联盟理论下风-火-电动汽车协同调度消纳风电的优化算法及利润分配

doi:10.3969/j.issn.1000-7229.2018.08.004

摘要/Abstract

摘要： 为促进电力系统多方主体的协同合作，系统成员间利润分配机制的合理制定至关重要。针对风电出力的随机性、波动性与反调峰性，本文首先将风、火发电机组打捆组成稳定的电力外送体系，并将其作为优先联盟与电动汽车（electric vehicle, EV）组成大联盟；其次，以利润最大为目标构建了大联盟及非联盟模式下的优化调度模型，并以不同调度模式下的利润结果为依据，利用Banzhaf-Owen值对大联盟及优先联盟内部成员间的利润进行分配；最后，通过核心理论判别该分配策略下风电商、火电商、电动汽车用户三者合作的可能性。算例仿真结果表明了大联盟内部成员联合调度可促进风电的消纳与发展，且采用Banzhaf-Owen值分配策略后，合作可以成立，大联盟及优先联盟内部成员均有可观收益。

关键词: 电动汽车（EV）, 风电消纳, 优先联盟, 利润分配, 核心理论

Abstract:

In order to promote the collaborative cooperation of multi-party entities in the power system, the rational establishment of the profit distribution mechanism among system members is of utmost importance. In view of the randomness, volatility and anti-peaking of wind power output, this paper first bundles wind and thermal power to form a stable power transmission system, and forms a major coalition of priority alliances with electric vehicles （EV）. Secondly, with the aim of maximizing profits, an optimal dispatch model under the major alliances and non-alliance models is constructed. On the basis of the profit results under different dispatch models, the Banzhaf-Owen value are used to make profits allocation among major coalitions and internal members of priority coalitions. Finally, the core theory is used to determine the possibility of cooperation among wind power providers, thermal power providers, and electric vehicle users under this allocation strategy. The example simulation results show that the joint scheduling of internal members of the Grand Alliance can promote the consumption and development of wind power. After the Banzhaf-Owen value allocation strategy is adopted, cooperation can be established, and major alliances and internal members of the priority alliance have considerable returns.

Key words: electric vehicle （EV）, wind power consumption, priority alliance, profit distribution, core theory

中图分类号:

TM 73

孙波，王璐，李思敏，李志恒. 联盟理论下风-火-电动汽车协同调度消纳风电的优化算法及利润分配[J]. 电力建设, 2018, 39(8): 24-31.

SUN Bo, WANG Lu, LI Simin, LI Zhiheng. Optimization Algorithm and Profit Distribution of Wind-Thermal-EV Cooperative Dispatch for Wind Power Consumption Under the Alliance Theory[J]. Electric Power Construction, 2018, 39(8): 24-31.

参考文献

［1］许沛东, 方华亮, 黄烁. 考虑风电消纳及潮流均衡度的分散式风电选址定容［J］. 电力建设, 2018, 39（1）: 99-105.

XU Peidong, FANG Hualiang, HUANG Shuo. Decentralized wind farm site selection considering wind power consumption and balance ［J］. Electric Power Construction, 2018, 39（1）: 99-105.

［2］国家能源局. 2017年风电并网运行情况［EB/OL］. （2018-02-01）［2018-03-31］. http://www.nea.gov.cn/2018-02/01/c_136942234.htm

［3］郭壮志, 洪俊杰, 孟安波. 基于多维度动态协调的大规模并网风电储能容量多指标优化配置策略［J］. 电力自动化设备, 2016, 36（2）: 161-168.

GUO Zhuangzhi, HONG Junjie, MENG Anbo. Multi-dimension optimal allocation strategy for large-scale grid-connected wind power storage capacity based on multi-dimensional dynamic coordination ［J］. Electric Power Automation Equipment, 2016,36（2）: 161-168.

［4］林建熙, 史俊祎, 文福拴,等. 计及可控负荷的工业微网源荷协同优化调度［J］. 电力建设, 2018, 39（1）: 1-9.

