.png){kind=icon}
.png){kind=icon}
Return
NSGA-II algorithm for multi-objective generation expansion planning problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.epsr.2008.09.011.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper presents an application of Elitist Non-dominated Sorting Genetic Algorithm version II (NSGA-II), to multi-objective generation expansion planning (GEP) problem. The GEP problem is considered as a two-objective problem. The first objective is the minimization of investment cost and the second objective is the minimization of outage cost (or maximization of reliability). To improve the performance of NSGA-II, two modifications are proposed. One modification is incorporation of Virtual Mapping Procedure (VMP), and the other is introduction of controlled elitism in NSGA-II. A synthetic test system having 5 types of candidate units is considered here for GEP for a 6-year planning horizon. The effectiveness of the proposed modifications is illustrated in detail. (C) 2008 Elsevier B.V. All rights reserved.
Keywords:
Combinatorial optimization
Generation expansion planning
Multi-objective
Non-dominated Sorting Genetic Algorithm
(NSGA-II)
Virtual Mapping Procedure
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.2
Papers:
1.1W
Citations:
2.2W