提出一种基于主从博弈的社区微网运营商电价优化方法,并通过场景削减对光伏不确定性进行描述。首先分别针对微网运营商和用户建立优化运行模型。然后分析运营商与用户之间的博弈关系,建立以运营商为领导者的主从博弈模型,并采用基于场景削减法的最优电价两阶段求解方法求解考虑不确定性的最优电价。最后,经算例分析验证,所提电价优化方法可将运营商的收益提高14.2%,还可将用户的电热成本降低0.92%;同时表明适量的储能可促进光伏的就地消纳并提高运营商收益;另外,该方法所求最优电价在不同随机场景下的运营商收益均值提高37.6元,而不同场景下的波动方差降低16.9%,即该电价在不同光伏出力场景下的普适性更好。
Abstract
electricity price optimization method for community microgrid operators based on leader-follower game is proposed inthis paper, At the same time, the photovoltaic uncertainty through scene reduction is described. Firstly, establish optimization operation models for microgrid operators and users respectively. Secondly, analyze the game relationship between operators and users, establish a leader-follower game model led by operators, and use a two-stage solution method based on scene reduction to solve the optimal electricity price considering uncertainty. Finally, through case analysis and verification, the proposed electricity price optimization method can increase the revenue of operators by 14.2%, while reducing the electricity and heating cost of users by 0.92%; It also indicates that an appropriate amount of energy storage can promote the on-site consumption of photovoltaic energy and increase the revenue of operators; In addition, the average revenue for operators in different random scenarios when the optimal electricity price obtained by this method increases by 37.6 yuan, while the fluctuation variance in different scenarios decreases by 16.9%, which means that the electricity price has better universality in different photovoltaic output scenarios.
关键词
不确定性分析 /
微网 /
优化 /
光伏 /
主从博弈 /
场景削减
Key words
uncertainty analysis /
microgrids /
optimization /
photovoltaic /
leader-follower game /
scene reduction
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 贺元康, 丁涛, 刘瑞丰, 等. 新能源消纳电量库交易机制的实践与经验[J]. 电力系统自动化, 2021, 45(7): 163-169.
HE Y K, DING T, LIU R F, et al.Practice and experience of trading mechanism for energy pool of renewable energy accommodation[J]. Automation of electric power systems, 2021, 45(7): 163-169.
[2] 张大海, 贠韫韵, 王小君, 等. 计及风光不确定性的新能源虚拟电厂多时间尺度优化调度[J]. 太阳能学报, 2022, 43(11): 529-537.
ZHANG D H, YUN Y Y, WANG X J, et al.Multi-time scale of new energy scheduling optimization for virtual power plant considering uncertainty of wind power and photovoltaic power[J]. Acta energiae solaris sinica, 2022, 43(11): 529-537.
[3] LI S M, WANG J, LIU Q, et al.Analysis of status of photovoltaic and wind power abandoned in China[J]. Journal of power and energy engineering, 2017, 5(1): 91-100.
[4] 王秀丽, 闫璐, 刘豹, 等. 基于合作-非合作博弈的光储荷网协同运行策略[J]. 太阳能学报, 2023, 44(5): 128-138.
WANG X L, YAN L, LIU B, et al.Cooperative operational strategies of photovoltaic, energy storage, load and power grid based on cooperative and non-cooperative game[J]. Acta energiae solaris sinica, 2023, 44(5): 128-138.
[5] 陈厚合, 吴桐, 李本新, 等. 考虑建筑热惯性的园区代理商电价策略及用能优化[J]. 电力系统自动化, 2021, 45(3): 148-156.
CHEN H H, WU T, LI B X, et al.Electricity pricing strategy of park retailer and energy optimization considering thermal inertia of building[J]. Automation of electric power systems, 2021, 45(3): 148-156.
[6] 李媛, 冯昌森, 文福拴, 等. 含电动汽车和电转气的园区能源互联网能源定价与管理[J]. 电力系统自动化, 2018, 42(16): 1-10.
LI Y, FENG C S, WEN F S, et al.Energy pricing and management for park-level energy internets with electric vehicles and power-to-gas devices[J]. Automation of electric power systems, 2018, 42(16): 1-10.
