Long term electric load forecasting based on particle swarm optimization
M.R. AlRashidi and
Applied Energy, 2010, vol. 87, issue 1, 320-326
This paper presents a new method for annual peak load forecasting in electrical power systems. The problem is formulated as an estimation problem and presented in state space form. A particle swarm optimization is employed to minimize the error associated with the estimated model parameters. Actual recorded data from Kuwaiti and Egyptian networks are used to perform this study. Results are reported and compared to those obtained using the well known least error squares estimation technique. The performance of the proposed method is examined and evaluated. Finally, estimated model parameters are used in forecasting the annual peak demands of Kuwait network.
Keywords: Forecasting; Particle; swarm; optimization; Least; error; Peak; load; Estimation (search for similar items in EconPapers)
References: View complete reference list from CitEc
Citations View citations in EconPapers (23) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:87:y:2010:i:1:p:320-326
Ordering information: This journal article can be ordered from
http://www.elsevier. ... 405891/bibliographic
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Series data maintained by Dana Niculescu ().