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Exponential smoothing approaches for prediction in real-time electricity markets

机译:用于实时电力市场预测的指数平滑方法

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摘要

The optimal design of offering strategies for wind power producers is commonly based on unconditional (and, hence, constant) expectation values for prices in real-time markets, directly defining their loss function in a stochastic optimization framework. This is why it may certainly be advantageous to account for the seasonal and dynamic behavior of such prices, hence translating to time-varying loss functions. With that objective in mind, forecasting approaches relying on simple models that accommodate the seasonal and dynamic nature of real-time prices are derived and analyzed. These are all based on the well-known Holt–Winters model with a daily seasonal cycle, either in its conventional form or conditioned upon exogenous variables, such as: (i) day-ahead price; (ii) system load; and(iii) wind power penetration. The superiority of the proposed approach over a number of common benchmarks is subsequently demonstrated through an empirical investigation for the Nord Pool, mimicking practical forecasting for a three-year period over 2008–2011.
机译:风电生产商提供策略的最佳设计通常基于实时市场价格的无条件(因此,是恒定的)期望值,并在随机优化框架中直接定义其损失函数。这就是为什么考虑此类价格的季节性和动态行为,从而转换为随时间变化的损失函数肯定会有利的原因。考虑到这一目标,得出并分析了基于简单模型的预测方法,这些模型适应了实时价格的季节性和动态性质。这些都是以众所周知的Holt-Winters模型为基础的,该模型具有常规季节性形式或以外部变量为条件的每日季节性周期,例如:(i)日前价格; (ii)系统负荷; (iii)风力渗透。随后,通过对Nord Pool进行的实证研究,证明了拟议方法相对于多个通用基准的优越性,与2008-2011年的三年期的实际预测相仿。

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