针对新型电力系统中可再生能源出力及负荷需求的不确定性造成源荷协调困难,导致难以制定合理的分时电价的问题,该文提出一种考虑源荷不确定性的分时电价动态修正机制。首先,根据可再生能源出力的波动性以及不确定性,建立新能源并网功率与并网电量偏差量化模型;其次,根据需求侧负荷的变化特征,结合可再生能源出力不确定性,通过多种不确定性因素影响条件的误差计算方法,建立电价概率密度模型。然后,根据负荷上报的用电量以及预报电价,建立考虑源荷不确定性的电力市场分时电价动态修正与优化模型,并采用粒子群算法进行模型求解。最后,通过实际运行数据仿真验证该文所提方法的有效性。
Abstract
In view of the uncertainty of renewable energy output and load demand in the new power system, the source-load coordination is difficult, and it is difficult to establish a reasonable time-of-use electricity price. This paper proposes a dynamic modification mechanism of time-of-use electricity prices considering the uncertainty of source load. First, according to the volatility and uncertainty of renewable energy output, calculate the deviation of new energy grid-connected electricity; Secondly, according to the change characteristics of the demand side load, combined with the uncertainty of renewable energy generation, through the error calculation method of multiple uncertainty conditions, the probability density of the final output variable is obtained. Then, according to the electricity consumption reported by the load and the forecast electricity price, a power market price setting model with the uncertainty of the source load is established, and the dynamic correction of the time-of-use electricity price considering the uncertainty of the source load is carried out. Finally, the effectiveness of the method proposed in this paper is verified by actual data simulation.
关键词
电力市场 /
动态电价 /
可再生能源 /
电价优化 /
新型电力系统
Key words
electricity market /
dynamic electricity price /
renewable energy /
electricity price optimization /
new power system
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参考文献
[1] 罗毅, 邱实. 基于负荷侧响应的含储热热电联产的风电消纳模型[J]. 太阳能学报, 2021, 42(2): 90-96.
LUO Y, QIU S.A wind power consumption model of CHP with thermal energy storage based on demand response[J]. Acta energiae solaris sinica, 2021, 42(2): 90-96.
[2] 王怡, 杨知方, 余娟, 等. 节点电价与对偶乘子的内在关联分析与推广[J]. 电力系统自动化, 2021, 45(6): 82-91.
WANG Y, YANG Z F, YU J, et al.Analysis and extension of internal relationship between locational marginal price and dual multiplier[J]. Automation of electric power systems, 2021, 45(6): 82-91.
[3] 张粒子, 唐成鹏, 刘方, 等. 基于多智能体强化学习的电力现货市场定价机制研究(二): 结合理论与仿真的定价机制决策框架[J]. 中国电机工程学报, 2021, 41(3): 1004-1017.
ZHANG L Z, TANG C P, LIU F, et al.Research on pricing mechanism of electricity spot market based on multi-agent reinforcement learning(Part Ⅱ): decision-making framework of pricing mechanism combined with theory and simulation[J]. Proceedings of the CSEE, 2021 , 41(3): 1004-1017.
[4] 景皓, 贾伯岩, 李小玉, 等. 考虑节点电价机制的主动配电网两阶段动态故障恢复方法[J]. 电力系统保护与控制, 2020, 48(20): 29-37.
JING H, JIA B Y, LI X Y, et al.A two-stage dynamic fault recovery method for active distribution network considering the node price mechanism[J]. Power system protection and control, 2020, 48(20): 29-37.
[5] 聂涌泉, 顾慧杰, 彭超逸, 等. 激励性含风电竞标日前市场出清电价机制的建模[J]. 电力系统保护与控制, 2020, 48(19): 25-34.
NIE Y Q, GU H J, PENG C Y, et al.Research on modeling the incentive electricity pricing mechanism in day-ahead electricity market clearing containing wind power bidding[J]. Power system protection and control, 2020, 48(19): 25-34.
[6] 杨柳, 曾智健, 张杰, 等. 统一结算点电价机制下金融输电权的交易模拟与结算风险评估[J]. 电力系统自动化, 2021, 45(6): 116-122.
