EN计及多级市场代理购电成本传导风险的分时电价定价模型
Time-of-Use Pricing Model Considering the Risk of Cost Transmission in Multi-level Market Agent Electricity Purchase
- 中国电力 2025年58卷第11期 页码：25-37
- 作者机构：
1. 华北电力大学 电气与电子工程学院,北京,102206
2. 国网能源研究院有限公司,北京,102209
- 作者简介：
- 基金信息：国家电网有限公司科技项目（面向园区级“源网荷储一体化”项目的价格机制理论模型研究与应用，1400-202457287A-1-1-ZN）。
DOI：10.11930/j.issn.1004-9649.202503013
中图分类号：-
网络出版：2025-12-01，
纸质出版：2025-12-01
- 稿件说明：
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王斯琪, 曹昉, 姚力. 计及多级市场代理购电成本传导风险的分时电价定价模型[J]. 中国电力, 2025, 58(11): 25-37.
WANG Siqi, CAO Fang, YAO Li. Time-of-Use Pricing Model Considering the Risk of Cost Transmission in Multi-level Market Agent Electricity Purchase[J]. 2025, 58(11): 25-37.
王斯琪, 曹昉, 姚力. 计及多级市场代理购电成本传导风险的分时电价定价模型[J]. 中国电力, 2025, 58(11): 25-37. DOI： 10.11930/j.issn.1004-9649.202503013.
WANG Siqi, CAO Fang, YAO Li. Time-of-Use Pricing Model Considering the Risk of Cost Transmission in Multi-level Market Agent Electricity Purchase[J]. 2025, 58(11): 25-37. DOI： 10.11930/j.issn.1004-9649.202503013.
摘要
针对当前省内分时电价机制忽略省级以上电力市场交易成本影响且忽视代理购电商购电成本传导风险的问题，提出一种考虑多级市场代理购电成本传导风险的分时电价定价模型。首先，基于购电成本最小化目标，设计多级市场购电决策模型；然后，采用概率场景描述现货市场价格预测偏差和用户响应预测偏差，并以条件风险价值（conditional value at risk，CVaR）作为传导风险评估指标，建立最大化传导上级市场购电成本变动和最小化代理购电商传导风险为目标的分时电价模型；最后，采用k-means和粒子群算法进行求解。算例分析结果表明，所提出的分时电价模型能更准确传导多级市场的成本与风险，向用户释放多级电力市场的综合价格信号，并能够为代理购电商提供多级市场交易情境下的风险分析。
Abstract
Aiming at the current issue that the intra-provincial time-of-use (TOU) electricity pricing mechanism overlooks the impact of transaction costs in electricity markets above the provincial level and ignores the risk of cost transmission for agent purchasers
this paper proposes a TOU electricity pricing model that considers the risk of cost transmission in multi-level market for agent electricity procurement. Firstly
a multi-level market electricity procurement decision-making model is established based on the objective of minimizing electricity procurement costs. Then
probabilistic scenarios are used to describe prediction deviations of spot market prices and user responses. Conditional value at risk (CVaR) is adopted as the risk assessment indicator for cost transmission. A TOU electricity pricing model is constructed with the dual objectives of maximizing the transmission of procurement cost fluctuations from upper-level markets and minimizing the transmission risk for agent electricity purchasers. Finally
k-means and particle swarm optimization (PSO) are used to solve the model. Case study shows that the proposed model can more accurately reflect the cost and risk of multi-level markets
deliver integrated price signals to users
and provide risk analysis for electricity retailers under multi-level market transactions.
关键词
Keywords
references
1曹婧祎, 何永秀, 周静涵, 等. 基于需求侧响应的不同时间尺度动态分时电价时段优化研究[J]. 电力科学与技术学报, 2024, 39 (6): 242- 250, 268.
CAO Jingyi, HE Yongxiu, ZHOU Jinghan, et al. Time slot optimization of dynamic time-of-use tariffs under different time scales based on demand side response[J]. Journal of Electric Power Science and Technology, 2024, 39 (6): 242- 250, 268.
2董雷, 倪佳炜, 张师铭, 等. 基于双重博弈的电价套餐设计方法[J]. 电网技术, 2024, 48 (2): 688- 700.
DONG Lei, NI Jiawei, ZHANG Shiming, et al. Designing of electricity price package method based on dual game[J]. Power System Technology, 2024, 48 (2): 688- 700.
3黄剑平, 余欣, 赵东生, 等. 考虑源网荷效益的峰谷电价与峰谷时段双层优化模型[J]. 电力自动化设备, 2024, 44 (6): 217- 224.
