Modified teaching learning based algorithm for economic load dispatch incorporating wind power

An economic load dispatch problem (ELD) for power system consisting of thermal generators integrated with wind farm is solved. Wind speed which is essentially a random variable is characterized by weibull probability density function (pdf). Apart from classic economic dispatch term in an objective function, the terms such as direct cost, overestimation and underestimation of available wind power are included. The simulation results for three tests systems are presented using Modified Teaching Learning Based optimization algorithm (MTLBO). To validate the efficacy of proposed method an ELD problem is solved without considering wind power penetration and the results obtained by MTLBO are compared with other algorithms such as Genetic Algorithm (GA), particle swarm optimization (PSO), biogeography-based optimization (BBO) and variable scaling hybrid differential evolution (VSHDE). The minimum cost of electricity obtained by MTLBO algorithm is shown to be better than or comparable to these methods.

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