YANG L, ZENG Z J, ZHANG J, et al.Transaction simulation and settlement risk assessment of financial transmission right with electricity pricing mechanism of unified settlement point[J]. Automation of electric power systems, 2021, 45(6): 116-122.
[7] 张粒子, 丛野, 陶文斌, 等. 电力现货市场环境下提供位置信号电价机制的协同作用[J]. 中国电力, 2020, 53(9): 9-18, 46.
ZHANG L Z, CONG Y, TAO W B, et al.Coordination functions of electricity price providing locational signals under the circumstance of electricity spot market[J]. China electric power, 2020, 53(9): 9-18, 46.
[8] 熊小萍, 李航, 李宁. 基于分布式电源模块化互联的多边交易电价机制设计[J]. 电网技术, 2020, 44(7): 2572-2581.
XIONG X P, LI H, LI N.Multilateral trading electricity price mechanism based on distributed power generation module interconnection[J]. Power system technology, 2020, 44(7): 2572-2581.
[9] 芮涛, 李国丽, 胡存刚, 等. 考虑电价机制的微电网群主从博弈优化方法[J]. 中国电机工程学报, 2020, 40(8): 2535-2545.
RUI T, LI G L, HU C G, et al.Stackelberg game optimization method for microgrid cluster considering electricity price mechanism[J]. Proceedings of the CSEE, 2020, 40(8): 2535-2545.
[10] 史一炜, 冯冬涵, ELLA ZHOU, 等. 基于主从博弈的充电服务商充电引导方法及其定价策略[J]. 电工技术学报, 2019, 34(增刊2): 742-751.
SHI Y W, FENG D H, ZHOU E, et al.Stackelberg game based on supervised charging method and pricing strategy of charging service providers[J]. Transactions of China Electrotechnical Society, 2019, 34(S2): 742-751.
[11] SUN P, TENG Y, CHEN Z.Robust coordinated optimization for multi-energy systems based on multiple thermal inertia numerical simulation and uncertainty analysis[J]. Applied energy, 2021, 296: 116982.
[12] 刘方, 张粒子, 李秀峰, 等. 巴西电力市场研究:电力市场化改革历程与市场交易机制[J]. 中国电机工程学报, 2020, 40(8): 2501-2514.
LIU F, ZHANG L Z, LI X F, et al.Research on Brazil’s electricity market: electricity market reform process and market transaction mechanism[J]. Proceedings of the CSEE, 2020, 40(8): 2501-2514.
[13] 张晓东, 艾欣, 潘玺安. 考虑用户可调度潜力的负荷聚合商优化调度策略[J/OL]. 华北电力大学学报(自然科学版), [2022-11-05]. http://kns.cnki.net/kcms/detail/13.1212.TM.20210811.1138.002.html.
ZHANG X D, AI X, PAN X A. Optimal scheduling strategy of load aggregators considering user’s scheduling potential[J/OL]. Journal of North China Electric Power University(natural science edition), [2022-11-05]. http://kns.cnki.net/kcms/detail/13.1212.TM.20210811.1138.002.html.
[14] 郑云飞, 熊志, 王博, 等. 考虑最优消纳区间的区域能源聚合商博弈策略[J]. 现代电力, 2022, 39(1): 64-71.
ZHENG Y F, XIONG Z, WANG B, et al.Game strategy of regional energy aggregators considering optimal accommodation interval[J]. Modern electric power, 2022, 39(1): 64-71.
[15] 冷钊莹, 陈中, 邢强, 等. 基于负荷类型细分的负荷聚合商日前投标非合作博弈模型[J]. 电网与清洁能源, 2020, 36(5): 17-28.
LENG Z Y, CHEN Z, XING Q, et al.Day-ahead bidding model of load aggregators based on load type subdivision and non-cooperative game[J]. Power system and clean energy, 2020, 36(5): 17-28.
基金
国网内蒙古东部电力有限公司科技项目（526601200005）
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