Abstract
In this article, monthly and yearly electricity consumption predictions for the German power market were calculated using the multiple variable regression model. This model accounts for several factors that are often neglected when forecasting electricity demand in practice, in particular the role of the higher efficiency of electricity usage from year to year. The analysis performed in this paper helps to explain why no growth in power consumption has been observed in Germany during the last decade. It shows that the electricity efficiency usage dataset is a relevant input for the model, which mitigates the combined impact of other factors on the final electricity consumption. The electricity demand forecasting model presented in this article was built in the year 2013 with forecasts for the future years’ electricity demand in Germany provided until 2020. These forecasts and related findings are also evaluated in this article.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference26 articles.
1. Green jobs? Economic impacts of renewable energy in Germany
2. UK Electricity Market Reform—revolution or much ado about nothing?
3. The role of residual demand in electricity price analysis and forecasting: Case of the Czech electricity market;Smolen;Int. J. Energy Econ. Policy,2017
4. Electricity Price and Demand Pattern Changes Due to Increases in Solar Generation in German Electricity Markets;Smolen;Int. J. Energy Econ. Policy,2018
5. Surviving the Energy Transition: Development of a Proposal for Evaluating Sustainable Business Models for Incumbents in Germany’s Electricity Market
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献