考虑源荷预测偏差的电力系统备用容量优化及成本分摊

曹智超; 贾燕冰; 黄亮; 段麟奇

doi:10.19912/j.0254-0096.tynxb.2025-0247

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (6) : 155-168. DOI: 10.19912/j.0254-0096.tynxb.2025-0247

考虑源荷预测偏差的电力系统备用容量优化及成本分摊

曹智超^1,2, 贾燕冰^1,2, 黄亮^1,2, 段麟奇^1,2

作者信息 +

RESERVE CAPACITY OPTIMIZATION AND COST ALLOCATION OF POWER SYSTEM CONSIDERING SOURCE-LOAD PREDICTION DEVIATION

Cao Zhichao^1,2, Jia Yanbing^1,2, Huang Liang^1,2, Duan Linqi^1,2

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文章历史 +

摘要

该文考虑不确定性针对需求侧参与的电力系统备用容量优化及成本分摊机制开展研究,基于高斯-拉普拉斯分布改进了风光预测偏差概率分布模型,提出基于Box Muller变换的改进拉丁超立方抽样方法以模拟备用需求场景,考虑条件风险约束构建成本最小为目标的备用总容量优化模型;提出以分摊效用值满足Maxmin公平为目标,以成本分摊约束区间为约束的备用容量成本分摊模型。IEEE-30标准测试算例表明该文改进拉丁超立方抽样法可有效提升抽样效率减小计算时间,所提分配策略可实现权责分配,更有效激励需求侧参与备用市场。

Abstract

In this paper, the optimization strategy of reserve capacity and cost sharing mechanism are studied considering the source-load uncertainty. The probability distribution model of wind and PV forecast deviation is improved based on Gauss-Laplace distribution, and an improved Latin hypercube sampling method is proposed based on Box-Muller transformation to promote the efficiency and accuracy. And then a reserve capacity optimization model is constructed to minimize the cost considering the constraints of condition risk. Finally, a reserve cost sharing mechanism is established with the objective of achieving Maxmin fairness in the allocation utility value and the constraint interval of cost allocation as the constraint condition. The IEEE-30 standard test cases show that the improved Latin hypercube sampling method can effectively improve the sampling efficiency and reduce the computation time, and the benefit sharing is more reasonable based on the proposed strategy, which can more effectively motivate the demand side to participate in the standby market.

导出引用

曹智超, 贾燕冰, 黄亮, 段麟奇. 考虑源荷预测偏差的电力系统备用容量优化及成本分摊[J]. 太阳能学报. 2026, 47(6): 155-168 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0247

Cao Zhichao, Jia Yanbing, Huang Liang, Duan Linqi. RESERVE CAPACITY OPTIMIZATION AND COST ALLOCATION OF POWER SYSTEM CONSIDERING SOURCE-LOAD PREDICTION DEVIATION[J]. Acta Energiae Solaris Sinica. 2026, 47(6): 155-168 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0247

