Optimal Daily Trading of Battery Operations Using Arbitrage Spreads
Optimal Daily Trading of Battery Operations Using Arbitrage Spreads
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DOI：
10.3390/en14164931
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发表时间：
2021-08
期刊：
影响因子：
3.2
通讯作者：
E. Abramova;D. Bunn
中科院分区：
文献类型：
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作者：
E. Abramova;D. Bunn
对于电池运营商来说，一个重要的收入来源往往是在前一天的拍卖中套利每小时的价差。如果考虑风险，那么最优的方法是具有挑战性的，因为这需要估计密度函数。由于每小时的价格不是正常的，也不是独立的，根据单独估计的价格密度的差异来创建价差密度通常是困难的。因此，所有日内每小时价差的预测都被直接指定为包含密度的上三角矩阵。该模型是一种灵活的四参数分布，用于根据外部因素(最重要的是风能、太阳能和提前一天的需求预测)产生动态参数估计。这些预测支持存储设施的最优每日调度，每天以单周期和多周期运行。这种优化在使用价差交易而不是小时价格方面是创新的，本文认为，后者在降低风险方面更具吸引力。与传统的交易每日峰值和低谷的方法不同，根据天气预报，多笔交易被发现是有利可图的，也是机会主义的。
An important revenue stream for electric battery operators is often arbitraging the hourly price spreads in the day-ahead auction. The optimal approach to this is challenging if risk is a consideration as this requires the estimation of density functions. Since the hourly prices are not normal and not independent, creating spread densities from the difference of separately estimated price densities is generally intractable. Thus, forecasts of all intraday hourly spreads were directly specified as an upper triangular matrix containing densities. The model was a flexible four-parameter distribution used to produce dynamic parameter estimates conditional upon exogenous factors, most importantly wind, solar and the day-ahead demand forecasts. These forecasts supported the optimal daily scheduling of a storage facility, operating on single and multiple cycles per day. The optimization is innovative in its use of spread trades rather than hourly prices, which this paper argues, is more attractive in reducing risk. In contrast to the conventional approach of trading the daily peak and trough, multiple trades are found to be profitable and opportunistic depending upon the weather forecasts.