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Kalakova, A., Nunna, H.S.V.S.K., Jamwal, P.K. and Doolla, S. (2021) A Novel Genetic Algorithm Based Dynamic Economic Dispatch with Short-Term Load Forecasting. IEEE Transactions on Industry Applications, 57, 2972-2982.
https://doi.org/10.1109/tia.2021.3065895

has been cited by the following article:

• TITLE: Solving the Economic Dispatch Problem of Power Systems Based on Multi-Population Genetic Algorithm

  AUTHORS: Yuke Dang, Yaming Ren

  KEYWORDS: Economic Dispatch Problem, Multi-Population Genetic Algorithm, Optimization

  JOURNAL NAME: Open Access Library Journal, Vol.11 No.11, November 26, 2024

  ABSTRACT: The economic dispatch problem in power systems is a classic issue in the field of power systems. This paper first uses the traditional genetic algorithm to solve the economic dispatch problem of power systems. The simulation results show that the classic genetic algorithm falls into the dilemma of local minimum values. Therefore, we introduce a multi-population genetic algorithm, setting different crossover and mutation probabilities in different populations, and introducing an immigration operator to replace the worst individuals in different populations with the best individuals found by various populations. The simulation results show that the introduction of the multi-population genetic algorithm avoids the algorithm falling into premature situations to a certain extent during the entire iteration process. Compared with the classic genetic algorithm, the optimal solution obtained by the multi-population genetic algorithm is obviously better than the optimal solution obtained by the classic genetic algorithm.