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A multiobjective evolutionary programming algorithm and its applications to power generation expansion planning
Meza, Jose L. Ceciliano Yildirim, Mehmet Bayram Masud, Abu S.M.
Meza, Jose L. Ceciliano
Yildirim, Mehmet Bayram
Masud, Abu S.M.
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Original Date
Digitization Date
Issue Date
2009-09
Type
Article
Genre
Keywords
Analytical hierarchy process,Evolutionary programming,Generation expansion planning (GEP),Multicriteria optimization,Operations research,Optimization methods,Power generation planning,Transmission expansion planning
Subjects (LCSH)
Citation
Abstract
The generation expansion planning (GEP) problem
is defined as the problem of determining WHAT, WHEN, and
WHERE new generation units should be installed over a planning
horizon to satisfy the expected energy demand. This paper
presents a framework to determine the number of new generating
units (e.g., conventional steam units, coal units, combined cycle
modules, nuclear plants, gas turbines, wind farms, and geothermal
and hydro units), power generation capacity for those units, number
of new circuits on the network, the voltage phase angle at each
node, and the amount of required imported fuel for a single-period
generation expansion plan. The resulting mathematical program is
a mixed-integer bilinear multiobjective GEP model. The proposed
framework includes a multiobjective evolutionary programming
algorithm to obtain an approximation of the Pareto front for
the multiobjective optimization problem and analytical hierarchy
process to select the best alternative. A Mexican power system
case study is utilized to illustrate the proposed framework. Results
show coherent decisions given the objectives and scenarios considered.
Some sensitivity analysis is presented when considering
different fuel price scenarios.
Table of Contents
Description
Publisher
IEEE
Journal
Book Title
Series
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 39, NO. 5, SEPTEMBER 2009;
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PubMed ID
DOI
ISSN
1083-4427