[7] 王海洋, 李珂, 张承慧, 等. 基于主从博弈的社区综合能源系统分布式协同优化运行策略[J]. 中国电机工程学报, 2020, 40(17): 5435-5445.
WANG H Y, LI K, ZHANG C H, et al.Distributed coordinative optimal operation of community integrated energy system based on stackelberg game[J]. Proceedings of the CSEE, 2020, 40(17): 5435-5445.
[8] LIU N, HE L, YU X H, et al.Multiparty energy management for grid-connected microgrids with heat-and electricity-coupled demand response[J]. IEEE transactions on industrial informatics, 2018, 14(5): 1887-1897.
[9] 刘文霞, 王舒, 张雯程, 等. 考虑需求侧电价的配电网储能设备运行策略与容量的协调优化[J]. 现代电力, 2018, 35(5): 70-78.
LIU W X, WANG S, ZHANG W C, et al.The coordination optimization method of operation strategy and capacity of energy storage devices in distribution network considering demand side electricity price[J]. Modern electric power, 2018, 35(5): 70-78.
[10] 王仕俊, 平常, 薛国斌. 考虑共享储能的社区综合能源系统协同优化研究[J]. 中国电力, 2018, 51(8): 77-84.
WANG S J, PING C, XUE G B.Synergic optimization of community energy Internet considering the shared energy storage[J]. Electric power, 2018, 51(8): 77-84.
[11] 蒋向兵, 汤波, 余光正, 等. 面向新能源就地消纳的园区储能与电价协调优化方法[J]. 电力系统自动化, 2022, 46(5): 51-64.
JIANG X B, TANG B, YU G Z, et al.Coordination and optimization method of park-level energy storage and electricity price for local accommodation of renewable energy[J]. Automation of electric power systems, 2022, 46(5): 51-64.
[12] 帅轩越, 马志程, 王秀丽, 等. 基于主从博弈理论的共享储能与综合能源微网优化运行研究[J]. 电网技术, 2023, 47(2): 679-690.
SHUAI X Y, MA Z C, WANG X L, et al.Optimal operation of shared energy storage and integrated energy microgrid based on leader-follower game theory[J]. Power system technology, 2023, 47(2): 679-690.
[13] 朱怡莹, 周荣生, 罗龙波. 考虑需求响应与光伏不确定性的电力系统经济调度[J]. 太阳能学报, 2023, 44(1): 62-68.
ZHU Y Y, ZHOU R S, LUO L B.Economic dispatch of power system considering demand response and PV uncertainty[J]. Acta energiae solaris sinica, 2023, 44(1): 62-68.
[14] 董文略, 王群, 杨莉. 含风光水的虚拟电厂与配电公司协调调度模型[J]. 电力系统自动化, 2015, 39(9): 75-81, 207.
DONG W L, WANG Q, YANG L.A coordinated dispatching model for a distribution utility and virtual power plants with wind/photovoltaic/hydro generators[J]. Automation of electric power systems, 2015, 39(9): 75-81, 207.
[15] 程杉, 黄天力, 魏荣宗. 含冰蓄冷空调的冷热电联供型微网多时间尺度优化调度[J]. 电力系统自动化, 2019, 43(5): 30-38.
CHENG S, HUANG T L, WEI R Z.Multi-time-scale optimal scheduling of CCHP microgrid with ice-storage air-conditioning[J]. Automation of electric power systems, 2019, 43(5): 30-38.
[16] 程杉, 徐建宇, 何畅, 等. 计及不确定性的综合能源系统容量规划方法[J]. 电力系统保护与控制, 2021, 49(18): 17-24.
CHENG S, XU J Y, HE C, et al.Optimal capacity planning of an integrated energy system considering uncertainty[J]. Power system protection and control, 2021, 49(18): 17-24.
[17] 赵诣, 方陈, 冯冬涵, 等. 考虑电池储能寿命损耗的风光储微网随机日前调度策略[J]. 电气工程学报, 2022, 17(3): 210-218.
ZHAO Y, FANG C, FENG D H, et al.Stochastic day-ahead scheduling optimization for wind-PV-ES microgrid considering battery life loss[J]. Journal of electrical engineering, 2022, 17(3): 210-218.
PDF(1277 KB)