HUANG Jianping, YU Xin, ZHAO Dongsheng, et al. Bi-layer optimization model of peak-valley prices and peak-valley periods considering benefits of source-grid-load[J]. Electric Power Automation Equipment, 2024, 44 (6): 217- 224.
4李骏龙, 尤培培, 张超, 等. 基于双重差分模型的分时电价机制对用电成本的影响分析[J]. 中国电力, 2024, 57 (11): 173- 182.
LI Junlong, YOU Peipei1 ZHANG Chao, et al. Analysis on the effect of time-of-use electricity price on electricity cost based on difference-in-differences model[J]. Electric Power, 2024, 57 (11): 173- 182.
5黄剑平, 陈皓勇, 钟佳宇, 等. 基于用户成本选择用户范围的分时电价最优策略[J]. 中国电力, 2020, 53 (9): 107- 116.
HUANG Jianping, CHEN Haoyong, ZHONG Jiayu, et al. Optimal Time-of-use price strategy with selecting customer's range based on cost[J]. Electric Power, 2020, 53 (9): 107- 116.
6蔡湛, 李泽文, 邹睿奇, 等. 基于负荷转移的售电公司分时电价优化策略[J]. 南方电网技术, 2024, 18 (1): 77- 84.
CAI Zhan, LI Zewen, ZOU Ruiqi, et al. Optimization strategy of time-of-use electricity price for electricity selling companies based on load transfer[J]. Southern Power System Technology, 2024, 18 (1): 77- 84.
7刘显茁, 李崇浩, 王皓怀, 等. 新型电力系统环境下电网储能运营机制和成本传导工程应用[J]. 能源与环保, 2024, 46 (3): 178- 183.
Liu Xianzhuo, Li Chonghao, Wang Haohuai, et al. Research on operation mechanism and cost conduction project application of grid energy storage in new power system environment[J]. China Energy and Environmental Protection, 2024, 46 (3): 178- 183.
8何凤枝. 电力市场化改革对碳成本传导机制的影响[J]. 低碳世界, 2024, 14 (2): 163- 165.
9闫豪楠, 赵文会, 刘玮. 考虑新能源参与的售电公司风险管理模型[J]. 中国电机工程学报, 2018, 38 (23): 6947- 6954, 7128.
YAN Haonan, ZHAO Wenhui, LIU Wei. A risk management model of power retailers considering the participation of new energy[J]. Proceedings of the CSEE, 2018, 38 (23): 6947- 6954, 7128.
10李亚鹏, 赵志鹏, 于申, 等. 计及风险的多尺度电力市场下梯级水电月度发电计划制定方法[J]. 中国电机工程学报, 2020, 40 (8): 2525- 2535.
LI Yapeng, ZHAO Zhipeng, YU Shen, et al. Risk constrained monthly generation scheduling of cascade hydropower plants in multiple time scale markets[J]. Proceedings of the CSEE, 2020, 40 (8): 2525- 2535.
11ALMAHDI S, YANG S Y. An adaptive portfolio trading system: a risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown[J]. Expert Systems with Applications, 2017, 87, 267- 279. DOI
12胡志林, 陈淳, 朱金吉. 基于CVaR的电网企业代理购电交易模型的研究[J]. 自动化应用, 2023, 64 (6): 195- 198, 201.
HU Zhilin, CHEN Chun, ZHU Jinji. Research on the model of power purchase agency transactions of power grid enterprises based on CVaR[J]. Automation Application, 2023, 64 (6): 195- 198, 201.
13黄婧杰, 李金成, 刘科明, 等. 含CVaR及增广ε-约束法的多目标光储充电站容量优化配置[J]. 南方电网技术, 2023, 17 (10): 94- 103.
HUANG Jingjie, LI Jincheng, LIU Keming, et al. Optimal allocation of multi-objective photovoltaic energy storage charging station capacity with CVaR and augmented ε-constraint method[J]. Southern Power System Technology, 2023, 17 (10): 94- 103.
14ASENSIO M, CONTRERAS J. Stochastic unit commitment in isolated systems with renewable penetration under CVaR assessment[J]. IEEE Transactions on Smart Grid, 2016, 7 (3): 1356- 1367. DOI
15李彦斌, 王佳妮, 肖婷婷, 等. 计及风险的电网企业代理购电中长期分时段滚动交易决策方法[J]. 电网技术, 2023, 47 (10): 4237- 4245.
LI Yanbin, WANG Jiani, XIAO Tingting, et al. Rolling trading decision methodology of grid companies in time division medium- & long-term electricity market considering risk management[J]. Power System Technology, 2023, 47 (10): 4237- 4245.
