Fuzzy Random Day-Ahead Optimal Dispatch of DC Distribution Network Considering the Uncertainty of Source-Load
Jin Guobin1, Pan Di1, Chen Qing2,3, Shi Chao1, Li Guoqing1
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China; 2. State Grid Jiangsu Electric Power Co. Ltd Nanjing 210000 China; 3. Jiangsu Electric Power Company Research Institute Nanjing 211100 China
Abstract Aiming at the uncertainty of distributed renewable energy and typical DC load in DC distribution network, the uncertainty load model considering load self elasticity coefficient and demand response of electricity price is proposed. Considering the randomness of renewable energy, the highly schedulable units such as electric vehicle is converted into deterministic load by signing a day-ahead charging contract; A fuzzy random day-ahead optimal dispatching model is established, for achieving the objective of smoothest power of line between the distribution network and upper power grid, and the objective of minimum daily dispatching cost. The entropy weight method is used to determine the weights of the two objectives. Taking a DC distribution network as an example, the effectiveness and superiority of the optimal dispatching model are verified according to different scenarios, different photovoltaic output, different confidence levels and different signing rate of electric vehicle contracts.
Jin Guobin,Pan Di,Chen Qing等. Fuzzy Random Day-Ahead Optimal Dispatch of DC Distribution Network Considering the Uncertainty of Source-Load[J]. Transactions of China Electrotechnical Society, 2021, 36(21): 4517-4528.
[1] 宋强, 赵彪, 刘文华, 等. 智能直流配电网研究综述[J]. 中国电机工程学报, 2013, 33(25): 9-19, 5. Song Qiang, Zhao Biao, Liu Wenhua, et al.An overview of research on smart DC distribution power network[J]. Proceedings of the CSEE, 2013, 33(25): 9-19, 5. [2] 李霞林, 郭力, 王成山, 等. 直流微电网关键技术研究综述[J]. 中国电机工程学报, 2016, 36(1): 2-17. Li Xialin, Guo Li, Wang Chengshan, et al.Key technologies of DC microgrids: an overview[J]. Proceedings of the CSEE, 2016, 36(1): 2-17. [3] 曹文远, 韩民晓, 谢文强, 等. 交直流配电网逆变器并联控制技术研究现状分析[J]. 电工技术学报, 2019, 34(20): 4226-4241. Cao Wenyuan, Han Minxiao, Xie Wenqiang, et al.Analysis on research status of parallel inverters control technologies for AC-DC distribution network[J]. Transactions of China Electrotechnical Society, 2019, 34(20): 4226-4241. [4] 成龙, 金国彬, 王利猛, 等. 考虑功率裕度和电压偏差的多端直流配电网自组织下垂控制[J]. 电力系统自动化, 2019, 43(23): 81-93. Cheng Long, Jin Guobin, Wang Limeng, et al.Self-organizing droop control of multi-terminal DC distribution network considering power margin and voltage deviation[J]. Automation of Electric Power Systems, 2019, 43(23): 81-93. [5] 张勇军, 刘子文, 宋伟伟, 等. 直流配电系统的组网技术及其应用[J]. 电力系统自动化, 2019, 43(23): 39-51. Zhang Yongjun, Liu Ziwen, Song Weiwei, et al.Networking technology and its application of DC distribution system[J]. Automation of Electric Power Systems, 2019, 43(23): 39-51. [6] 李海波, 赵宇明, 刘国伟, 等. 基于时序仿真的商业楼宇交流与直流配电系统能效对比[J]. 电工技术学报, 2020, 35(19): 4194-4206. Li Haibo, Zhao Yuming, Liu Guowei, et al.The time sequential simulation based energy efficiency comparison of AC and DC distribution power system in commercial buildings[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4194-4206. [7] 郭国太. 电动汽车充电站负荷计算及影响因素[J]. 