风电参与能量—调频联合市场的优化策略

CUI Da

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风电参与能量—调频联合市场的优化策略

更新时间：2025-08-13

- 风电参与能量—调频联合市场的优化策略
- Automation of Electric Power Systems Vol. 40, Issue 13, Pages: 5-12(2016)
- 作者机构：
  
  清华大学电机工程与应用电子技术系,北京市,100084
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
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CUI Da. [J]. Automation of electric power systems, 2016, 40(13): 5-12.
DOI：

CUI Da. [J]. Automation of electric power systems, 2016, 40(13): 5-12. DOI：

摘要

设计合理的市场机制

允许风电自行选择参与能量市场与调频市场

将有助于缓解系统调频压力

并提升风电自身收益。考虑调频资源的调频性能、按调频质量结算是调频市场的主要特征

而风电的调频性能指标受到其投标策略和风电出力的影响

是一个动态变化的参数。为此

文中开展了风电参与能量—调频联合市场的优化策略研究

提出了考虑调频性能指标与偏差惩罚机制的能量—调频联合市场机制。对风电的调频性能指标进行了建模分析

提出了调频性能指标的估值方法

建立了所提出市场机制下的风电最大收益模型

并给出了求解风电参与能量—调频联合市场的最优投标策略的方法。算例分析表明

调频性能收益是激励风电调频的重要因素

而在投标决策中精确地对调频性能指标进行动态估值

将有助于提升风电的预期收益。

Abstract

Designing rational market mechanisms and allowing wind power to bid in energy and frequency regulation markets will relieve the frequency regulation pressure of the system and increase the market revenue of wind power. The performance of regulation resources and the “paid-by-performance” mechanism are the key features of the frequency regulation market. Meanwhile

the frequency regulation performance index(FRPI)of wind power is dynamically determined by its bidding strategy and output. Therefore

this paper studies the optimal strategy for wind power bidding in energy and frequency regulation markets. Moreover

a market mechanism taking FRPI and the deviation penalty into account is proposed. Then an evaluation approach is developed for modelling FRPI of wind power. The maximum revenue model under the proposed market mechanism is developed. The solving method of the optimal strategy for wind power bidding in energy and frequency regulation markets is given. The case study results reveal that the frequency regulation performance revenue is important to incent the wind power to provide frequency regulation service

and precisely estimating regulation performance index in bidding decision-making is good for the expected revenue of wind power to be increased. This work is supported by National Natural Science Foundation of China(No. 51537005)and State Grid Corporation of China(No. 5201011400LV).

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Related Institution

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