Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts

Antonio Giannitrapani, S. Paoletti, A. Vicino, Donato Zarrilli
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引用次数: 5

Abstract

In recent years, the interest in clean renewable energy resources, such as wind and photovoltaic, has grown rapidly. It is well known that the inherent variability in wind power generation and the related difficulty in predicting future generation profiles, raise major challenges to wind power integration into the electricity grid. In this work we study the problem of optimizing energy bids for an independent Wind Power Producer (WPP) taking part into a competitive electricity market. It is assumed that the WPP is subject to financial penalties for generation shortfall and surplus. This means that, if the energy delivered over a given time slot is different from that subscribed in the bid, the WPP will be penalized, the monetary entity of the penalty depending on the wholesale market behavior, the day of the year and the time slot involved. An optimization procedure is devised to minimize this risk and maximize the expected profit of the seller. Specifically, each energy bid is computed by exploiting the forecast energy price for the day ahead market, the historical wind statistics at the plant site and the day-ahead wind speed forecasts provided by a meteorological service. We also examine and quantify the strategic role of an energy storage device in increasing reliability of bids and mitigating the financial risks of the WPP.
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有气象预报的风力发电商最优投标策略
近年来,人们对风能和光伏等清洁可再生能源的兴趣迅速增长。众所周知,风力发电的内在可变性以及预测未来发电状况的相关困难,对风力发电并入电网提出了重大挑战。本文研究了独立风力发电商(WPP)参与竞争性电力市场时的能源报价优化问题。假设WPP会因发电不足和盈余而受到经济处罚。这意味着,如果在给定时间段内交付的能源与投标中订购的能源不同,WPP将受到处罚,处罚的货币实体取决于批发市场行为,一年中的哪一天以及所涉及的时间段。设计了一个优化程序,使这种风险最小化,并使卖方的预期利润最大化。具体来说,每个能源报价是通过利用前一天市场的预测能源价格、工厂现场的历史风力统计数据和气象机构提供的前一天风速预报来计算的。我们还研究并量化了储能设备在提高投标可靠性和减轻WPP财务风险方面的战略作用。
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