Day-ahead joint market operation strategy of grid-connected wind farms with flexible allowable generation deviation rates

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
Tianhui Meng, Jilai Yu, Yufeng Guo
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引用次数: 0

Abstract

The uncertainty of wind power output affects the efficient operation of the electricity spot market and has become a key factor restricting the participation of wind farms in the market. To this end, this paper proposes a day-ahead joint market operation strategy that considers allowable deviation rates of wind power output. Unlike traditional electricity markets which impose uniform deviation requirements on all wind farms, the main grid side provides a more diverse range of selectable deviation rates. The bidding strategy for wind farms in the joint day-ahead and balancing markets is explored, allowing them to independently select deviation rates and submit schedule curves and offer prices. A joint clearing model for the day-ahead energy-reserve and balancing market is established, incorporating the carbon emission trading costs of thermal power units, with the aim of minimizing the system operating cost. Numerical results indicate that compared with the traditional market participation method, the proposed strategy not only encourages wind farms to improve output accuracy, but also reflects the market economic principle of high quality and high price. Meanwhile, integrating carbon emission trading costs into the model helps to reduce carbon emissions while ensuring the economic operation of the system.
具有柔性允许发电偏差率的并网风电场日前联合市场运行策略
风电输出的不确定性影响着电力现货市场的高效运行,成为制约风电场参与市场的关键因素。为此,本文提出了考虑风电出力允许偏差率的日前联合市场运行策略。与传统电力市场对所有风电场施加统一的偏差要求不同,主电网方面提供了更多样化的可选择偏差率范围。探讨了风电场在日前平衡联合市场下自主选择偏离率、提交进度曲线和报价的竞价策略。以系统运行成本最小为目标,建立了纳入火电机组碳排放交易成本的日前储能平衡市场联合清算模型。数值结果表明,与传统的市场参与方法相比,所提出的策略不仅鼓励风电场提高输出精度,而且体现了高质量、高价格的市场经济原则。同时,将碳排放交易成本纳入模型,有助于在保证系统经济运行的同时减少碳排放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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