Bidding Decision-making Method of Wind Power-Energy Storage Integrated Station Based on Residual Demand Curve

ZHAO Zongzheng; LIU Yixin; GUO Li; WANG Chengshan

doi:10.7500/AEPS20220421004

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Bidding Decision-making Method of Wind Power-Energy Storage Integrated Station Based on Residual Demand Curve

Basic Research | 更新时间：2025-06-16

- Bidding Decision-making Method of Wind Power-Energy Storage Integrated Station Based on Residual Demand Curve
- Automation of Electric Power Systems Vol. 47, Issue 8, Pages: 99-108(2023)
- 作者机构：
  
  智能电网教育部重点实验室（天津大学），天津市 300072
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2020YFE0200400);National Nature Science Foundation of China(51907140)
- DOI：10.7500/AEPS20220421004
  CLC：
- Received：21 April 2022，
  
  Revised：2022-12-14，
  
  Published Online：24 February 2023，
  
  Published：25 April 2023
- 稿件说明：
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赵宗政,刘一欣,郭力等.基于剩余需求曲线的风电-储能一体化电站投标决策方法[J].电力系统自动化,2023,47(8):99-108.

ZHAO Zongzheng,LIU Yixin,GUO Li,et al.Bidding Decision-making Method of Wind Power-Energy Storage Integrated Station Based on Residual Demand Curve[J].Automation of Electric Power Systems,2023,47(8):99-108.
赵宗政,刘一欣,郭力等.基于剩余需求曲线的风电-储能一体化电站投标决策方法[J].电力系统自动化,2023,47(8):99-108. DOI： 10.7500/AEPS20220421004.

ZHAO Zongzheng,LIU Yixin,GUO Li,et al.Bidding Decision-making Method of Wind Power-Energy Storage Integrated Station Based on Residual Demand Curve[J].Automation of Electric Power Systems,2023,47(8):99-108. DOI： 10.7500/AEPS20220421004.

摘要

针对风电-储能一体化电站（简称风储电站）在日前电能量和备用市场中同时作为价格决定者的投标问题，提出了一种基于剩余需求曲线的电量-备用联合投标决策方法。首先，考虑储能系统运行约束以及电能量-备用市场的耦合关系，在风储电站日前投标范围内生成电量-备用的可行投标组合，基于神经网络预测计算对应的市场出清电价，提出了电能量和备用市场中剩余需求曲线的联合建模方法。然后，建立了用于开展日前电量-备用联合投标的随机优化决策模型，以风储电站收益期望最大为目标调整储能系统的日前出力计划和备用容量，同时考虑实时市场的不确定性，通过调用储能系统的备用容量降低风储电站的实时偏差惩罚。最后，通过算例仿真验证了所提投标决策方法的有效性。

Abstract

Aiming at the bidding problem of wind power-energy storage integrated stations (referred to as wind-storage station) serving as an price-maker in the day-ahead energy market and reserve market

an electric quantity-reserve joint bidding decision-making method based on residual demand curve is proposed. Firstly

the feasible electric quantity-reserve bidding pairs are generated within the scope of day-ahead bidding of the wind-storage station

considering the operation constraints of the energy storage system as well as the coupling relationship between the electric quantity and the reserve market. The corresponding market clearing price is forecasted and calculated based on neural network. The joint modelling method of residual demand curve is proposed for the electric quantity and reserve market. Secondly

a stochastic optimization decision-making model is established for joint bidding in both day-ahead electric quantity and reserve. The day-ahead output power schemes and reserve capacity of the energy storage system are adjusted with the goal of maximizing the income expectation of the wind-storage station. At the same time

the real-time deviation penalty of wind-storage station can be reduced by dispatching the reserve capacity of the energy storage system while considering the uncertainty of the real-time market. Finally

the effectiveness of the proposed bidding decision-making method is verified by numerical simulation.

关键词

Keywords

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