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This paper presents a method for short-term electricity load forecasting using an Artificial Neural Network (ANN), addressing the limitations of traditional econometric approaches that assume linear relationships. The proposed single-layer ANN model incorporates key input variables such as hour, day indicators, and weather-related inputs, demonstrating improved forecasting accuracy. The findings highlight the adaptability of ANNs in optimizing power system operations, including unit commitment and power tra

Author

Shivam Koli

Language

EN