16郭祚刚, 喻磊, 胡洋, 等. 基于合作博弈的综合能源服务商现货市场风险规避策略[J]. 中国电力, 2019, 52 (11): 28- 34.
GUO Zuogang, YU Lei, HU Yang, et al. Research on competition strategy of integrated energy service provider under the pool-based market mechanism[J]. Electric Power, 2019, 52 (11): 28- 34.
17LI C, XU Y, YU X, et al. Risk-averse energy trading in multienergy microgrids: a two-stage stochastic game approach[J]. IEEE Transactions on Industrial Informatics, 2017, 13 (5): 2620- 2630.
18陈黎军, 潘熙, 黄茜, 等. 电网企业代理购电风险及其策略优化研究[J]. 广东电力, 2024, 37 (1): 39- 48.
CHEN Lijun, PAN Xi, HUANG Qian, et al. Study on electricity purchasing agent service and strategy optimization of power grid enterprises[J]. Guangdong Electric Power, 2024, 37 (1): 39- 48.
19王博钰, 许小峰, 曹正, 等. 基于多维度风险度量的代理购电多市场交易策略研究[J]. 电网技术, 2025, 49 (3): 1032- 1044.
WANG Boyu, XU Xiaofeng, CAO Zheng, et al. Research on multi-market trading strategies for agency power purchase based on multi-dimensional risk measurement[J]. Power System Technology, 2025, 49 (3): 1032- 1044.
20曾丹, 姚建国, 杨胜春, 等. 计及价格型负荷响应不确定性的概率潮流计算[J]. 电力系统自动化, 2015, 39 (20): 66- 71, 97.
ZENG Dan, YAO Jianguo, YANG Shengchun, et al. Probabilistic load flow calculation considering price-elasticity load uncertainties[J]. Automation of Electric Power Systems, 2015, 39 (20): 66- 71, 97.
21孙博宇, 喻洁, 梅军, 等. 考虑可调负荷集群响应不确定性的联合调度模型[J]. 电力系统保护与控制, 2016, 44 (23): 61- 67.
SUN Boyu, YU Jie, MEI Jun, et al. Combined dispatch model of adjustable load clusters considering response uncertainty[J]. Power System Protection and Control, 2016, 44 (23): 61- 67.
22易明月, 童晓阳. 考虑风荷预测误差不确定性的动态经济调度[J]. 电网技术, 2019, 43 (11): 4050- 4057.
YI Mingyue, TONG Xiaoyang. Dynamic economic dispatch considering uncertainties of wind power and load forecast error[J]. Power System Technology, 2019, 43 (11): 4050- 4057.
23邢家省, 杨义川, 吴桑. 关于n维正态分布线性函数服从正态分布的证明[J]. 吉首大学学报(自然科学版), 2021, 42 (3): 1- 5.
XING Jiasheng, YANG Yichuan, WU Sang. Proof that n-dimensional normally distributed linear functions obey normal distribution[J]. Journal of Jishou University (Natural Sciences Edition), 2021, 42 (3): 1- 5.
24张立卓. 两个非独立正态变量的联合分布不服从二维正态分布的示例[J]. 大学数学, 2014, 30 (2): 94- 98.
ZHANG Lizhuo. Examples on the joint distribution of two non-independent normal variables does not obey two-dimensional normal distribution[J]. College Mathematics, 2014, 30 (2): 94- 98.
25马燕峰, 范振亚, 刘伟东, 等. 考虑碳权交易和风荷预测误差随机性的环境经济调度[J]. 电网技术, 2016, 40 (2): 412- 418.
MA Yanfeng, FAN Zhenya, LIU Weidong, et al. Environmental and economic dispatch considering carbon trading credit and randomicity of wind power and load forecast error[J]. Power System Technology, 2016, 40 (2): 412- 418.
26王子强, 李豹, 杜哲宇, 等. PJM电力市场风险管控措施及对南方区域的建议[J]. 南方电网技术, 2024, 18 (1): 28- 37, 68.
WANG Ziqiang, LI Bao , DU Zheyu, et al. Risk management and control measures in pjm power market and suggestions for southern region[J]. Southern Power System Technology, 2024, 18 (1): 28- 37, 68.
27曹祎, 张莉, 郭静, 等. 基于大语言模型的低碳电力市场发展应用前景[J]. 智慧电力, 2024, 52 (2): 8- 16. DOI
CAO Yi, ZHANG Li, GUO Jing, et al. Prospects for development of low-carbon electricity markets based on large language models[J]. Smart Power, 2024, 52 (2): 8- 16. DOI
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