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Wind power bidding strategy in the short-term electricity market

机译:短期电力市场中的风电竞标策略

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摘要

This paper presents an analytical trading electricity model for wind power producers (WPPs) in the short-term electricity market in the U.S. This model addresses four specific uncertainties: real-time (RT) wind power generation, day-ahead (DA) locational marginal prices (LMPs), RT LMPs, and deviation penalty rates. The model is designed to find the optimal bidding strategy to maximize the expected revenue under these uncertainties. In addition, this paper shows that advanced forecasting techniques could be used with the proposed bidding strategy to help WPPs trade energy in short-term markets. A case study is presented to illustrate the effectiveness of this proposed bidding strategy and advanced forecasting techniques using a set of real data taken from a wind farm in the PJM electricity market. (C) 2018 Elsevier B.V. All rights reserved.
机译:本文提出了一种针对美国短期电力市场中的风能生产者(WPP)的分析性交易用电模型。该模型解决了四个特定的不确定性:实时(RT)风力发电,提前(DA)位置边际价格(LMP),RT LMP和偏差罚款率。该模型旨在查找在这些不确定性条件下可以最大化预期收入的最佳出价策略。此外,本文表明,先进的预测技术可以与提议的出价策略结合使用,以帮助WPP在短期市场上进行能源交易。提出了一个案例研究,以使用从PJM电力市场的风电场获取的一组真实数据来说明此提议的投标策略和高级预测技术的有效性。 (C)2018 Elsevier B.V.保留所有权利。

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