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A novel online kernel ridge to forecast next-day electricity price

机译:一部小说在线内核山脊预测下一天电价

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摘要

Accurate prediction for electricity price plays a great role in developing bidding strategy in the competitive energy market. In this brief, a novel variant of kernel ridge, namely multivariate slide-window online kernel ridge, is proposed to capture the nonlinearity and non-stationarity of electricity price as seasonal time series, by handling the timestamps in one period synchronously. Compared to traditional time series techniques like autoregressive integrated moving average (ARIMA) and other techniques like random forest and support vector regression, it provides much higher accuracy with lower computation cost, and can be easily integrated with other related data. Results from EPEX France spot market are presented.
机译:准确的电价预测在竞争能源市场中培养招标策略方面发挥着重要作用。 在此简述中,提出了一种新颖的内核变体,即多变量幻灯片窗口在线核脊,通过在一个时期同步地处理时间戳来捕获作为季节性时间序列的电价的非线性和非公平性。 与传统的时间序列技术相比,如自回归综合移动平均(Arima)和其他技术,如随机森林和支持向量回归,它提供了更高的计算成本的准确性,并且可以与其他相关数据轻松集成。 举行了ePEx法国现货市场的结果。

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