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Interval prediction algorithm and optimal scenario making model for wind power producers bidding strategy
Optimization and Engineering ( IF 2.1 ) Pub Date : 2021-03-24 , DOI: 10.1007/s11081-021-09610-6
Azim Heydari , Gholamreza Memarzadeh , Davide Astiaso Garcia , Farshid Keynia , Livio De Santoli

Nowadays, renewable energies are important sources for supplying electric power demand and a key entity of future energy markets. Therefore, wind power producers (WPPs) in most of the power systems in the world have a key role. On the other hand, the wind speed uncertainty makes WPPs deferent power generators, which in turn causes adequate bidding strategies, that leads to market rules, and the functional abilities of the turbines to penetrate the market. In this paper, a new bidding strategy has been proposed based on optimal scenario making for WPPs in a competitive power market. As known, the WPP generation is uncertain, and different scenarios must be created for wind power production. Therefore, a prediction intervals method has been improved in making scenarios and increase the accuracy of the presence of WPPs in the balancing market. Besides, a new optimization algorithm has been proposed called the grasshopper optimization algorithm to simulate the optimal bidding problem of WPPs. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of the proposed method.



中文翻译:

风力发电企业竞价策略的区间预测算法与最优情景决策模型

如今,可再生能源已成为满足电力需求的重要来源,并且是未来能源市场的重要组成部分。因此,世界上大多数电力系统中的风力发电者(WPP)都扮演着关键角色。另一方面,风速的不确定性使WPP成为不同的发电机,这反过来又导致了适当的投标策略,从而导致了市场规则以及涡轮机渗透市场的功能。本文在竞争激烈的电力市场中,基于最优方案制定了一种新的竞标策略。众所周知,WPP的产生是不确定的,必须为风力发电创建不同的方案。因此,在间隔场景中改进了预测间隔方法,并增加了WPP在平衡市场中的准确性。此外,提出了一种新的优化算法,称为蚱hopper优化算法,以模拟WPP的最优竞标问题。一组数值示例以及基于实际数据的案例研究可以说明和讨论所提出方法的性质。

更新日期:2021-03-24
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