J 2021

Residual electricity demand: An empirical investigation

DO, Linh Phuong Catherine; Štefan LYÓCSA and Peter MOLNÁR

Basic information

Original name

Residual electricity demand: An empirical investigation

Authors

DO, Linh Phuong Catherine; Štefan LYÓCSA (703 Slovakia, guarantor, belonging to the institution) and Peter MOLNÁR

Edition

Applied Energy, Elsevier, 2021, 0306-2619

Other information

Language

English

Type of outcome

Article in a journal

Country of publisher

Netherlands

Confidentiality degree

is not subject to a state or trade secret

References:

RIV identification code

RIV/00216224:14560/21:00122734

Organization

Ekonomicko-správní fakulta – Repository – Repository

UT WoS

000613289500003

EID Scopus

2-s2.0-85097784646

Keywords in English

Electricity demand; Residual demand; Renewables; Quantile regression
Changed: 13/1/2024 03:23, RNDr. Daniel Jakubík

Abstract

V originále

Residual electricity demand represents the load that cannot be met by renewable production and that therefore must be provided by conventional power plants, electricity imports or storage capacity. Residual demand is thus a key variable for power system operators and electricity market participants. However, the literature lacks a comprehensive study exploring the drivers of residual demand. Using linear and quantile regression models, we are able to identify previous demand, major and minor holidays, day of the week and temperature as having a significant influence on demand and residual demand. However, the influence of these factors differs not only for lower (left-) and upper (right-tail) levels of total and residual demand but also for total and residual demand during the day. We find that i) the influence of the outside temperature on electricity demand is weakened by the spatial variation in the temperature across a country, ii) the heating and cooling degree influences residual demand much more than they influence total demand, and iii) residual demand is much harder to predict than total demand. Our results imply, that electricity producers, risk managers, market participants and policy makers need comprehensive empirical models to predict residual demand.

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