鲁棒优化方法求解。考虑实际生产中可能出现的弃风现象，为增加风电消纳引入弃风惩罚成本。算例仿真结果证明了所提调度方法的合理性与经济性。

关键词: 冷热电联供, 风电消纳, 源荷不确定, 经济调度

Abstract: Considering the influence of uncertainties of wind power outputs and load on the operation of microgrid, a two-stage robust stochastic scheduling model is established for CCHP microgrid with multi-type distributed generations after distinguishing the characteristics of uncertain sources and loads. Although the current accuracy of wind power prediction is low, its fluctuation range is easy to measure, so a robust optimization method is applied; the load forecasting accuracy is high and has certain regularity, and then a stochastic optimization method is applied. Firstly, multiple load scenarios are formed by random sampling, then several typical load scenarios are obtained by reducing them. Next a day-ahead scheduling scheme is formulated with the goal of minimizing the weighted average of the scheduling cost of each scenario, in which a two-stage robust optimization method is used to solve the scheme. Considering the phenomenon of wind abandonment in actual production, penalty cost is introduced to increase wind power absorption. Simulation results show the rationality and economy of the proposed scheduling method.

Key words: CCHP, wind power accommodation, uncertain sources and loads, economic dispatch

王长浩, 刘洋, 许立雄. 考虑风电和负荷不确定冷热电联供微网日前经济调度[J]. 中国电力, 2020, 53(8): 50-59.

WANG Changhao, LIU Yang, XU Lixiong. Day-Ahead Economic Dispatch for a Combined Cooling, Heat and Power Microgrid System Considering Wind Power and Load Uncertainty[J]. Electric Power, 2020, 53(8): 50-59.

