High-performance hybrid genetic algorithm to solve transmission network expansion planning

In this study, a high-performance hybrid genetic algorithm (HGA) is proposed to solve static and multistage transmission network expansion planning (TNEP) problem. The main features of the HGA are: (i) it avoids homogenised solutions by using a special genetic algorithm as the backbone of the proced...

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Bibliographic Details
Published in:IET generation, transmission & distribution Vol. 11; no. 5; pp. 1111 - 1118
Main Authors: Gallego, Luis A, Garcés, Lina P, Rahmani, Mohsen, Romero, Ruben A
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 30.03.2017
Subjects:
Colombian 93‐bus electrical system
constructive heuristic algorithm
fast relaxation strategy
fitness function
genetic algorithms
high‐performance HGA
high‐performance hybrid genetic algorithm
linear programming
linear programming problem
multistage TNEP problem
North‐Northeast Brazilian 87‐bus electrical system
path‐relinking algorithm
power transmission planning
Research Article
South Brazilian 46‐bus electrical system
static transmission network expansion planning problem
transmission network expansion planning
static transmission network expansion planning problem
linear programming problem
fitness function
linear programming
Colombian 93-bus electrical system
genetic algorithms
North-Northeast Brazilian 87-bus electrical system
South Brazilian 46-bus electrical system
high-performance HGA
constructive heuristic algorithm
high-performance hybrid genetic algorithm
transmission network expansion planning
path-relinking algorithm
power transmission planning
multistage TNEP problem
fast relaxation strategy
ISSN:1751-8687, 1751-8695
Online Access:Get full text
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Summary:In this study, a high-performance hybrid genetic algorithm (HGA) is proposed to solve static and multistage transmission network expansion planning (TNEP) problem. The main features of the HGA are: (i) it avoids homogenised solutions by using a special genetic algorithm as the backbone of the procedure, (ii) uses a powerful path-relinking algorithm for the deep exploration of local solutions, (iii) employs an efficient constructive heuristic algorithm for finding high-quality initial solutions and for improving solution qualities and (iv) uses a fast relaxation strategy for solving the linear programming problems required for calculating the fitness functions. This procedure will result in an intelligent exploration of a large search space in less amount of time. The proposed methodology is tested with three electrical systems: South Brazilian 46-bus, Colombian 93-bus and the North-Northeast Brazilian 87-bus.
ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2016.0511