Log in

Create a user profile using your existing professional profile on LinkedIn, Academia, or ResearchGate.


Alternatively, register a username and password to start an account.


By creating an account you will be able to contribute articles, engage in discussion groups, network with fellow professionals and businesses, and receive interest-related alerts.

Forgot Password

Please enter your email address below and you will receive a temporary link to re-activate your account

Article image

Council for Scientific and Industrial Research, Paul Mokilane, Renée Koen, Thandulwazi Magadla

17 September 2014

English

uKESA Librarian, Paul Mokilane

Conference paper

Council for Scientific and Industrial Research

South Africa

Downloads

Website References

Energy

Energy

Energy conservation

Energy surveys

Methodologies

Renewable energy

Renewable energy resources

South Africa

Sustainability

Developing long-term scenario forecasts to support electricity generation investment decisions

Renée Koen, Thandulwazi Magadla, Paul Mokilane

Many decisions regarding capital investment in electricity generation technologies need to be made well in advance, usually when there is still a large amount of uncertainty regarding the favourability of future conditions. There may be uncertainty about the amount of electricity required in future as well as the variability in the demand, and both of these uncertainties can affect decisions pertaining to such capital investment decisions. This paper presents an approach that uses multilevel models to develop scenario forecasts for South African load profiles (hour-to-hour changes in the electricity demand), which can then be used to support decisions regarding the electricity generation capacity required. Although historical load profile patterns are known, there is uncertainty about how future patterns will deviate from historical ones. By developing scenarios that represent different views about future load profile patterns, forecasts can be obtained for each scenario and, in turn, these scenario forecasts can be used to investigate the effect of changes in demand patterns on future electricity generation requirements. The approach of using multilevel modelling to obtain long-term hourly forecasts for a particular scenario has not been seen elsewhere in the literature but shows promise for providing appropriate support electricity generation expansion decisions

View Contributors:

Comments

No comments available
LOAD MORE