J 2021

Residual electricity demand: An empirical investigation

DO, Linh Phuong Catherine; Štefan LYÓCSA a Peter MOLNÁR

Základní údaje

Originální název

Residual electricity demand: An empirical investigation

Autoři

DO, Linh Phuong Catherine; Štefan LYÓCSA (703 Slovensko, garant, domácí) a Peter MOLNÁR

Vydání

Applied Energy, Elsevier, 2021, 0306-2619

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Kód RIV

RIV/00216224:14560/21:00122734

Organizace

Ekonomicko-správní fakulta – Masarykova univerzita – Repozitář

UT WoS

000613289500003

EID Scopus

2-s2.0-85097784646

Klíčová slova anglicky

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

Anotace

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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