In this paper, we apply the machine learning (ML) methodology to solve such a problem. Two power systems are chosen as case studies.
In this paper, we solve the economic load dispatch (ELD) by means of the radial basis neural network (RBN). It is shown that, by using the trained RBN, the time ...
Based on the historical data, this paper proposes a prediction method based on RBF (radial basis function) neural network. This method is based on the model ...
This work reports the application of ensemble artificial neural networks, a machine learning technique, in the solution of short term optimal power generation.
In this paper, a load dispatch model is developed for the system consisting of both thermal generators and wind turbines. The probability of stochastic wind ...
Apr 15, 2024 · The proposed model can improve the accuracy of wind power prediction by experiments. Real datasets from wind farm in China is employed for the modeling study.
Missing: Economic | Show results with:Economic
Jul 18, 2023 · This article focuses on the development of a very-short-term forecasting model using machine learning algorithms.
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May 16, 2018 · This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN).
An accurate short-term forecasting method for load of electric power system can help the electric power system's operator to reduce the risk of ...
Missing: Economic Dispatch
The aim of this work was to develop an efficient model for forecasting wind energy in the short term using machine learning and metaheuristics methods. The ...