吴莹,王觉非,李俊杰,王坤,沈妍,吴英俊
WU Ying,WANG Juefei,LI Junjie,WANG Kun,SHEN Yan,WU Yingjun

• 1:国网浙江省电力有限公司经济技术研究院
• 2:河海大学电气与动力工程学院

摘要(Abstract)：

参与中长期调度运行的水电站如何评估并应对径流与电价带来的风险是亟待解决的问题。为此，提出一种兼顾最大化预期净收益与降低中长期运行风险的水电站调度模型。首先，基于CVaR（条件风险价值）理论，利用边缘分布函数描述径流不确定性风险与电价波动风险，对市场化运营的水电站做出准确的风险评估。其次，基于LSCV（最小平方交叉验证法）思想确定核密度估计过程中的最佳带宽参数以确保对离散径流与电价数据的拟合优度。然后，采用Copula-Monte Carlo模拟方法对径流与电价联合风险项进行建模，并采用拉丁超立方采样方法提高模型计算精度。最后，通过算例仿真分析，验证了所提出模型的有效性。
Evaluating and addressing the risks posed by runoff and electricity prices in hydropower plants involved in medium-to long-term scheduling is a pressing issue. To address this, a scheduling model is proposed that aims to maximize expected net revenue while minimizing medium-to long-term operational risks. First, using the conditional value at risk(CVaR) theory, marginal distribution functions are utilized to characterize the risks of runoff uncertainty and electricity price volatility(EPV), enabling accurate risk assessment for market-operated hydropower plants. Second, the least-squares cross validation(LSCV) is applied to determine the optimal bandwidth parameter in kernel density estimation(KDE), ensuring a good fit for discrete runoff and electricity price data. Next, a Copula-Monte Carlo simulation method is used to model the joint risks of runoff and electricity prices, with Latin hypercube sampling(LHS) employed to enhance computational precision. Finally, case simulation and analysis are conducted to validate the effectiveness of the proposed model.

关键词(KeyWords)： 水电站;优化调度;径流;条件风险价值;核密度估计
hydropower plant;optimal scheduling;runoff;CVaR;KDE

Abstract:

Keywords:

基金项目(Foundation): 江苏省自然科学基金（BK20221165）;; 国网浙江省电力有限公司经济技术研究院专项项目（SGZJJY00JJJS2310243）

作者(Author): 吴莹,王觉非,李俊杰,王坤,沈妍,吴英俊
WU Ying,WANG Juefei,LI Junjie,WANG Kun,SHEN Yan,WU Yingjun