LIN Jianxi, SHI Junyi, WEN Fushuan, et al. A coordinated optimal scheduling of source and load of industrial microgrid considering controllable load ［J］. Electric Power Construction, 2018, 39（1）: 1-9.

［5］刘祚宇, 齐峰, 文福拴,等. 含电动汽车虚拟电厂参与碳交易时的经济与环境调度［J］. 电力建设, 2017, 38（9）: 45-52.

LIU Zuoyu, QI Feng, WEN Fushuan, et al. Economic and environmental dispatching in electric vehicles embedded virtual power plants with participation in carbon trading ［J］. Electric Power Construction, 2017, 38（9）: 45-52.

［6］王诚良,刘洪，宫建锋,等. 面向风电消纳的综合能源系统多类型储能联合调度［J］. 电力建设, 2018, 39（4）: 35-44.

WANG Chengliang, LIU Hong, GONG Jianfeng, et al. Integrated scheduling of multi-type energy storage for integrated energy systems oriented to wind power consumption ［J］. Electric Power Construction, 2018, 39（4）: 35-44.

［7］唐晓瑭, 倪桦, 王永生. 电动汽车供电能源优化组合及智能充电策略［J］. 电力建设, 2013, 34（12）: 111-115.

TANG Xiaotang, NI Hua, WANG Yongsheng. Energy supply optimization and intelligent charging strategy of electric vehicles［J］. Electric Power Construction, 2013, 34（12）: 111-115.

［8］伍栋文, 于艾清. 大规模多源联合外送协调调度中基于核仁理论的利润分配［J］. 电网技术, 2016, 40（10）: 2975-2981.

WU Dongwen, YU Aiqing. Research on nucleolus theory based profit distribution for joint delivery system of large-scale hybrid power generation ［J］.Power System Technology, 2016, 40 （10）: 2975-2981.

［9］谭忠富, 宋艺航, 张会娟,等. 大规模风电与火电联合外送体系及其利润分配模型［J］. 电力系统自动化, 2013, 37（23）: 63-70.

TAN Zhongfu, SONG Yihang, ZHANG Huijuan, et al. Joint delivery system of large-scale wind power and thermal power generation and its profit distribution model ［J］.Automation of Electric Power Systems, 2013, 37（23）: 63-70.

［10］刘文霞, 凌云頔, 赵天阳. 低碳经济下基于合作博弈的风电容量规划方法［J］. 电力系统自动化, 2015, 39（19）: 68-74.

LIU Wenxia, LING Yuncheng, ZHAO Tianyang. Cooperative game based capacity planning model for wind power in low carbon economy ［J］.Automation of Electric Power Systems, 2015, 39（19）: 68-74.

［11］张晨, 陈坤, 谭忠富,等. 利用大用户直接消纳风电的利益均衡优化模型［J］. 中国电力, 2015, 48（6）: 20-25.

ZHANG Chen, CHEN Kun, TAN Zhongfu, et al. Optimization model of wind power accommodation for interests-balancing with large consumer ［J］.Electric Power, 2015, 48 （6）: 20-25.

［12］孟凡永, 张强, 谭春桥,等. 合作对策论理论基础［M］. 北京：科学出版社，2016: 1-31.

［13］汪贤裕, 肖玉明. 博弈论及其应用［M］. 北京：科学出版社，2008: 191-196.

［14］王莹莹, 梅生伟, 刘锋. 混合电力系统合作博弈规划的分配策略研究［J］. 系统科学与数学, 2012, 32（4）: 418-428.

WANG Yingying, MEI Shengwei, LIU Feng. Imputation schemes for the cooperative game in the hybrid power system planning ［J］.Journal of Systems Science and Mathematical Sciences, 2012, 32（4）: 418-428.

［15］张延宇, 曾鹏, 臧传志. 智能电网环境下多电动汽车协调充电优化调度算法［J］. 科学技术与工程, 2015, 15（26）: 60-64.

ZHANG Yanyu, ZENG Peng, ZANG Chuanzhi.Coordinated optimization charging algorithm for electric vehicles in smart grid ［J］.Science Technology and Engineering, 2015, 15 （26）: 60-64.

