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中国工业与应用数学学会会刊
主管:中华人民共和国教育部
主办:西安交通大学
ISSN 1005-3085  CN 61-1269/O1

工程数学学报 ›› 2024, Vol. 41 ›› Issue (5): 853-866.doi: 10.3969/j.issn.1005-3085.2024.05.005

• • 上一篇    下一篇

基于条件风险价值的风储系统储能容量优化配置研究

王  蒙1,    刘辰月2,   汪  莹1,   王  聪1,   张春霞3,   汪泓涛3   

  1. 1. 国家电网西北分部,西安 710048
    2. 南开大学金融学院,天津  300350
    3. 西安交通大学数学与统计学院,西安 710049
  • 收稿日期:2022-11-13 接受日期:2023-03-04 出版日期:2024-10-15
  • 基金资助:
    国家自然科学基金 (61976174).

Research on Optimal Allocation of Energy Storage Capacity of Wind Storage System Based on Conditional Value-at-risk

WANG Meng1,   LIU Chenyue2,   WANG Ying1,   WANG Cong1,   ZHANG Chunxia3,   WANG Hongtao3   

  1. 1. Northwest Branch of State Grid Corporation of China, Xi'an 710048
    2. School of Finance, Nankai University, Tianjin 300350
    3. School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049
  • Received:2022-11-13 Accepted:2023-03-04 Online:2024-10-15
  • Supported by:
    The National Natural Science Foundation of China (61976174).

摘要:

随着风能资源的广泛利用,风电场效率和安全性越来越得到人们的重视。运用统计学方法对风速的特性进行分析,可以掌握风能的变化规律,从而对电量进行合理的分配与调度,最大化降低损失和风险。目前,已有大量利用储能系统平抑风电场输出的相关文献,而将条件风险价值作为评价指标引入风能资源评估的研究较少。针对风速不稳定性及其所带来的风电场弃风限电量严重的问题,提出了在风电场并网处配置一定容量的储能装置,将系统的条件风险价值作为优化目标,利用储能装置对风电场进行充放电控制,从而实现平抑风功率大幅度波动、减少弃风限电的目的。通过实际算例分析了储能系统对风功率波动的平抑作用,量化结果和可视化结果表明该方法在风功率削峰填谷中具有重要作用。

关键词: 储能容量, 弃风限电, 条件风险价值, 粒子群算法

Abstract:

With the extensive utilization of wind energy resources, more and more attention has been paid to the efficiency and safety of wind penetration. Using statistical methods to analyze the characteristics of wind speed, we can know the change rule of wind energy, so as to make reasonable distribution and scheduling of electricity, and to maximize the reduction of losses and risks. At present, there are a large number of literatures on the use of energy storage system to suppress wind farm output, but there are few researches on the introduction of conditional VaR (Value-at-Risk) as an evaluation index into wind energy resource assessment. Aiming at sloving the instability of wind speed and the serious problem of wind curtailment and power limitation, this paper proposes to configure energy storage devices with a certain capacity at the grid-connected wind farms. In the proposed method, the conditional risk value of the system is taken as the optimization objective, and energy storage devices are adopted to control the charging and discharging of wind farms, so as to achieve the purpose of stabilizing wind power fluctuations and reducing wind curtailment. We analyze the calming effect of energy storage system on wind power fluctuation through real-world examples. The quantitative and visual results show that the proposed method is of great significance in wind power peaking and valley filling.

Key words: energy storage capacity, wind curtailment and power limitation, conditional value-at-risk, particle swarm optimization

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