Despite the tightening of energy performance standards for buildings in various countries
and the increased use of efficient and renewable energy technologies, it is clear that the …

This research, conducted throughout the years 2022 and 2023, examines the role of
blockchain technology in optimizing Demand Response (DR) within Smart Grids (SGs). It …

Distribution System Operators (DSOs) and Aggregators benefit from novel energy
forecasting (EF) approaches. Improved forecasting accuracy may make it easier to deal with …

The continuous growth of urban populations has led to the persistent problem of traffic
congestion, which imposes adverse effects on quality of life, such as commute times, road …

The knowledge of daily peak load consumption is crucial for energy planning, energy
management, and resource allocation, as it is an essential element of supply-side …

Accurate electricity demand forecasting is crucial for ensuring the sustainability and
reliability of power systems. Least square support vector machines (LSSVM) are well suited …

This study explores the application of deep learning in forecasting electricity consumption.
Initially, we assess the performance of standard neural networks, such as convolutional …

Accurate cooling consumption forecasts are crucial for optimizing energy management,
storage, and overall efficiency in interconnected HVAC systems. Weather conditions …

This study introduces an innovative approach to day-ahead solar irradiance forecasting,
utilizing the NeuralProphet model—a deep learning-based extension of the Prophet tool—to …

The population growth and urbanization have a significant impact on the current rise in
electricity demand. Therefore, it is essential to embrace a proactive approach to determine …