电气技术, 2019, 20(3): 93-97. Guo Guotai.Load calculation and influence factors of electric vehicle charging station[J]. Electrical Engineering, 2019, 20(3): 93-97. [8] 姜欣, 冯永涛, 熊虎, 等.基于出行概率矩阵的电动汽车充电站规划[J]. 电工技术学报, 2019, 34(增刊1): 272-281. Jiang Xin, Feng Yongtao, Xiong Hu, et al.Electric vehicle charging station planning based on travel probability matrix[J]. Transactions of China Electrotechnical Society, 2019, 34(S1): 272-281. [9] 孙鹏飞, 贺春光, 邵华, 等. 直流配电网研究现状与发展[J]. 电力自动化设备, 2016, 36(6): 64-73. Sun Pengfei, He Chunguang,Shao Hua, et al.Research status and development of DC distribution network[J]. Electric Power Automation Equipment, 2016, 36(6): 64-73. [10] 周逢权, 黄伟. 直流配电网系统关键技术探讨[J]. 电力系统保护与控制, 2014, 42(22): 62-67. Zhou Fengquan, Huang Wei.Study on the key technology of DC distribution power network[J]. Power System Protection and Control, 2014, 42(22): 62-67. [11] 马骏超, 江全元, 余鹏, 等. 直流配电网能量优化控制技术综述[J]. 电力系统自动化, 2013, 37(24): 89-96. Ma Junchao, Jiang Quanyuan, Yu Peng, et al.Survey on energy optimized control technology in DC distribution network[J]. Automation of Electric Power Systems, 2013, 37(24): 89-96. [12] 张永斌, 聂明林, 张俊鹏, 等. 考虑分布式电源不确定性的配电网网架模糊规划[J]. 电工技术学报, 2019, 34(增刊1): 258-263. Zhang Yongbin, Nie Minglin, Zhang Junpeng, et al.Grid fuzzy planning of the distribution network with distributed generation[J]. Transactions of China Electrotechnical Society, 2019, 34(S1): 258-263. [13] 夏鹏, 刘文颖, 张尧翔, 等. 考虑风电高阶不确定性的分布式鲁棒优化调度模型[J]. 电工技术学报, 2020, 35(1): 189-200. Xia Peng, Liu Wenying, Zhang Yaoxiang, et al.A distributionally robust optimization scheduling model cosidering higher-order uncertainty of wind power[J]. Transactions of China Electrotechnical Society, 2020, 35(1): 189-200. [14] 王家怡, 高红均, 刘友波, 等. 考虑风电不确定性的交直流混合配电网分布式优化运行[J]. 中国电机工程学报, 2020, 40(2): 550-563. Wang Jiayi, Gao Hongjun, Liu Youbo, et al.A distributed operation optimization model for AC/DC hybrid distribution network considering wind power uncertainty[J]. Proceedings of the CSEE, 2020, 40(2): 550-563. [15] 刘文颖, 徐鹏, 赵子兰, 等. 基于区间估计的风电出力多场景下静态电压安全域研究[J]. 电工技术学报, 2015, 30(3): 172-178. Liu Wenying, Xu Peng, Zhao Zilan, et al.A research of static voltage stability region in wind power scenario based on interval estimation[J]. Transactions of China Electrotechnical Society, 2015, 30(3): 172-178. [16] 王永杰, 吴文传, 张伯明. 考虑负荷量测和光伏不确定性的主动配电网鲁棒电压控制[J]. 电力系统自动化, 2015, 39(9): 138-144. Wang Yongjie, Wu Wenchuan, Zhang Boming.Robust voltage control model for active distribution network considering load and photovoltaic uncertainties[J]. Automation of Electric Power Systems, 2015, 39(9): 138-144. [17] 徐俊俊, 戴桂木, 吴在军, 等. 计及电动汽车和光伏不确定性的主动配电网量测优化配置[J]. 电力系统自动化, 2017, 41(1): 57-64. Xu Junjun, Dai Guimu, Wu Zaijun, et al.Optimal meter placement for active distribution network considering uncertainties of plug-in electric vehicles and photovoltaic systems[J]. Automation of Electric Power Systems, 2017, 41(1): 57-64. [18] 孙宇军, 李扬, 王蓓蓓, 等. 计及不确定性需求响应的日前调度计划模型[J]. 电网技术, 2014, 38(10): 2708-2714. Sun Yujun, Li Yang, Wang Beibei, et al.A day-ahead scheduling model considering demand response and its uncertainty[J]. Power System Technology, 2014, 38(10): 2708-2714. [19] 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. [20] 孙宇军, 王岩, 王蓓蓓, 等. 考虑需求响应不确定性的多时间尺度源荷互动决策方法[J]. 