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浙江大学学报(工学版)
浙江大学学报(工学版)  2025, Vol. 59 Issue (9): 1891-1901    DOI: 10.3785/j.issn.1008-973X.2025.09.013
电气工程     
考虑储能提供灵活爬坡产品的日前市场经济调度
邢海军1(),俞钱1,成明洋2,郭啟振1,黄程浩1
1. 上海电力大学 电气工程学院，上海 200090
2. 国网江苏省电力有限公司 连云港供电公司，江苏 连云港 222000
Day-ahead market economic dispatch considering energy storage providing flexible ramping products
Haijun XING1(),Qian YU1,Mingyang CHENG2,Qizhen GUO1,Chenghao HUANG1
1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
2. Lianyungang Power Supply Company, State Grid Jiangsu Electric Power Co. Ltd, Lianyungang 222000, China
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摘要：

针对新型电力系统建设背景下常规火电机组不能满足系统灵活性需求的问题，为了充分挖掘各资源的灵活调节能力，保障系统实时灵活性，提出考虑储能提供灵活爬坡产品（FRPs）的日前市场经济调度模型. 介绍FRPs的需求构成和机会成本计算方法；通过对日前市场和实时市场的FRPs决策方案进行概率分析，得到FRPs在日前和实时市场参与灵活爬坡部署的决策树模型，在FRPs充足和短缺的情况下进行成本和收益分析. 在此基础上建立考虑储能提供FRPs的日前市场经济调度模型，并在日前市场进行经济调度后，根据FRPs的日前市场接受概率和实时市场预期部署概率来实现成本和FRPs收益结算. 通过改进的IEEE 30节点进行算例分析，验证了储能参与下该模型的优越性，并探讨了日前市场接受概率和实时市场预期部署概率对系统的影响.
关键词： 灵活爬坡产品;  储能;  日前市场接受概率;  实时市场部署概率;  决策树    
Abstract:

A day-ahead market economic dispatch model that incorporated the flexible ramping products (FRPs) provided by energy storage systems was proposed to fully harness the flexible regulatory capabilities of various resources to ensure real-time flexibility, thereby addressing the problem that conventional thermal power units cannot meet the power system’s flexibility demands against the backdrop of the construction of a new type of power system. The demand composition and the opportunity cost of FRPs were introduced. A decision tree model for FRPs participation in flexible ramping deployment in the day-ahead and real-time markets was obtained by conducting the probabilistic analysis of the decision-making schemes for FRPs in both the day-ahead and real-time markets, and the cost and revenue analyses were performed under the scenarios where FRPs are either abundant or scarce. Based on this, a day-ahead market economic dispatch model that considered energy storage providing FRPs was established. After the economic dispatch in the day-ahead market, the cost and FRPs revenue settlement was achieved based on the probability of accepting FRPs in the day-ahead market and the expected deployment probability in the real-time market. A case study analysis using an improved IEEE 30-bus system was conducted to validate the superiority of the model with energy storage participation, and the impact of the acceptance probability in the day-ahead market and the expected deployment probability in the real-time market on the system was discussed.
Key words: flexible ramping products    energy storage    day-ahead market acceptance probability    real-time market deployment probability    decision tree
收稿日期: 2024-12-24 出版日期: 2025-08-25
CLC:  TP 393  
基金资助: 国家自然科学基金资助项目(52477106).
作者简介: 邢海军（1979—），男，讲师，博士，从事电力市场、综合能源研究. orcid.org/0000-0002-8056-6842. E-mail：xinghj@shiep.edu.cn
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引用本文:

邢海军,俞钱,成明洋,郭啟振,黄程浩. 考虑储能提供灵活爬坡产品的日前市场经济调度[J]. 浙江大学学报(工学版), 2025, 59(9): 1891-1901.

Haijun XING,Qian YU,Mingyang CHENG,Qizhen GUO,Chenghao HUANG. Day-ahead market economic dispatch considering energy storage providing flexible ramping products. Journal of ZheJiang University (Engineering Science), 2025, 59(9): 1891-1901.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2025.09.013    或    https://www.zjujournals.com/eng/CN/Y2025/V59/I9/1891

图 1  考虑调节能力的电力系统爬坡需求
机组$\lambda^{\mathrm{G}} /\left(\$ \cdot \mathrm{MW}^{-1} \cdot \mathrm{h}^{-1}\right)$$ {R}_{\text{up}}^{\text{G}}/{\mathrm{MW}} $$ {C}_{\text{op}}^{\text{G}} /\left(\$ \cdot \mathrm{MW}^{-1} \cdot \mathrm{h}^{-1}\right)$
G120200
G218202
G316104
G412108
G5101010
G62510—
表 1  FRPs机会成本与电能量市场报价的关系
图 2  FRPs机会成本和爬坡需求的关系
图 3  FRPs参与日前和实时市场的决策树
图 4  FRPs参与市场结算的成本和收益
图 5  改进的IEEE 30节点系统结构图
机组$ P_{i,\max }^{{\mathrm{G}}} $/
MW		$ P_{i,\min }^{{\mathrm{G}}} $/
MW		$ {R}_{i}^{\text{G}\text{ }} $/
(MW·h?1)		$ {\lambda }_{i}^{\text{G}} $/
($·MW?1)		$t_{{\text{on}}}^{\min }/{\mathrm{h}}$$t_{{\text{off}}}^{\min }/{\mathrm{h}}$$t_{\text{run}}^{\;}/{\mathrm{h}}$
G12001002516101010
G2100403020888
G38040202466?6
G440203026444
G550202028333
G62010403011?1
表 2  火电机组参数
图 6  日前风电出力和实时风电出力预测结果
图 7  日前负荷和实时负荷预测结果
图 8  日前市场和实时市场电价
场景$ C $/(104 $)$ {C_{{\text{FRPs}}}} $/(104 $)$ {R_{{\text{FRPs}}}} $/(104 $)$ {C_{\text{p}}} $/(104 $)
119.410.000.004.57
216.041.251.781.79
314.561.412.540.45
表 3  不同场景下的系统运行成本对比
图 9  场景2中储能出力分析
图 10  场景3中储能出力分析
图 11  FRPs在日前市场的上调和下调中标容量
$ \alpha $$ P_{{{\mathrm{up}}}}^{{\mathrm{G}}}/{\text{MW}} $$ P_{{\text{dn}}}^{{\mathrm{G}}}/{\text{MW}} $$ P_{{\text{up}}}^{{{\mathrm{E}}}{\text{d}}}/{\text{MW}} $$ P_{{\text{dn}}}^{{{\mathrm{E}}}{\text{c}}}/{\text{MW}} $$ {P_{{\text{up}}}}/{\text{MW}} $$ {P_{{\text{dn}}}}/{\text{MW}} $
0.00.00.00.00.00.00.0
0.133.546.511.60.045.146.5
0.265.693.124.70.090.393.1
0.399.0125.636.212.2135.2138.2
0.4130.5151.050.635.0181.1186.0
0.5154.1176.971.555.8225.6232.8
0.6179.2213.890.165.4270.1279.2
0.7195.7244.6120.182.2315.8325.8
0.8202.1264.5158.0107.8360.1372.3
0.9197.6264.5208.4154.4406.0418.9
1.0184.5264.5266.7200.5451.2465.0
表 4  日前市场接受概率与容量之间的关系
图 12  日前市场接受概率对成本的影响
图 13  实时市场预期部署概率对成本和收益的影响
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