Paper Info
Title
Analysis of Constraint-Handling in Metaheuristic Approaches for the Generation and Transmission Expansion Planning Problem with Renewable Energy.
Abstract
A multiperiod generation and transmission expansion planning (G&TEP) problem is considered. This model integrates conventional generation with renewable energy sources, assuming a stochastic approach. The proposed approach is based on a centralized planned transmission expansion. Due to the worldwide recent energy guidelines, it is necessary to generate expansion plans adequate to the forecast demand over the next years. Nowadays, in most energy systems, a public entity develops both the short and long of electricity-grid expansion planning. Due to the complexity of the problem, there are different strategies to find expansion plans that satisfy the uncertainty conditions addressed. We proposed to address the G&TEP problem with a pure genetic algorithm approach. Different constraint-handling techniques were applied to deal with two complex case studies presented. Numerical results are shown to compare the strategies used in the test systems, and key factors such as a prior initialization of population and the estimated minimum number of generations are discussed.
Year
DOI
Venue
2018
10.1155/2018/1438196
COMPLEXITY
Field
DocType
Volume
Transmission (mechanics),Population,Mathematical optimization,Renewable energy,Public entity,Artificial intelligence,Initialization,Genetic algorithm,Mathematics,Machine learning,Metaheuristic
Journal
2018
ISSN
Citations 
PageRank 
1076-2787
0
0.34
References 
Authors
10
5
Name
Order
Citations
PageRank
María de Lourdes Martínez-Villaseñor1268.35
Hiram E. Ponce22613.63
Jose Antonio Marmolejo Saucedo3204.22
Juan M. Ramirez4257.54
Agustina Hernández500.34