基于风电离散化概率序列的机会约束规划优化调度方法

doi:10.19595/j.cnki.1000-6753.tces.171617

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摘要风电出力的不确定性加重了系统备用负担,影响了风电消纳。此外,传统计及风电不确定性的优化调度方法由于求解复杂、计算时间长,存在结果最优性与方法实用性之间的矛盾。针对以上问题,提出了一种基于风电离散化概率序列的机会约束规划优化调度方法。该方法利用一组Beta分布概率密度函数族描述风电不确定性,并结合概率序列运算理论将其简化为离散化概率序列,降低了风电概率分布模型的复杂程度;在此基础上,结合机会约束规划理论,建立了基于风电离散化概率序列的机会约束规划调度模型,并进行求解,进一步简化计算,降低求解时间,为考虑风电不确定性的优化调度问题提供了一种简单有效的解决思路。最后,以某地区电网为例,验证了所提方法的可行性和有效性。

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关键词 ：风电不确定性, 机会约束规划, 优化调度, 概率分布, 离散化概率序列

Abstract：Wind power uncertainty raises the reserve requirement of power system and holds back the consumpation of wind power. However, traditional optimal scheduling method considering wind power uncertainty, has a problem of contradiction between result optimality and method practicability, due to its complex solution and long computing time. Therefore, an optimal scheduling method of chance constrained programming based on discrete wind power probability sequences was presented. A family of Beta distribution probability density functions were used to describe wind power uncertainty, and then were simplified to discrete probability sequences based on the theory of probability sequence operation, and this reduced the complexity of wind power probability distribution. On that basis, an optimal scheduling model of chance constrained programming based on discrete wind power probability sequences was built and solved. That can further simplify calculation, and propose a effective solution to the traditional optimal scheduling problem considering wind power uncertainty. At last, the correctness and effectiveness of the method were verified by the simulation results based on a regional power grid.

Key words： Wind power uncertainty chance-constrained programming optimal scheduling probability distribution discrete probability sequence

收稿日期: 2017-11-29 出版日期: 2018-11-12

PACS:

TM732

基金资助:国家自然科学基金面上项目（51377053）、国家科技支撑计划项目（2015BAA01B04）、国家电网公司项目（522727160002）和国网甘肃省电力公司科技项目（SGGSKY00JNJS1700152）资助

作者简介: 夏鹏男,1992年生,博士研究生,研究方向为电力系统分析与控制、新能源电力系统特性与多能互补。E-mail：xiapeng23@163.com（通信作者）刘文颖女,1955年生,教授,博士生导师,研究方向为电力系统分析与控制、新能源电力系统特性与多能互补。E-mail: liuwenyingls@sina.com

引用本文:

夏鹏, 刘文颖, 蔡万通, 汪宁渤, 梁琛. 基于风电离散化概率序列的机会约束规划优化调度方法[J]. 电工技术学报, 2018, 33(21): 5069-5079. Xia Peng, Liu Wenying, Cai Wantong, Wang Ningbo, Liang Chen. Optimal Scheduling Method of Chance Constrained Programming Based on Discrete Wind Power Probability Sequences. Transactions of China Electrotechnical Society, 2018, 33(21): 5069-5079.