DOI: 10.19585/j.zjdl.202501003

参考文献(References)：

• [1]王明博，李刚，李亚鹏，等.计及不同交易方式的梯级水电站的中长期合约电量分解方法[J/OL].中国电机工程学报，1-12[2024-05-10]. https：//doi. org/10.13334/j.0258-8013.pcsee.231972.WANG Mingbo,LI Gang,LI Yapeng,et al.Decomposition method for medium and long-term contract of cascaded hydropower taking into account multi trading modes[J].Proceedings of the CSEE:1-12.[2024-05-10].https：//doi.org/10.13334/j.0258-8013.pcsee.231972.
• [2]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.
• [3] LIU B X,LIAO S L,CHENG C T,et al. Hydropower curtailment in Yunnan Province,southWestern China:constraint analysis and suggestions[J]. Renewable Energy,2018,121:700-711.
• [4] TORABI HAGHIGHI A,BIN ASHRAF F,RIML J,et al.A power market-based operation support model for subdaily hydropower regulation practices[J].Applied Energy,2019,255:113905.
• [5]刘方，张粒子.流域梯级水电站中长期调度与跨价区交易组合双层优化模型[J].中国电机工程学报，2018,38(2):444-455.LIU Fang,ZHANG Lizi. Bi-level optimization model for medium and long-term scheduling and cross-price area trading portfolio of cascade hydropower stations[J]. Proceedings of the CSEE,2018,38(2):444-455.
• [6]李亚鹏，赵麟，王祥祯，等.不确定碳-电耦合市场下梯级水电双层竞价模型[J].电力系统自动化，2023,47(20):83-94.LI Yapeng,ZHAO Lin,WANG Xiangzhen,et al.Bi-level bidding model for cascaded hydropower under uncertain carbon-electricity coupled market[J].Automation of Electric Power Systems,2023,47(20):83-94.
• [7]刘方，张粒子.计及随机和风险因素的梯级水电调度交易优化模型和方法[J].电网技术，2018,42(3):870-878.LIU Fang,ZHANG Lizi.Optimization model and method of cascade hydropower scheduling transaction considering stochastic and risk factors[J].Power System Technology,2018,42(3):870-878.
• [8] ALGARVIO H,LOPES F,SOUSA J,et al.Multi-agent electricity markets:retailer portfolio optimization using Markowitz theory[J].Electric Power Systems Research,2017,148:282-294.
• [9]王俊，徐箭，王晶晶，等.基于条件风险价值的虚拟电厂参与能量及备用市场的双层随机优化[J].电网技术，2024,48(6):2502-2510.WANG Jun,XU Jian,WANG Jingjing,et al.Bi-level stochastic optimization for a virtual power plant participating in energy and reserve market based on conditional value At risk[J].Power System Technology,2024,48(6):2502-2510.
• [10]姚艳，康家乐，汪雅静，等.考虑综合需求响应和多能储能装置的综合能源系统优化调度[J].浙江电力，2022,41(8):65-72.YAO Yan,KANG Jiale,WANG Yajing,et al. Optimal dispatching of integrated energy system considering integrated demand response and multi-energy storage devices[J].Zhejiang Electric Power,2022,41(8):65-72.
• [11]刘军，李凌阳，吴梦凯，等.分布式抽水蓄能电站与新能源发电联合参与现货市场的两阶段优化运行策略[J].浙江电力，2023,42(2):50-58.LIU Jun,LI Lingyang,WU Mengkai,et al. A two-stage optimal operation strategy of distributed pumped storage power plant and new energy power generation jointly participating in spot market[J]. Zhejiang Electric Power,2023,42(2):50-58.
• [12]唐力，刘继春，杨阳方，等.基于信息间隙决策理论的多种零售合同模式下售电公司购售电策略[J].电网技术，2019,43(6):1978-1988.TANG Li,LIU Jichun,YANG Yangfang,et al.Study on strategies of electricity procurement and sale of power retailer with multiple retail contract modes based on information gap decision theory[J]. Power System Technology,2019,43(6):1978-1988
• [13]徐家良，李晓露，柳劲松，等.考虑多重不确定性的综合能源系统与充电站的鲁棒定价策略[J/OL].现代电力，1-13[2024-05-31]. https：//doi. org/10.19725/j. cnki. 1007-2322.2023.0127.XU Jialiang,LI Xiaolu,LIU Jinsong,et al.Robust pricing strategies for integrated energy systems and charging stations considering multiple uncertainties[J]. Modern Electric Power,1-13[2024-05-31].https：//doi.org/10.19725/j.cnki.1007-2322.2023.0127.
• [14] GE X L,ZHANG L Z,SHU J,et al. Short-term hydropower optimal scheduling considering the optimization of water time delay[J]. Electric Power Systems Research,2014,110:188-197.
• [15]沈佳程，李梦诗，季天瑶，等.基于多层级条件风险价值的高渗透可再生能源电力系统低碳运行联合优化[J].电网与清洁能源，2024,40(2):37-46.SHEN Jiacheng,LI Mengshi,JI Tianyao,et al.Joint optimization for low-carbon operation of high-penetration renewable energy system based on multi-layer conditional value-at-risk[J].Power System and Clean Energy,2024,40(2):37-46.
• [16]陈雨佳，裴玮，马腾飞，等.考虑条件风险价值的分布式发电与用户间点对点交易非对称纳什谈判模型[J/OL].现代电力，1-13[2024-06-10]. https：//doi. org/10.19725/j.cnki.1007-2322.2023.0065.CHEN Yujia,PEI Wei,MA Tengfei,et al. Asymmetric nash bargaining model for P2P transactions between distributed generation and consumers considering conditional value-at-risk[J]. Modern Electric Power,1-13[2024-06-10]. https：//doi. org/10.19725/j. cnki. 1007-2322.2023.0065.
• [17] MOHAMMADKARIMI M,DOBRE O A.Blind identification of spatial multiplexing and alamouti space-time block code via Kolmogorov-Smirnov(K-S)test[J].IEEE Communications Letters,2014,18(10):1711-1714.
• [18]童坤，刘恒，耿雷华，等.基于核密度估计的AM-MCMC算法在径流模拟中的应用[J].长江科学院院报，2018,35(1):36-39.TONG Kun,LIU Heng,GENG Leihua,et al. AMMCMC algorithm for runoff simulation model based on kernel density estimation[J].Journal of Yangtze River Scientific Research Institute,2018,35(1):36-39.
• [19] LU J,LI G,CHENG C T,et al.A long-term intelligent operation and management model of cascade hydropower stations based on chance constrained programming under multi-market coupling[J]. Environmental Research Letters,2021,16(5):055034.