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Operation Strategy for Maximizing Revenue of an Energy Storage System With a Photovoltaic Power Plant Considering the Incentive for Forecast Accuracy in South Korea

机译:考虑到韩国预测准确性激励的光伏发电厂,最大限度地利用光伏电力储存系统的策略

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摘要

Adequate policies or incentives are needed to support investment in renewable energy industries. However, renewable power plant operators in South Korea may face the risk of finding it difficult to recoup their capital cost in the absence of a peak-biased incentive for the power plant with energy storage systems (ESS). Incentives for the forecast accuracy of the power plant will be adopted after the abolition of the incentive. This study explores the impact of incentives on power plant operations. In this study, we propose an ESS optimization model combined with a photovoltaic power plant. We design a coordinated model of the power plant to model the structures of revenues and costs based on actual power generation and a forecast error ratio. Optimization problems from the model are formulated as mixed integer linear programming to maximize revenue with the incentive for forecast accuracy. The revenue of the incentive is designed to reflect the unit price of the incentive, varying with the forecast error ratio. The effects of incentive adoption are evaluated in comparison with the absence of incentives.
机译:需要充分的政策或奖励来支持可再生能源产业的投资。然而,韩国的可再生能源厂家运营商可能面临难以在没有能量存储系统(ESS)的电厂的峰值偏见激励的情况下难以收回其资本成本的风险。在取消激励后,将采用电厂预测准确性的激励措施。本研究探讨了激励对电厂运营的影响。在这项研究中,我们提出了一种ESS优化模型与光伏电厂相结合。我们设计了电厂的协调模型,基于实际发电和预测误差比来模拟收入和成本的结构。模型的优化问题被制定为混合整数线性编程,以最大限度地提高预测准确性的激励。激励的收入旨在反映激励的单位价格,随着预测错误比而变化。与缺乏激励措施相比,评估了激励采用的影响。

著录项

  • 作者

    Woong Ko; Mun-Kyeom Kim;

  • 作者单位
  • 年度 2021
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  • 原文格式 PDF
  • 正文语种 eng
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