中图分类号： TM7

参考文献

[1] 李增辉, 于钊, 孙大雁, 等. 新能源预测纳入备用对平衡和消纳的影响研究[J]. 电网技术, 2024, 48(4): 1393-1402.
LI Z H, YU Z, SUN D Y, et al.Research on influences to power balance & new energy consumption of taken-into-account proportion of new energy’s predicted output in day-ahead power reserve[J]. Power system technology, 2024, 48(4): 1393-1402.
[2] CRUZ-DE-JESÚS E, MARANO-MARCOLINI A, MARTÍNEZ-RAMOS J L. Participation of energy communities in electricity markets and ancillary services: an overview of successful strategies[J]. Energies, 2024, 17(18): 4631.
[3] 闫斯哲, 王维庆, 王海云, 等. 源荷两端不确定性的跨区系统运行策略研究[J]. 太阳能学报, 2022, 43(8): 8-16.
YAN S Z, WANG W Q, WANG H Y, et al.Research on operation strategy of cross regional system with uncertainty at both ends of power supply and load[J]. Acta energiae solaris sinica, 2022, 43(8): 8-16.
[4] 崔杨, 孙喜斌, 朱晗, 等. 考虑“燃煤+”耦合发电与灵活性资源备用的综合能源系统低碳经济调度[J]. 中国电机工程学报, 2026, 46(1): 198-211, I0015.
CUI Y, SUN X B, ZHU H, et al.Low-carbon economic dispatch of integrated energy systems considering “coal-fired+” coupling power generation and flexible resource reserves[J]. Proceedings of the CSEE, 2026, 46(1): 198-211, I0015.
[5] RANCILIO G, BOVERA F, SPILLER M, et al.BESS and the ancillary services markets: a symbiosis yet? Impact of market design on performance[J]. Applied energy, 2024, 375: 124153.
[6] 刘硕, 杨燕, 杨知方, 等. 计及新能源随机特性的备用容量确定及其成本分摊[J]. 电力系统自动化, 2023, 47(4): 10-18.
LIU S, YANG Y, YANG Z F, et al.Reserve capacity determination and its cost allocation considering stochastic characteristics of renewable energy[J]. Automation of electric power systems, 2023, 47(4): 10-18.
[7] 李力行. 考虑动态相关性的电力系统不确定性建模与优化运行方法研究[D]. 武汉: 华中科技大学, 2020.
LI L X.Research on uncertainty modeling and optimal operation method of power system considering dynamic correlation[D]. Wuhan: Huazhong University of Science and Technology, 2020.
[8] 李令仪. 新能源电力系统备用容量优化研究[D]. 北京: 华北电力大学, 2023.
LI L Y.Research on reserve capacity optimization of renewable energy power system[D]. Beijing: North China Electric Power University, 2023.
[9] 肖逸, 谢俊, 刘若平, 等. 计及风电功率预测误差的备用容量计算新方法[J]. 电力系统保护与控制, 2019, 47(9): 72-79.
XIAO Y, XIE J, LIU R P, et al.A new calculation method of reserve capacity considering wind power forecasting error[J]. Power system protection and control, 2019, 47(9): 72-79.
[10] 缪鹏彬. 基于改进核密度估计和拉丁超立方抽样的电动汽车负荷模型[D]. 重庆: 重庆大学, 2016.
MIAO P B.Research on electric vehicle load model based on improved kernel density estimation and Latin hyper cube sampling[D]. Chongqing: Chongqing University, 2016.
[11] 叶伦, 欧阳旭, 姚建刚, 等. 考虑多重不确定性因素的可靠性指标计算与备用容量优化[J]. 上海交通大学学报, 2024, 58(1): 30-39.
YE L, OUYANG X, YAO J G, et al.Reliability index calculation and reserve capacity optimization considering multiple uncertainties[J]. Journal of Shanghai Jiao Tong University, 2024, 58(1): 30-39.
[12] 胡鑫. 考虑源荷双侧不确定性的备用容量配置及优化方法研究[D]. 武汉: 华中科技大学, 2023.
HU X.Study on allocation and optimization method of reserve capacity considering bilateral uncertainty of source and load[D]. Wuhan: Huazhong University of Science and Technology, 2023.
[13] 赵书强, 赵蓬飞, 李志伟, 等. 基于相关机会目标规划的电力系统备用优化研究[J]. 太阳能学报, 2025, 46(1): 540-546.
ZHAO S Q, ZHAO P F, LI Z W, et al.Reserve optimization of power system based on dependent-chance goal programming[J]. Acta energiae solaris sinica, 2025, 46(1): 540-546.
[14] 叶伦. 高比例可再生能源并网辅助服务优化与成本分摊模型研究[D]. 长沙: 湖南大学, 2022.
YE L.Research on optimization and cost allocation model of auxiliary service for grid-connected high-proportion renewable energy[D]. Changsha: Hunan University, 2022.
