A weather temperature methodology on the Italian electricity demand

Matteo Contu, G. Pecoraro, F. Quaglia, Mauro Bonanni, F. Allella, A. Pascucci, E. Carlini
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Abstract

This paper presents a proposal methodology to study the temperature dependence of the Italian electricity demand. Indeed, weather temperature has a significant influence on the electricity consumption. From a Transmission System Operator (TSO) perspective, an accurate estimation of this effect is crucial to interpret and predict demand fluctuations. Several dispatching applications consider these phenomena, as for example adequacy analysis, demand forecasting tools, and real-time operational procedures. Based on the geographical features of Italy, it was possible to identify various sensitivity behaviors at regional scale. The purpose of this study is to develop a temperature sensitivity model to be applied on electricity demand profile with different time granularity (e.g., daily, hourly). A clustering analysis on the historical input data is performed. Furthermore, a thorough investigation to identify the optimal best-fitting method for this application is described. In order to test the methodology, some relevant business cases are simulated considering also extreme scenarios. Results on COVID-19 scenario is also described. Finally, an outlook on the planned future developments of the method is provided.
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意大利电力需求的天气温度方法学
本文提出了一种研究意大利电力需求的温度依赖性的建议方法。的确,天气温度对用电量有显著的影响。从输电系统运营商(TSO)的角度来看,准确估计这种影响对于解释和预测需求波动至关重要。一些调度应用程序考虑了这些现象,例如充足性分析、需求预测工具和实时操作程序。根据意大利的地理特征,可以在区域尺度上识别各种敏感性行为。本研究的目的是建立一个适用于不同时间粒度(如日、时)的电力需求曲线的温度敏感性模型。对历史输入数据进行聚类分析。此外,一个彻底的调查,以确定最佳的最佳拟合方法,为该应用程序描述。为了测试该方法,还模拟了一些相关的业务案例,并考虑了极端场景。并介绍了新冠肺炎情景下的结果。最后,对该方法的未来发展进行了展望。
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