Artificial neural network based short term electrical load forecasting

نویسندگان

چکیده

In power generation, a 24-hour load profile can vary significantly throughout the day. Therefore, generation must be adjusted to reduce money loss due excess generation. This paper presents short-term forecasting (STLF) system design using artificial neural network (ANN). As ANN come in many different configurations, this analyzes best configuration via trial-and-error method. To train ANN, historical data from 2016 2018 of south energy cooperative (AEC) is used. A simple feedforward type with one hidden layer implemented, where 48 neurons are used at input layer. For layer, an arbitrary 50 chosen and 24 output generate day ahead profile. measure activation function for SLTF application, four non-linear functions will tested create two three architecture. Finally, performance new networks compared against model. From obtained result, performing model found as layers Tanh its 8.9% testing mean absolute percentage error (MAPE).

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ژورنال

عنوان ژورنال: International Journal of Power Electronics and Drive Systems

سال: 2022

ISSN: ['2722-2578', '2722-256X']

DOI: https://doi.org/10.11591/ijpeds.v13.i1.pp586-593