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AI concepts for Demand Side Shedding Management in Libya
conference contribution
posted on 2019-11-19, 10:06 authored by Ali A A Alarbi, Dani StricklandDani Strickland, Richard BlanchardRichard BlanchardDemand side management is traditionally concerned
with adjusting the load to meet generation to assist with
stability, ratings or other constraints. However, in many
countries, load outstrips generation and instead of managing the
load, shedding the load is more common. This paper looks at a
portion of the Libyan grid system which suffers from daily load
shedding and explores if AI concepts can be used to intelligently
manage the shedding of this load so that it is unnoticeable to
consumers
History
School
- Mechanical, Electrical and Manufacturing Engineering
Research Unit
- Centre for Renewable Energy Systems Technology (CREST)
Published in
2019 8th International Conference on Renewable Energy Research and Applications (ICRERA)Pages
505 - 510Source
8th International Conference on Renewable Energy Research and Applications (ICRERA 2019)Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2019-08-22Publication date
2020-02-13Copyright date
2019ISBN
9781728135878eISSN
2572-6013Publisher version
Language
- en
Location
Brasov, RomaniaEvent dates
3rd November 2019 - 6th November 2019Depositor
Dr Dani Strickland. Deposit date: 18 November 2019Administrator link
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