Optimal Planning of Energy Storage for Wind Farm GENCO in Power Spot Market

2022 7th Asia Conference on Power and Electrical Engineering (ACPEE) Pub Date : 2022-04-01 DOI:10.1109/ACPEE53904.2022.9783634

Zhiyong Pu, Miao Wang, Hao Zheng, Zirui Liu

{"title":"Optimal Planning of Energy Storage for Wind Farm GENCO in Power Spot Market","authors":"Zhiyong Pu, Miao Wang, Hao Zheng, Zirui Liu","doi":"10.1109/ACPEE53904.2022.9783634","DOIUrl":null,"url":null,"abstract":"When large-scale of wind generation participate in power spot market, it is facing financial risk and curtailment challenge due to its volatility. Energy storage system (ESS) is one of the key means to enhance the controllability of wind generation. Planning of reasonable scale of ESS is important for wind farm GENCO to ensure the overall economic benefits. In the paper, a process for optimal planning of ESS for a wind farm GENCO in a power spot market is proposed. Day-ahead and real-time market price of a power spot market is predicted based on a production cost simulation model. And day-ahead and real-time power output of wind generation are established based on a probabilistic model using historical data. The optimal capacity and energy of ESS is obtained by using an optimization model that maximizes the combined economic benefits of the wind farm and ESS by reducing wind generation curtailment and the economic loss due to the forecast error in the spot market. A case study is performed based on actual power system data to optimize the ESS scale for a wind farm.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPEE53904.2022.9783634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

When large-scale of wind generation participate in power spot market, it is facing financial risk and curtailment challenge due to its volatility. Energy storage system (ESS) is one of the key means to enhance the controllability of wind generation. Planning of reasonable scale of ESS is important for wind farm GENCO to ensure the overall economic benefits. In the paper, a process for optimal planning of ESS for a wind farm GENCO in a power spot market is proposed. Day-ahead and real-time market price of a power spot market is predicted based on a production cost simulation model. And day-ahead and real-time power output of wind generation are established based on a probabilistic model using historical data. The optimal capacity and energy of ESS is obtained by using an optimization model that maximizes the combined economic benefits of the wind farm and ESS by reducing wind generation curtailment and the economic loss due to the forecast error in the spot market. A case study is performed based on actual power system data to optimize the ESS scale for a wind farm.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

电力现货市场下风电场发电公司储能优化规划

大规模风电参与电力现货市场时，由于其波动性，面临着财务风险和弃风挑战。储能系统是提高风力发电可控性的关键手段之一。规划合理的ESS规模对风电场发电公司保证整体经济效益具有重要意义。本文提出了一种电力现货市场条件下风电场发电机组ESS的优化规划方法。基于生产成本仿真模型，对电力现货市场的日前和实时市场价格进行了预测。利用历史数据建立概率模型，建立风力发电的日前实时输出功率。采用优化模型，通过减少弃风量和现货市场预测误差造成的经济损失，使风电场和ESS的综合经济效益最大化，从而获得ESS的最优容量和最优能量。基于实际电力系统数据进行了案例研究，以优化风力发电场的ESS规模。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)

自引率

0.00%

发文量