Mohamad Ridzuan, Mohamad Radzi (2018) An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming. Masters thesis, UTeM.
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Abstract
Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.
Item Type: | Thesis (Masters) |
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Uncontrolled Keywords: | Evolutionary programming (Computer science), Mathematical optimization, Engineering mathematics, Heuristic programming, Environmentally Energy Dispatch, New Meta Heuristic Evolutionary Programming |
Subjects: | T Technology > T Technology (General) |
Divisions: | Library > Tesis > FKE |
Depositing User: | Mohd. Nazir Taib |
Date Deposited: | 23 Aug 2019 03:34 |
Last Modified: | 07 Feb 2022 11:25 |
URI: | http://eprints.utem.edu.my/id/eprint/23310 |
Statistic Details: | View Download Statistic |
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