[15] MEI S F, TAN Q L, LIU Y, et al.Optimal bidding strategy for virtual power plant participating in combined electricity and ancillary services market considering dynamic demand response price and integrated consumption satisfaction[J]. Energy, 2023, 284: 128592.
[16] 邵立政, 刘荣辉, 汪红波, 等. 基于条件风险价值的备用成本分摊方法[J]. 电力系统保护与控制, 2018, 46(20): 23-30.
SHAO L Z, LIU R H, WANG H B, et al.A method for cost allocation of reserve based on conditional value at risk[J]. Power system protection and control, 2018, 46(20): 23-30.
[17] 陶仁峰, 李凤婷, 李燕青, 等. 基于辅助服务费用分摊的新能源电厂并网价格动态计算方法[J]. 电网技术, 2020, 44(3): 962-972.
TAO R F, LI F T, LI Y Q, et al.A dynamic tariff calculation method of renewable power plants based on ancillary service cost allocation[J]. Power system technology, 2020, 44(3): 962-972.
[18] TAO R F, LI F T, LI Y Q, et al.A dynamic tariff calculation method of renewable power plants based on ancillary service cost allocation[J]. Power system technology, 2020, 44(3): 962-972.
[19] 黄康乾, 黄靖茵, 胡鑫, 等. 基于贡献率矩阵的运行备用分摊优化方法建模与仿真[J]. 电子设计工程, 2022, 30(11): 150-154.
HUANG K Q, HUANG J Y, HU X, et al.Modeling and simulation of operational reserve allocation optimization method based on contribution matrix[J]. Electronic design engineering, 2022, 30(11): 150-154.
[20] 余哲轩. 电力市场中灵活爬坡服务的出清及成本分摊机制研究[D]. 广州: 华南理工大学, 2023.
YU Z X.Research on the clearing and cost sharing mechanism of flexible ramping products in the electricity market[D]. Guangzhou: South China University of Technology, 2023.
[21] 周家浩. 考虑相关性的含风电电力系统备用优化及备用成本分摊[D]. 重庆: 重庆大学, 2020.
ZHOU J H.Reserve optimization and reserve cost allocation of power system with wind power considering correlation[D]. Chongqing: Chongqing University, 2020.
[22] 杨康. 考虑风、光出力不确定性的梯级水库群多尺度优化调度[D]. 西安: 西安理工大学, 2024.
YANG K.Multi-scale optimal scheduling of a group of terraced reservoirs considering wind and light output uncertainties[D]. Xi’an: Xi’an University of Technology, 2024.
[23] 王森, 孙永辉, 侯栋宸, 等. 基于多窗宽核密度估计的风电功率超短期自适应概率预测[J]. 高电压技术, 2024, 50(7): 3070-3079.
WANG S, SUN Y H, HOU D C, et al.Ultrashort-term adaptive probabilistic forecasting of wind power based on multi-band width kernel density estimation[J]. High voltage engineering, 2024, 50(7): 3070-3079.
[24] DEON A F, MENYAEV Y A.Twister generator of random normal numbers by box-muller model[J]. Journal of computer science, 2020, 16(1): 1-13.
[25] 董厚琦, 曾博, 吴晨, 等. 利用需求侧资源降低配电网脆弱性的优化方法研究[J]. 太阳能学报, 2022, 43(2): 120-126.
DONG H Q, ZENG B, WU C, et al.Optimization method for mitigating vulnerability of distribution network based on demand-side resources[J]. Acta energiae solaris sinica, 2022, 43(2): 120-126.
[26] 张建文, 刘国亮, 刘铭洋. 风电提供柔性爬坡容量的电力系统优化调度[J]. 太阳能学报, 2021, 42(8): 414-420.
ZHANG J W, LIU G L, LIU M Y.Optimal dispatch of power system with wind power providing flexible ramping capacity[J]. Acta energiae solaris sinica, 2021, 42(8): 414-420.
[27] WANG Y, YANG Z F, YU J, et al.Revisit the electricity price formulation: a formal definition, proofs, and examples[J]. Energy, 2020, 200: 117542.
[28] 严晓生, 刘仲稳, 赵建红, 等. 混合储能辅助火电机组一次调频及其容量配置[J]. 太阳能学报, 2024, 45(11): 647-654.
YAN X S, LIU Z W, ZHAO J H, et al.Primary frequency regulation and capacity configuration of hybrid energy storage auxiliary thermal power unit[J]. Acta energiae solaris sinica, 2024, 45(11): 647-654.
[29] 蒋静. 考虑新能源消纳的辅助服务成本分摊新机制研究[D]. 南京: 东南大学, 2020.
JIANG J.Research on the new allocation mechanism of auxiliary service cost considering the consumption of renewable energy[D]. Nanjing: Southeast University, 2020.