Using multivariate time series methods to estimate location and climate change effects on temperature readings employed in electricity demand simulation

Bowden Ross S.; Clarke Brenton R.

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Using multivariate time series methods to estimate location and climate change effects on temperature readings employed in electricity demand simulation

机译：使用多元时间序列方法估算位置和气候变化对电力需求模拟中使用的温度读数的影响

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Long-term historical daily temperatures are used in electricity forecasting to simulate the probability distribution of future demand but can be affected by changes in recording site and climate. This paper presents a method of adjusting for the effect of these changes on daily maximum and minimum temperatures. The adjustment technique accommodates the autocorrelated and bivariate nature of the temperature data which has not previously been taken into account. The data are from Perth, Western Australia, the main electricity demand centre for the South-West of Western Australia. The statistical modelling involves a multivariate extension of the univariate time series interleaving method', which allows fully efficient simultaneous estimation of the parameters of replicated Vector Autoregressive Moving Average processes. Temperatures at the most recent weather recording location in Perth are shown to be significantly lower compared to previous sites. There is also evidence of long-term heating due to climate change especially for minimum temperatures.

机译：长期历史日温度用于电力预测中，以模拟未来需求的概率分布，但会受到记录地点和气候变化的影响。本文提出了一种调整这些变化对每日最高和最低温度的影响的方法。调整技术可适应温度数据的自相关和双变量性质，而以前从未考虑过。数据来自西澳大利亚州珀斯市，这是西澳大利亚州西南部的主要电力需求中心。统计建模涉及单变量时间序列交织方法的多变量扩展，该方法允许对复制的矢量自回归移动平均过程的参数进行完全有效的同时估计。与之前的站点相比，珀斯的最新气象记录位置的温度明显降低。也有证据表明由于气候变化，特别是最低温度，会长期供暖。

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《Australian & New Zealand journal of statistics》 |2017年第4期|413-431|共19页
作者
Bowden Ross S.; Clarke Brenton R.;
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作者单位

Murdoch Univ, Sch Engn & Informat Technol, Math & Stat, Murdoch, WA 6150, Australia;

Murdoch Univ, Sch Engn & Informat Technol, Math & Stat, Murdoch, WA 6150, Australia;

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正文语种 eng
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data correction; forecasting; maximum likelihood; replicated process; VARMA;

机译：数据校正;预测;最大似然;复制过程;VARMA;

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Using multivariate time series methods to estimate location and climate change effects on temperature readings employed in electricity demand simulation

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