可再生能源配额制下风光储联合参与现货市场的交易决策

doi:10.11930/j.issn.1004-9649.202306053

摘要/Abstract

摘要：

可再生能源配额制与现货市场建设的并行推进引起风电发电商、光伏发电商及储能电站（风光储）联合参与现货市场的交易决策发生变化。通过构建双层交易决策模型，对可再生能源配额制下风光储联合参与日前电能量及调频辅助服务市场的交易决策进行求解分析。模型上层以风光储总利润最大化为目标，同时考虑到风光储的内部调控，求解风光储最优交易策略；下层实现日前电能量和调频辅助服务市场的联合出清及绿色证书市场的清算。通过库恩-塔克（Karush-Kuhn-Tucker，KKT）条件、强对偶定理等方法将双层模型转换为混合整数线性规划问题进行求解。最后，通过算例验证了所提模型的有效性。结果表明：所提框架与模型能够优化风光储报量报价决策；可再生能源配额制的引入丰富了风光储的套利手段，风光储内部调控更加活跃；风光渗透率及配额制考核权重的变化对风光储的交易决策有重要影响。

关键词: 风光储, 可再生能源配额制, 电能量市场, 调频辅助服务市场, 双层交易决策模型

Abstract:

The parallel promotion of renewable portfolio standards (RPSs) and spot market construction leads to changes in the transaction decisions of wind power producers, photovoltaic producers, and energy storage power stations jointly participating in the spot market. This paper constructs a bi-level transaction decision-making model to solve and analyze the transaction decisions of wind/photovoltaic/energy storage jointly participating in the day-ahead energy and frequency modulation auxiliary service markets under RPSs. The upper level of the model solves the optimal transaction strategy of wind/photovoltaic/energy storage with the goal of maximizing the overall profit by considering the modulation within wind/photovoltaic/energy storage. The lower level realizes the joint clearing of the day-ahead energy and frequency modulation auxiliary service markets and the clearing of the green certificate market. Then, by using Karush-Kuhn-Tucker (KKT) conditions, the strong duality theorem, and other methods, the bi-level model is recast into a mixed-integer linear programming problem to be solved. Finally, an example is given to verify the effectiveness of the proposed model. The results show that the proposed framework and model in this paper can optimize the bidding strategies of wind/photovoltaic/energy storage. The introduction of the RPSs enriches the arbitrage means of wind/photovoltaic/energy storage, and the modulation within wind/photovoltaic/energy storage is more active. The changes of wind/photovoltaic penetration level and ratio of RPSs have an important influence on the transaction decisions of wind/photovoltaic/energy storage.

Key words: wind/photovoltaic/energy storage, renewable portfolio standards, energy market, frequency modulation auxiliary service market, bi-level transaction decision-making model

武群丽, 朱新宇. 可再生能源配额制下风光储联合参与现货市场的交易决策[J]. 中国电力, 2024, 57(4): 77-88.

Qunli WU, Xinyu ZHU. Transaction Decision-Making of Wind/Photovoltaic/Energy Storage Joint Participation in Spot Market under Renewable Portfolio Standards[J]. Electric Power, 2024, 57(4): 77-88.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202306053

https://www.electricpower.com.cn/CN/Y2024/V57/I4/77

图/表 13

图 1 风光储参与联合市场交易的框架

Fig.1 Framework of wind/photovoltaic/energy storage participating in transaction of joint markets

图 2 双层交易决策模型

Fig.2 Bi-level transaction decision-making model

图 3 颁发给储能的绿证求解流程

Fig.3 Solution process of green certificates issued to energy storage

图 4 绿证供给和需求曲线

Fig.4 Supply and demand curves of green certificates

表 1 常规机组申报信息

Table 1 Bidding information of conventional units

机组	额定功率/ MW	发电报价/ (元·(MW·h)^–1)	调频容量/ MW	调频容量报价/ (元·(MW·h)^–1)	调频里程报价/ (元·(MW·h)^–1)	里程- 容量比
G1	300	191	22	12	15	9
G2	150	190	0	—	—	—
G3	300	177	20	13	16	12
G4	160	165	16	16	18	12
G5	300	150	0	—	—	—
G6	200	185	24	15	14	11

图 5 典型日风光出力曲线及负荷曲线

Fig.5 Wind power output curve, photovoltaic output curve, and load curve on a typical day

图 6 SM及STM场景下市场负荷及储能剩余容量的变化曲线

Fig.6 Variation curves of market load and energy storage residual capacity under SM and STM scenarios

图 7 SM及STM场景下风光充电量及储能充放电量

Fig.7 Amount of wind/photovoltaic charge and energy storage charge/discharge under SM and STM scenarios

图 8 SM及STM场景下电能量市场中标情况

Fig.8 Bidding results in energy market under SM and STM scenarios

图 9 SM与STM场景下调频辅助服务市场中标比例情况

Fig.9 Bidding ratio in frequency modulation auxiliary service market under SM and STM scenarios

图 10 各风光渗透率及RPS考核权重下风光充电量及储能充放电量

Fig.10 Amount of wind/photovoltaic charge and energy storage charge/discharge under different wind/photovoltaic penetration levels and RPS ratios

图 11 各风光渗透率及RPS考核权重下电能量市场中标情况

Fig.11 Bidding results in energy market under different wind/photovoltaic penetration levels and RPS ratios

图 12 各风光渗透率及RPS考核权重下调频辅助服务市场中标情况

Fig.12 Bidding results in frequency modulation auxiliary service market under different wind/photovoltaic penetration levels and RPS ratios

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