TY - GEN
T1 - Environmental/Economic Power Dispatch Using Multiobjective Evolutionary Algorithms
T2 - A Comparative Study
AU - Abido, M. A.
PY - 2003
Y1 - 2003
N2 - A comparative study of newly developed Pareto-based Multi-Objective Evolutionary Algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. Specifically, Niched Pareto Genetic Algorithm (NPGA), Nondominated Sorting Genetic Algorithm (NSGA), and Strength Pareto Evolutionary Algorithm (SPEA) have been developed and successfully applied to Environmental/Economic electric power Dispatch (EED) problem. These multiobjective evolutionary algorithms have been individually examined and applied to the standard IEEE 30-bus test system. A feasibility check procedure has been developed and superimposed on MOEA to restrict the search to the feasible region of the problem space. The results of MOEA have been compared to those reported in the literature. The comparison shows the superiority of MOEA to the traditional multiobjective optimization techniques and confirms their potential to handle power system multiobjective optimization problems.
AB - A comparative study of newly developed Pareto-based Multi-Objective Evolutionary Algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. Specifically, Niched Pareto Genetic Algorithm (NPGA), Nondominated Sorting Genetic Algorithm (NSGA), and Strength Pareto Evolutionary Algorithm (SPEA) have been developed and successfully applied to Environmental/Economic electric power Dispatch (EED) problem. These multiobjective evolutionary algorithms have been individually examined and applied to the standard IEEE 30-bus test system. A feasibility check procedure has been developed and superimposed on MOEA to restrict the search to the feasible region of the problem space. The results of MOEA have been compared to those reported in the literature. The comparison shows the superiority of MOEA to the traditional multiobjective optimization techniques and confirms their potential to handle power system multiobjective optimization problems.
KW - Economic power dispatch
KW - Emission reduction
KW - Environmental impact
KW - Evolutionary algorithms
KW - Multiobjective optimization
UR - https://www.scopus.com/pages/publications/1542329636
M3 - Conference contribution
AN - SCOPUS:1542329636
SN - 0780379896
SN - 9780780379893
T3 - 2003 IEEE Power Engineering Society General Meeting, Conference Proceedings
SP - 920
EP - 925
BT - 2003 IEEE Power Engineering Society General Meeting, Conference Proceedings
ER -
