Forecasting and Assessing Risk of Individual Electricity Peaks.

• Superior document: Mathematics of Planet Earth Series
• Author: Jacob, Maria.
• TeilnehmendeR: Neves, Cláudia.; Vukadinović Greetham, Danica.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2019.; ©2020.
• Year of Publication: 2019
• Edition: 1st ed.
• Language: English
• Series: Mathematics of Planet Earth Series
• Physical Description: 1 online resource (108 pages)

Table of Contents

Intro -- Preface -- Contents -- Acronyms -- 1 Introduction -- 1.1 Forecasting and Challenges -- 1.2 Data -- 1.2.1 Irish Smart Meter Data -- 1.2.2 Thames Valley Vision Data -- 1.3 Outline and Objectives -- References -- 2 Short Term Load Forecasting -- 2.1 Forecasts -- 2.1.1 Linear Regression -- 2.1.2 Time Series Based Algorithms -- 2.1.3 Permutation Based Algorithms -- 2.1.4 Machine Learning Based Algorithms -- 2.2 Forecast Errors -- 2.2.1 Point Error Measures -- 2.2.2 Time Shifted Error Measures -- 2.3 Discussion -- References -- 3 Extreme Value Theory -- 3.1 Basic Definitions -- 3.2 Maximum of a Random Sample -- 3.3 Exceedances and Order Statistics -- 3.3.1 Exceedances -- 3.3.2 Asymptotic Distribution of Certain Order Statistics -- 3.4 Extended Regular Variation -- References -- 4 Extreme Value Statistics -- 4.1 Block Maxima and Peaks over Threshold Methods -- 4.2 Maximum Lq-Likelihood Estimation with the BM Method -- 4.2.1 Upper Endpoint Estimation -- 4.3 Estimating and Testing with the POT Method -- 4.3.1 Selection of the Max-Domain of Attraction -- 4.3.2 Testing for a Finite Upper Endpoint -- 4.3.3 Upper Endpoint Estimation -- 4.4 Non-identically Distributed Observations-Scedasis Function -- References -- 5 Case Study -- 5.1 Predicting Electricity Peaks on a Low Voltage Network -- 5.1.1 Short Term Load Forecasts -- 5.1.2 Forecast Uncertainty -- 5.1.3 Heteroscedasticity in Forecasts -- References -- Index.