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参考文献

[1] 姚良忠, 朱凌志, 周明, 等. 高比例可再生能源电力系统的协同优化运行技术展望[J]. 电力系统自动化, 2017, 41(9): 36-43
YAO Liangzhong, ZHU Lingzhi, ZHOU Ming, et al. Prospects of coordination and optimization for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9): 36-43
[2] 王成山, 洪博文, 郭力, 等. 冷热电联供微网优化调度通用建模方法[J]. 中国电机工程学报, 2013, 33(31): 26-33
WANG Chengshan, HONG Bowen, GUO Li, et al. A general modeling method for optimal dispatch of combined cooling, heating and power microgrid[J]. Proceedings of the CSEE, 2013, 33(31): 26-33
[3] 吴奎华, 杨中源, 梁荣, 等. 具有两种制冷方式的CCHP系统优化运行策略及其判别条件[J]. 电力系统自动化, 2018, 42(6): 18-24, 80
WU Kuihua, YANG Zhongyuan, LIANG Rong, et al. Optimal operation strategy and their discriminating conditions for CCHP systems with two cooling ways[J]. Automation of Electric Power Systems, 2018, 42(6): 18-24, 80
[4] 杨志鹏, 张峰, 梁军, 等. 含热泵和储能的冷热电联供型微网经济运行[J]. 电网技术, 2018, 42(6): 1735-1742
YANG Zhipeng, ZHANG Feng, LIANG Jun, et al. Economic generation scheduling of CCHP microgrid with heat pump and energy storage[J]. Power System Technology, 2018, 42(6): 1735-1742
[5] 吴鸣, 骆钊, 季宇, 等. 基于模型预测控制的冷热电联供型微网动态优化调度[J]. 中国电机工程学报, 2017, 37(24): 7174-7184
WU Ming, LUO Zhao, JI Yu, et al. Optimal dynamic dispatch for combined cooling, heating and power microgrid based on model predictive control[J]. Proceedings of the CSEE, 2017, 37(24): 7174-7184
[6] 蔡超, 窦晓波, 曹水晶, 等. 基于模型预测控制的园区热电联供微电网能量优化[J]. 电力建设, 2019, 40(3): 27-33
CAI Chao, DOU Xiaobo, CAO Shuijing, et al. Energy optimization based on model predictive control for combined heating and power microgrid in industrial park[J]. Electric Power Construction, 2019, 40(3): 27-33
[7] 王思明, 牛玉刚, 方磊, 等. 考虑新能源出力不确定性的微网社区双阶段调度策略[J]. 电力系统保护与控制, 2018, 46(17): 89-98
WANG Siming, NIU Yugang, FANG Lei, et al. Dual stage scheduling strategy for microgrid community considering uncertainty of renewable energy[J]. Power System Protection and Control, 2018, 46(17): 89-98
[8] 税月, 刘俊勇, 高红均, 等. 考虑风电不确定性的电热综合系统分布鲁棒协调优化调度模型[J]. 中国电机工程学报, 2018, 38(24): 7235-724,7450
SHUI Yue, LIU Junyong, GAO Hongjun, et al. A distributionally robust coordinated dispatch model for integrated electricity and heating systems considering uncertainty of wind power[J]. Proceedings of the CSEE, 2018, 38(24): 7235-724,7450
[9] 别朝红, 李更丰, 谢海鹏. 计及负荷与储能装置协调优化的微网可靠性评估[J]. 电工技术学报, 2014, 29(2): 64-73
BIE Chaohong, LI Gengfeng, XIE Haipeng. Reliability evaluation of microgrid considering coordinative optimization of loads and storage device[J]. Transactions of China Electrotechnical Society, 2014, 29(2): 64-73
[10] 李怡瑾, 唐昊, 吕凯, 等. 源荷不确定冷热电联供微网能量调度的建模与学习优化[J]. 控制理论与应用, 2018, 35(1): 56-64
LI Yijin, TANG Hao, LV Kai, et al. Modeling and learning-based optimization of the energy dispatch for a combined cooling, heat and power microgrid system with uncertain sources and loads[J]. Control Theory & Applications, 2018, 35(1): 56-64
[11] 王皓, 艾芊, 甘霖, 等. 基于多场景随机规划和MPC的冷热电联合系统协同优化[J]. 电力系统自动化, 2018, 42(13): 51-58
WANG Hao, AI Qian, GAN Lin, et al. Collaborative optimization of combined cooling heating and power system based on multi-scenario stochastic programming and model predictive control[J]. Automation of Electric Power Systems, 2018, 42(13): 51-58
[12] 刘一欣, 郭力, 王成山. 微电网两阶段鲁棒优化经济调度方法[J]. 中国电机工程学报, 2018, 38(14): 4013-4022
LIU Yixin, GUO Li, WANG Chengshan. Economic dispatch of microgrid based on two stage robust optimization[J]. Proceedings of the CSEE, 2018, 38(14): 4013-4022
[13] ZHANG C, XU Y, DONG Z Y, et al. Robust coordination of distributed generation and price-based demand response in microgrids[J]. IEEE Transactions on Smart Grid, 2018, 9(5): 4236-4247.
[14] 吴雄, 王秀丽, 王建学, 等. 微网经济调度问题的混合整数规划方法[J]. 中国电机工程学报, 2013, 33(28): 1-8
WU Xiong, WANG Xiuli, WANG Jianxue, et al. Economic generation scheduling of a microgrid using mixed integer programming[J]. Proceedings of the CSEE, 2013, 33(28): 1-8
[15] 张刚, 张峰, 张利, 等. 考虑碳排放交易的日前调度双阶段鲁棒优化模型[J]. 中国电机工程学报, 2018, 38(18): 5490-5499
ZHANG Gang, ZHANG Feng, ZHANG Li, et al. Two-stage robust optimization model of day-ahead scheduling considering carbon emissions trading[J]. Proceedings of the CSEE, 2018, 38(18): 5490-5499
[16] 徐秋实, 邓长虹, 赵维兴, 等. 含风电电力系统的多场景鲁棒调度方法[J]. 电网技术, 2014, 38(3): 653-661
XU Qiushi, DENG Changhong, ZHAO Weixing, et al. A multi-scenario robust dispatch method for power grid integrated with wind farms[J]. Power System Technology, 2014, 38(3): 653-661
[17] 崔杨, 杨志文, 严干贵, 等. 降低火电机组调峰成本的光热电站储热容量配置方法[J]. 中国电机工程学报, 2018, 38(6): 1605-1611, 1896
CUI Yang, YANG Zhiwen, YAN Gangui, et al. Capacity configuration of thermal energy storage within CSP to reduce the cost of peak load regulation[J]. Proceedings of the CSEE, 2018, 38(6): 1605-1611, 1896
[18] LIU G, XU Y, TOMSOVIC K. Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization[J]. IEEE Transaction on Smart Grid, 2016, 7(1): 227-237.
[19] 刘怀东, 冯志强, 王锦桥, 等. 计及条件风险价值的综合能源系统经济调度[J]. 电网技术, 2018, 42(5): 1385-1392
LIU Huaidong, FENG Zhiqiang, WANG Jinqiao, et al. Economic dispatch of integrated energy systems considering conditional value-at-risk[J]. Power System Technology, 2018, 42(5): 1385-1392

考虑风电和负荷不确定冷热电联供微网日前经济调度

Day-Ahead Economic Dispatch for a Combined Cooling, Heat and Power Microgrid System Considering Wind Power and Load Uncertainty

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考虑风电和负荷不确定冷热电联供微网日前经济调度

Day-Ahead Economic Dispatch for a Combined Cooling, Heat and Power Microgrid System Considering Wind Power and Load Uncertainty

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