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Research on Cross-border Electricity Price Spread Model of Nordic Power Market

机译：北欧电力市场跨境电价价差模型研究

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摘要

In this paper, the cross-border electricity price difference data in the Nordic power market is modeled with the standard generalized autoregressive conditional heteroscedasticity model, GJR model and Markov-switching GARCH model. These models are estimated with normal, skewed normal and skewed student-t-t distributions. Studies show that cross-border electricity price difference data is not only a "spike" higher than the electricity price data, data jumping is more obvious, but also "volatility cluster" and strongly regime-dependent. The example analysis shows that the MS-GARCH model estimated with skewed normal distribution has the better predictive performance than other models, according to evaluation index like mean squared error MSE and the mean absolute error MAE for one- and multi-step ahead forecasts. Accurate cross-border electricity price difference forecast results can enable power companies and consumers to avoid risks when auctioning in the financial transmission right market.
机译：本文利用标准的广义自回归条件异方差模型，GJR模型和马尔可夫切换GARCH模型对北欧电力市场中的跨境电价差数据进行建模。用正态，偏态正态和偏态学生t-t分布估计这些模型。研究表明，跨境电价差数据不仅比电价数据高出“峰值”，数据跳变更为明显，而且还具有“波动性集群”和强烈的制度依赖性。实例分析表明，根据一阶和多阶超前预测的均方误差MSE和平均绝对误差MAE等评估指标，使用偏态正态分布估计的MS-GARCH模型比其他模型具有更好的预测性能。准确的跨境电价差异预测结果可以使电力公司和消费者在金融传输权市场上进行拍卖时规避风险。

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