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An explanatory analysis of electricity prices within day-ahead Spanish energy market by using a graphical automatization with R

机译:使用R的图形化自动化对日前西班牙能源市场中的电价进行解释性分析

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Since 1998, the Spanish and Portuguese Administrations began to share a common path in building the Iberian Electricity Market (MIBEL). This cooperation has been very successful, not only for its contribution to the existence of an electricity market on an Iberian level, but also on a European scale, as a significant step in building the Internal Energy Market. The price of electricity in the MIBEL is very changeable. This creates a lot of uncertainty and risk in market actors. Due to continuous changes in demand and marginal price adjustment, buyers and sellers can not know in advance the evolution of prices. Our interest is to study of this uncertainty since the perspective of the buyer and not the seller's perspective. The aim of this work is to develop a graphical analysis of the variables involved in the Spanish Energy Market in order to explain the electric price and provide to small traders, that could be interested in participating in that market, better knowledge of the schedule. On the other hand, large industrial consumers use this information to design strategies to optimize its production capacity and improve their production costs. In this article the variable of interest is the marginal price instead of demand. This paper provides a graphical analysis by means of an easily reproducible automatization with the R project for statistical computing that allows to explore, visualize and understand the key variables that define its final value. Mibel 2011 and 2012 data are used for ilustrations. The results show the importance of the calendar effect, seasonality and trend as principal factors to take into account for posterior fases: modeling and forecasting.
机译:自1998年以来,西班牙和葡萄牙政府开始在建立伊比利亚电力市场(MIBEL)方面走出一条共同道路。作为建立内部能源市场的重要一步,这种合作不仅在伊比利亚水平上为电力市场的存在做出了贡献,而且在欧洲范围内也取得了成功。 MIBEL中的电价变化很大。这给市场参与者带来了很多不确定性和风险。由于需求的不断变化和边际价格调整,买卖双方无法事先知道价格的变化。我们的兴趣是研究这种不确定性,因为是买方的观点,而不是卖方的观点。这项工作的目的是对西班牙能源市场中涉及的变量进行图形化分析,以解释电价并将其提供给有兴趣参与该市场的小交易者,以便他们更好地了解时间表。另一方面,大型工业消费者使用此信息来设计策略以优化其生产能力并提高其生产成本。在本文中,利益变量是边际价格而不是需求。本文通过R项目的易于重复的自动化进行了图形化分析,以进行统计计算,从而可以探索,可视化和理解定义其最终值的关键变量。 Mibel 2011和2012数据用于说明。结果表明,日历效应,季节性和趋势作为考虑后发因素的主要因素的重要性:建模和预测。

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