Electric load forecasting using an artificial neural network

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A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons (2020, background): “A load time series is a pattern of measured values of load, exhibiting daily, weekly, and seasonal periodicities [66].”
Quantifying Changes in Building Electricity Use, With Application to Demand Response (2011, methodology): “, [21]), and regression with principal component analysis.”
Deep neural network based demand side short term load forecasting (2016, methodology): “Another branch of load forecasting is to use an artificial neural network (ANN) model [3], [4].”
Deep Learning for Time Series Forecasting: The Electric Load Case (2019, background): “Authors in [11] propose a shallow neural network with a single hidden layer to provide a 24-hour forecast using both load and temperature information.”
Electric load forecasting: Literature survey and classification of methods (2002, methodology): “Park et al. (1991b) developed a composite model for load prediction, composed of three components: nominal load, type load and residual load.”