Simulation optimization: simulation-based optimization
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
A Constraint-Handling Genetic Algorithm to Power Economic Dispatch
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Putting more brain-like intelligence into the electric power grid: what we need and how to do it
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Multiobjective evolutionary algorithms for electric power dispatch problem
IEEE Transactions on Evolutionary Computation
Heuristic power scheduling of electric vehicle battery charging based on discrete event simulation
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Evolutionary optimization of multi-agent controlstrategies for electric vehicle charging
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Genetic programming enabled evolution of control policies for dynamic stochastic optimal power flow
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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The implementation of intelligent power grids, in form of smart grids, introduces new challenges to the optimal dispatch of power. Thus, optimization problems need to be solved that become more and more complex in terms of multiple objectives and an increasing number of control parameters. In this paper, a simulation based optimization approach is introduced that uses metaheuristic algorithms for minimizing several objective functions according to operational constraints of the electric power system. The main idea is the application of simulation for computing the fitness-values subject to the solution generated by a metaheuristic optimization algorithm. Concerning the satisfaction of constraints, the central concept is the use of a penalty function as a measure of violation of constraints, which is added to the cost function and thus minimized simultaneously. The corresponding optimization problemis specified with respect to the emerging requirements of future smart electric grids.