［16］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）: 1-9.

WU Xiong, WANG Xiuli, WANG Jianxue, et al. Economic generation scheduling of a microgrid using mixed integer linear programming ［J］.Proceedings of the CSEE, 2013,33（28）: 1-9.

［17］刘继春. 电力调度优化理论及其应用［M］. 北京：中国电力出版社，2010: 36-40.

［18］施泉生, 平宗飞, 陈敏骏. 计及电动汽车入网的电价联动模型［J］. 电力自动化设备, 2014, 34（11）: 34-40.

SHI Quansheng, PING Zongfei, CHEN Minjun. Electricity price linkage model considering V2G ［J］.Electric Power Automation Equipment, 2014, 34（11）: 34-40.

[1]	王瀚琳, 刘洋, 许立雄, 陈贤邦, 谭思维. 考虑风电消纳的区域多微网分层协调优化模型[J]. 电力建设, 2020, 41(8): 87-98.
[2]	郑惠萍, 曾鹏, 刘新元, 程雪婷, 薄利明, 杨尉薇, 张一帆, 崔杨. 基于误差前馈预测的多时空尺度风电集群有功功率分层控制策略[J]. 电力建设, 2020, 41(8): 120-128.
[3]	张浩禹，邱晓燕，周晟锐，赵有林，李凌昊，张楷 . 基于机会约束目标规划的多电-气互联综合能源系统分布式优化模型[J]. 电力建设, 2020, 41(7): 82-91.
[4]	谭忠富，谭彩霞，蒲雷，杨佳澄. 基于协同免疫量子粒子群优化算法的虚拟电厂双层博弈模型[J]. 电力建设, 2020, 41(6): 9-17.
[5]	苏俊妮，张鑫，赵俊炜，张锐，曲明辉，杨艳红. 计及需求响应和储能的电-气综合能源系统优化调度[J]. 电力建设, 2020, 41(5): 1-8.
[6]	林紫菡，蒋晨威，陈明辉，尚慧玉，赵宏伟，阳曾，王一铮，文福拴. 计及柔性负荷的综合能源系统低碳经济运行[J]. 电力建设, 2020, 41(5): 9-18.
[7]	都成，魏震波. 基于模糊激励型需求响应的微电网两阶段优化调度模型[J]. 电力建设, 2020, 41(5): 37-44.
[8]	朱金菊，赵清松，刘成刚，王勇，李琼慧，龙虹毓. 考虑终端“储热”差异性的调峰能力提升与风电消纳最优化技术[J]. 电力建设, 2019, 40(8): 69-76.
[9]	周思宇，刘成刚，戈阳阳，赵清松，李琼慧，王彩霞，龙虹毓. 面向风电消纳的车-储-热协同调度策略[J]. 电力建设, 2019, 40(8): 77-83.
[10]	谭思维，刘洋，许立雄，王瀚琳. 考虑风电消纳的区域多微网-配电网能源交易模式[J]. 电力建设, 2019, 40(7): 1-9.
[11]	邓强，詹红霞，杨孝华，梅哲，张豪，朱金龙. 直购电背景下利用储能配合旋转备用的风电并网容量优化[J]. 电力建设, 2019, 40(4): 98-109.
[12]	李平，王春生，穆永强，王海霞，唱友义，张耕宇，刘爱民，李卫东. 供热系统热动态特性回归模型及热电联合调度[J]. 电力建设, 2019, 40(3): 17-26.
[13]	董京营，周博，刘晋源，高红均，石玉东，刘俊勇，吕林. 考虑用户舒适度的虚拟电厂热电联合调度模型[J]. 电力建设, 2019, 40(1): 19-26.
[14]	明煦，陈艳，刘源，邹芹，李玮，胡文博，王宣，杨军. 适应于光伏接入与商圈通勤需求的电动汽车充换电能量管理策略[J]. 电力建设, 2019, 40(1): 49-59.
[15]	李刚, 黄奕敏, 郑顾平, 周国亮. 雷电网络在电动汽车充电交易中的技术前景[J]. 电力建设, 2018, 39(9): 78-86.