… Smart grid-based monitoring devices such as smart meters, … adjustment systems were used
to evaluate the system efficacy. … a hybrid sequential deep learning-based energy forecasting …

… , electricity generation, and energy demand to predict future … energy consumption of air
conditioners within the smart grid … , the efficiency of the hybrid Support Vector Machine (SVM) and …

… price forecasting, the merit order of energy price forecasting, … Grid-based clustering for
energy systems can be … of energy store control facility, a modern ‘Graciosa Hybrid Renewable …

… increase in energy consumption as the consumer turns on the air … Additionally, cooling
systems must work harder as they must … Electricity Demand Forecasting for Smart Grid based on …

… use of Tensorflow libraries that predict energy consumption and deep reinforcement learning
to … the battery of the vehicles as an injection to the grid, and the air conditioning system of a …

… the best combination of energy sources in a Hybrid Energy System (HES). The HES case …
The algorithms utilized a dataset comprised 50 columns, including air temperature, relative …

… methods, artificial intelligence techniques, and hybrid models to … role of deep learning in
building energy forecasting and … electricity from the grid based on the electricity price are …

… This paper presents a hybrid model that combines support vector … forecasting the
consumption of electricity units and analyses the peak demand using efficient machine learning …

… -term forecasting model using a supervised machine learning … and used to forecast future
electric power consumption and … the forecasting of energy consumption of Air Conditioner (AC). …

… or machine learning techniques train and forecast data by … networks protected by conventional
air-gapped separations [… of the power system using a hybrid support vector machine and …