英文标题：
《Probabilistic Mid- and Long-Term Electricity Price Forecasting》
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作者：
Florian Ziel, Rick Steinert
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最新提交年份：
2018
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英文摘要：
  The liberalization of electricity markets and the development of renewable energy sources has led to new challenges for decision makers. These challenges are accompanied by an increasing uncertainty about future electricity price movements. The increasing amount of papers, which aim to model and predict electricity prices for a short period of time provided new opportunities for market participants. However, the electricity price literature seem to be very scarce on the issue of medium- to long-term price forecasting, which is mandatory for investment and political decisions. Our paper closes this gap by introducing a new approach to simulate electricity prices with hourly resolution for several months up to three years. Considering the uncertainty of future events we are able to provide probabilistic forecasts which are able to detect probabilities for price spikes even in the long-run. As market we decided to use the EPEX day-ahead electricity market for Germany and Austria. Our model extends the X-Model which mainly utilizes the sale and purchase curve for electricity day-ahead auctions. By applying our procedure we are able to give probabilities for the due to the EEG practical relevant event of six consecutive hours of negative prices. We find that using the supply and demand curve based model in the long-run yields realistic patterns for the time series of electricity prices and leads to promising results considering common error measures.
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中文摘要：
电力市场的自由化和可再生能源的开发给决策者带来了新的挑战。伴随着这些挑战，未来电价变动的不确定性越来越大。旨在短期内建模和预测电价的论文数量不断增加，为市场参与者提供了新的机会。然而，关于中长期电价预测问题的电价文献似乎非常缺乏，这对于投资和政治决策来说是强制性的。我们的论文通过引入一种新方法来缩小这一差距，这种方法可以模拟几个月到三年内每小时的电价。考虑到未来事件的不确定性，我们能够提供概率预测，即使从长期来看，也能够检测价格飙升的概率。作为市场，我们决定在德国和奥地利使用EPEX日前电力市场。我们的模型扩展了X模型，该模型主要利用电力日前拍卖的买卖曲线。通过应用我们的程序，我们能够给出连续六小时负价格的EEG实际相关事件的概率。我们发现，从长期来看，使用基于供需曲线的模型可以得出电价时间序列的现实模式，并在考虑常见误差度量的情况下得出有希望的结果。
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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