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Dynamic Economic Emission Dispatch Considering Wind Uncertainty Using Non-Dominated Sorting Crisscross Optimization

CL Chinnadurrai, T. Aruldoss Albert Victoire

2020IEEE Access34 citationsDOIOpen Access PDF

Abstract

This paper presents a multi objective crisscross optimization to solve dynamic economic emission dispatch with wind-power uncertainty. The dynamic economic dispatch with combined emission requirements is formulated as a multi-objective optimization problem. The wind power output is predicted as an uncertain model and varies within a bounded limit. Minimizing the wind curtailment is added as an objective to the existing problem objectives of minimizing cost and emissions. Multi-objective crisscross optimization is proposed to solve the problem, utilizing a fast non-dominated sorting principle to obtain the optimal Pareto set of solutions. The proposed non-dominated sorting also ensures diversity, elitism and various complexities due to the high dimensionality of the problem. Exploration for global convergence and exploitation for a better solution is governed by two operators, namely, horizontal crossover and vertical crossover. The proposed solution technique is applied to standard multi-objective benchmark test problems and subsequently to standard dynamic economic dispatch problems with different ratios of wind power penetration.

Topics & Concepts

Economic dispatchMathematical optimizationSortingWind powerCrossoverMulti-objective optimizationComputer scienceOptimization problemPareto principleBenchmark (surveying)Electric power systemPower (physics)MathematicsEngineeringAlgorithmQuantum mechanicsElectrical engineeringGeodesyArtificial intelligencePhysicsGeographyElectric Power System OptimizationEnergy Load and Power ForecastingIntegrated Energy Systems Optimization
Dynamic Economic Emission Dispatch Considering Wind Uncertainty Using Non-Dominated Sorting Crisscross Optimization | Litcius