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[1] 鲁宗相, 李海波, 乔颖. 高比例可再生能源并网的电力系统灵活性评价与平衡机理[J]. 中国电机工程学报, 2017, 37(1): 9-20.
Lu Zongxiang, Li Haibo, Qiao Ying.Flexibility evaluation and supply/demand balance principle of power system with high-penetration renewable electricity[J].Proceedings of the CSEE, 2017, 37(1): 9-20.
[2] 胡源, 别朝红, 宁光涛, 等. 计及风电不确定性的多目标电网规划期望值模型与算法[J]. 电工技术学报, 2016, 31(10): 168-175.
Hu Yuan, Bie Zhaohong, Ning Guangtao, et al.The expected model and algorithm of multi-objective transmission network planning considering the uncertainty of wind power[J]. Transactions of China Electrotechnical Society, 2016, 31(10): 168-175.
[3] 薛禹胜, 雷兴, 薛峰, 等. 关于风电不确定性对电力系统影响的评述[J]. 中国电机工程学报, 2014, 34(29): 5029-5040.
Xue Yusheng, Lei Xing, Xue Feng, et al.A review on impacts of wind power uncertainties on power systems[J]. Proceedings of the CSEE, 2014, 34(29): 5029-5040.
[4] 文晶, 刘文颖, 谢昶, 等. 计及风电消纳效益的电力系统源荷协调二层优化模型[J]. 电工技术学报, 2015, 30(8): 247-256.
Wen Jing, Liu Wenying, Xie Chang, et al.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.
[5] 元博, 周明, 李庚银, 等. 基于可靠性指标的含风电电力系统的发电和运行备用的协调调度模型[J]. 电网技术, 2013, 37(3): 800-807.
Yuan Bo, Zhou Ming, Li Gengyin, et al.A coordinated dispatching model considering generation and operating reserve for wind power integrated power system based on elnsr[J]. Power System Technology, 2013, 37(3): 800-807.
[6] 殷超. 考虑风电不确定性的电网备用优化决策方法研究[J]. 电网与清洁能源, 2015, 31(4): 106-112.
Yin Chao.Study of optimized backup method for power grid considering the uncertainty of wind power[J]. Power System and Clean Energy, 2015, 31(4): 106-112.
[7] 赵冬梅, 殷加玞. 考虑源荷双侧不确定性的模糊随机机会约束优先目标规划调度模型[J]. 电工技术学报, 2018, 33(5): 1076-1085.
Zhao Dongmei, Yin Jiafu.Fuzzy random chance constrained preemptive goal programming scheduling model considering source-side and load-side uncertainty[J]. Transactions of China Electrotechnical Society, 2018, 33(5): 1076-1085.
[8] 段翩, 朱建全, 刘明波. 基于双层模糊机会约束规划的虚拟电厂优化调度[J]. 电工技术学报, 2016, 31(9): 58-67.
Duan Pian, Zhu Jianquan, Liu Mingbo.Optimal dispatch of virtual power plant based on bi-level fuzzy chance constrained programming[J]. Transactions of China Electrotechnical Society, 2016, 31(9): 58-67.
[9] 王鲁浩, 李歧强, 丁然, 等. 可再生能源微网鲁棒多目标优化调度[J]. 电工技术学报, 2017, 32(5): 184-192.
Wang Luhao, Li Qiqiang, Ding Ran, et al.Robust multi-objective optimization scheduling of micro-grids with renewable energy[J]. Transactions of China Electrotechnical Society, 2017, 32(5): 184-192.
[10] 于丹文, 杨明, 韩学山, 等. 计及风电概率分布特征的鲁棒实时调度方法[J]. 中国电机工程学报, 2017, 37(3): 727-738.
Yu Danwen, Yang Ming, Han Xueshan, et al.Robust real-time dispatch considering probabilistic distribution of wind generation[J]. Proceedings of the CSEE, 2017, 37(3): 727-738.
[11] Zhao Chaoyue, Guan Yongpei.Unified stochastic and robust unit commitment[J]. IEEE Transactions on Power Systems, 2013, 28(3): 3353-3361.
[12] 黄映, 周科峰, 叶婷. 基于机会约束规划法和非支配排序差分进化算法的含风电多目标输电网规划[J]. 电气应用, 2016, 35(6): 42-46.
Huang Ying, Zhou Kefeng, Ye Ting.Wind power multi-objective transmission network planning based on opportunistic constrained programming and non-dominated sorting differential evolution algorithm[J]. Electrotechnical Application, 2016, 35(6): 42-46.
[13] 孙欣, 方陈, 沈风, 等. 考虑风电出力不确定性的发用电机组组合方法[J]. 电工技术学报, 2017, 32(4): 204-211.
Sun Xin, Fang Chen, Shen Feng, et al.Optimal dispatch of virtual power plant based on bi-level fuzzy chance constrained programming[J]. Transactions of China Electrotechnical Society, 2017, 32(4): 204-211.
[14] 夏澍, 顾劲岳, 葛晓琳, 等. 风光联合优化配置的多目标机会约束规划方法[J]. 电力系统保护与控制, 2016, 44(6): 35-40.
Xia Shu, Gu Jinyue, Ge Xiaolin, et al.Multiobjective chance-constrained programming method for wind generations and photovoltaic allocating[J]. Power System Protection and Control, 2016, 44(6): 35-40.
[15] 郭小璇, 龚仁喜, 鲍海波, 等. 含新能源电力系统机会约束经济调度的二阶锥规划方法[J]. 电力系统保护与控制, 2015, 43(22): 85-91.
Guo Xiaoxuan, Gong Renxi, Bao Haibo, et al.Second-order cone programming method of chance constrained economic dispatch considering renewable energy sources[J]. Power System Protection and Control, 2015, 43(22): 85-91.
[16] 范松丽, 艾芊, 贺兴. 基于机会约束规划的虚拟电厂调度风险分析[J]. 电机工程学报, 2015, 35(16): 4025-4034.
Fan Songli, Ai Qian, He Xing.Risk Analysis on dispatch of virtual power plant based on chance constrained programming[J]. Proceedings of the CSEE, 2015, 35(16): 4025-4034.
[17] 艾欣, 周树鹏, 陈政琦, 等. 多随机因素下含可中断负荷的电力系统优化调度模型与求解方法研究[J]. 中国电机工程学报, 2017, 37(8): 2231-2242.
Ai Xin, Zhou Shupeng, Chen Zhengqi, et al.Research on optimal scheduling model and solving method for power system with interruptible load considering multi stochastic factors[J]. Proceedings of the CSEE, 2017, 37(8): 2231-2242.
[18] Bofinger S, Luig A, Beyer H G.Qualification of wind power forecasts[C]//Global Wind Power Conference, Paris, France, 2002: 2-5.
[19] Fabbri A, Roman T G S, Abbad J R, et al. Assessment of the cost associated with wind generation prediction errors in a liberalized electricity market[J]. IEEE Transactions on Power Systems, 2005, 20(3): 1440-1446.
[20] 杨宏, 苑津莎, 张铁峰. 一种基于Beta分布的风电功率预测误差最小概率区间的模型和算法[J]. 中国电机工程学报, 2015, 35(9): 2135-2142.
Yang Hong, Yuan Jinsha, Zhang Tiefeng.A model and algorithm for minimum probability interval of wind power forecast errors based on beta distribution[J]. Proceedings of the CSEE, 2015, 35(9): 2135-2142.
[21] 康重庆, 白利超, 夏清, 等. 概率性序列及其运算理论[J]. 清华大学学报(自然科学版), 2003, 43(3): 322-325.
Kang Chongqing, Bai Lichao, Xia Qing, et al.Probabilistic sequences and operation theory[J]. Journal of Tsinghua University (Science and Technology), 2003, 43(3): 322-325.
[22] 杨家然, 王兴成, 蒋程, 等. 计及风力发电风险的电力系统多目标动态优化调度[J]. 电力系统保护与控制, 2016, 44(7): 25-31.
Yang Jiaran, Wang Xingcheng, Jiang Cheng, et al.Multi-objective dynamic optimal scheduling of power system considering wind power risk[J]. Power System Protection and Control, 2016, 44(7): 25-31.
[23] 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.