A new multiobjective procedure for solving nonconvex environmental/economic power dispatch

Complexity ◽  
2014 ◽  
Vol 20 (2) ◽  
pp. 47-62 ◽  
Author(s):  
Roozbeh Morsali ◽  
Mohsen Mohammadi ◽  
Iman Maleksaeedi ◽  
Noradin Ghadimi
Keyword(s):  
Environmental Economic ◽  
Economic Power ◽  
Power Dispatch ◽  
Economic Power Dispatch

scholarly journals A Pareto Optimal Solution for Environmental/Economic Power Dispatch using Multi-objective Genetic Algorithm

2019 ◽  
Vol 11 (4) ◽  
Author(s):  
Jawad Talaq
Keyword(s):  
Genetic Algorithm ◽  
Environmental Economic ◽  
Economic Power ◽  
Pareto Optimal ◽  
Fuel Cost ◽  
Trade Off ◽  
Pareto Optimal Front ◽  
Multi Objective ◽  
Power Dispatch ◽  
Economic Power Dispatch

The aim of this paper is to apply genetic algorithm (GA) to the solution of the environmental economic power dispatch problem. The environmental economic power dispatch is a multi-objective optimization problem. Fuel cost is considered as one of the objectives. The other objective is emissions such as SO2 or NOx or a combination of both. A trade-off relation between fuel cost and emissions can be formed through a pareto optimal front. Valve point opening and prohibited operating zones add non-smoothness and non-convexities to the objective functions. Evolutionary algorithms can efficiently solve such non-smooth and non-convex problems. Solutions need to be diversified and distributed among the whole range of the pareto optimal front. This allows operators to trade-off between fuel cost and emissions in feasible optimal regions. Applying genetic algorithm with diversity enhancement proves its effectiveness. Application of the algorithm on three and six unit systems is demonstrated

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