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MEAN-VARIANCE MAPPING OPTIMIZATION TECHNIQUES FOR NONCONVEX ECONOMIC DISPATCH PROBLEMS

TRUONG, HOANG KHOA (2015) MEAN-VARIANCE MAPPING OPTIMIZATION TECHNIQUES FOR NONCONVEX ECONOMIC DISPATCH PROBLEMS. Masters thesis, Universiti Teknologi PETRONAS.

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Abstract

Economic dispatch (ED) is the determination of optimized real power output from a number of electricity generators needed to meet load requirements at lowest possible cost. Real-world ED problems have non-convex objective functions with complex constraints due to the generators characteristics such as valve point loading effects, usage of multiple fuel options and the existence of prohibited operating zones. This leads to the difficulty in finding the global optimal solution. This thesis presents a new application for solving non-convex ED problems by using mean-variance mapping optimization (MVMO) techniques. MVMO algorithm has conceptual similarities with other known metaheuristic algorithms which use three evolutionary operators: selection, mutation and crossover. However, the special feature ofMVMO is the mapping function applied for the mutation based on the mean and variance of nbest archived population. The original MVMO utilizes a single particle to start the search process.

Item Type: Thesis (Masters)
Academic Subject : Academic Department - Foundation And Applied Science
Subject: Q Science > Q Science (General)
Divisions: Fundamental and Applied Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Sep 2021 09:01
Last Modified: 20 Sep 2021 09:01
URI: http://utpedia.utp.edu.my/id/eprint/21464

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