A Genetic Algorithm to Solve Power System Expansion Planning with Renewable Energy
Journal
Advances in Soft Computing
Lecture Notes in Computer Science
ISSN
0302-9743
1611-3349
Date Issued
2018
Author(s)
Marmolejo Saucedo, José Antonio
Ramírez, Juan Manuel
Hernández, Agustina
Type
Resource Types::text::book::book part
DOI
URL
Abstract
In this paper, a deterministic dynamic mixed-integer programming model for solving the generation and transmission expansion-planning problem is addressed. The proposed model integrates conventional generation with renewable energy sources and it is based on a centralized planned transmission expansion. Due a growing demand over time, it is necessary to generate expansion plans that can meet the future requirements of energy systems. Nowadays, in most systems a public entity develops both the short and long of electricity-grid expansion planning and mainly deterministic methods are employed. In this study, an heuristic optimization approach based on genetic algorithms is presented. Numerical results show the performance of the proposed algorithm. © 2018, Springer Nature Switzerland AG.
Subjects