Abstract
This paper illustrates an integrated Computational Intelligence (CI) technique using Artificial Neural Networks (ANN) and Genetic Algorithms (GA) for Electric Load Forecasting. A load forecasting model has been developed based on ANN and GA. The model produces a short-term forecast of the load in the 24 hours of the forecast day concerned. Optimum weights and the biases of ANN are found by the Genetic Algorithm. The technique has been tested on data provided by an Italian power company and the results obtained through the application of integrated computational intelligence approach show that this approach is not practical without high computational facilities as this problem is very complex. However, this points to the direction of evolutionary computing being integrated with parallel processing techniques to solve practical problems.
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