Optimization of power and heating systems based on a new hybrid algorithm

Optimization of power and heating systems based on a new hybrid algorithm

A novel combination of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is applied on a base case cogeneration optimization problem called the modified CGAM problem with two objective functions. The first objective function, the exergetic efficiency, should be maximized and the second on...

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Bibliographic Details
Main Authors: M.J. Mahmoodabadi, A.R. Ghavimi, S.M.S. Mahmoudi
Format: Article
Language:English
Published: Elsevier 2015-09-01
Series:Alexandria Engineering Journal
Subjects:
CGAM problem
Exergoeconomic optimization
Hybrid algorithms
Particle swarm optimization
Genetic algorithm
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016815000691
Description
Summary:A novel combination of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is applied on a base case cogeneration optimization problem called the modified CGAM problem with two objective functions. The first objective function, the exergetic efficiency, should be maximized and the second one is the total cost rate that should be minimized. The effects of important parameters, such as equivalence ratio, emission, and unit cost of fuel are studied on the exergetic and economic performance of the system.
ISSN:1110-0168

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