电力系统自动化, 2018, 42(2): 106-113, 159. Sun Yujun, Wang Yan, Wang Beibei, et al.Multi time scale decision method for source load interaction considering demand response uncertainty[J]. Automation of Electric Power Systems, 2018, 42(2): 106-113, 159. [21] 罗纯坚, 李姚旺, 许汉平, 等. 需求响应不确定性对日前优化调度的影响分析[J]. 电力系统自动化, 2017, 41(5): 22-29. Luo Chunjian, Li Yaowang, Xu Hanping, et al.Influence of demand response uncertainty on day-ahead optimization dispatching[J]. Automation of Electric Power Systems, 2017, 41(5): 22-29. [22] 李姚旺, 苗世洪, 刘君瑶, 等. 考虑需求响应不确定性的光伏微电网储能系统优化配置[J]. 电力系统保护与控制, 2018, 46(20): 69-77. Li Yaowang, Miao Shihong, Liu Junyao, et al.Optimal allocation of energy storage system in PV micro grid considering uncertainty of demand response[J]. Power System Protection and Control, 2018, 46(20): 69-77. [23] 王锡凡, 邵成成, 王秀丽, 等. 电动汽车充电负荷与调度控制策略综述[J]. 中国电机工程学报, 2013, 33(1): 1-10. Wang Xifan, Shao Chengcheng, Wang Xiuli, et al.Survey of electric vehicle charging load and dispatch control strategies[J]. Proceedings of the CSEE, 2013, 33(1): 1-10. [24] 钱甜甜, 李亚平, 郭晓蕊, 等. 基于时空活动模型的电动汽车充电功率计算和需求响应潜力评估[J]. 电力系统保护与控制, 2018, 46(23): 127-134. Qian Tiantian, Li Yaping, Guo Xiaorui, et al.Calculation of electric vehicle charging power and evaluation of demand response potential based on spatial and temporal activity model[J]. Power System Protection and Control, 2018, 46(23): 127-134. [25] 魏大钧, 张承慧, 孙波, 等. 基于分时电价的电动汽车充放电多目标优化调度[J]. 电网技术, 2014, 38(11): 35-40. Wei Dajun, Zhang Chenghui, Sun Bo, et al.A time-of-use price based multi-objective optimal dispatching for charging and discharging of electric vehicles[J]. Power System Technology, 2014, 38(11): 35-40. [26] 杨晓东, 张有兵, 赵波, 等. 供需两侧协同优化的电动汽车充放电自动需求响应方法[J]. 中国电机工程学报, 2017, 37(1): 120-130. Yang Xiaodong, Zhang Youbing, Zhao Bo, et al.Automated demand response method for electric vehicles charging and dischagring to achieve supply-demand coordinated optimization[J]. Proceedings of the CSEE, 2017, 37(1): 120-130. [27] 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. [28] 董雷, 陈卉, 蒲天骄, 等. 基于模型预测控制的主动配电网多时间尺度动态优化调度[J]. 中国电机工程学报, 2016, 36(17): 110-118. Dond Lei, Chen Hui, Pu Tianjiao, et al.Multi-time scale dynamic optimal dispatch in active distribution network based on model predictive control[J]. Proceedings of the CSEE, 2016, 36(17): 110-118. [29] 信桂新, 杨朝现, 杨庆媛, 等. 用熵权法和改进TOPSIS模型评价高标准基本农田建设后效应[J]. 农业工程学报, 2017, 33(1): 238-249. Xin Guixin, Yang Chaoxian, Yang Qingyuan, et al.Post-evaluation of well-facilitied capital farmland construction based on entropy weight method and improved TOPSIS model[J]. Transactions of the CSAE, 2017, 33(1): 238-249. [30] 王璟, 蒋小亮, 杨卓, 等. 光伏集中并网电压约束下的准入容量与电压波动的评估方法[J]. 电网技术, 2015, 39(9): 2450-2457. Wang Jing, Jiang Xiaoliang, Yang Zhuo, et al.Penetration capacity under voltage constraint and evaluation methodology of voltage fluctuation caused by centralized grid connection of photovoltaic power[J]. Power System Technology, 2015, 39(9): 2450-2457. [31] 张洪财, 胡泽春, 宋永华, 等. 考虑时空分布的电动汽车充电负荷预测方法[J]. 电力系统自动化, 2014, 38(1): 19-26. Zhang Hongcai, Hu Zechun, Song Yonghua, et al.A prediction method for electric vehicle charging load considering spatial and temporal distribution[J]. Automation of Electric Power Systems, 2014, 38(1): 19-26.
2021, Vol. 36 
