The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …

The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …

The energy and climate crises have accelerated the decarbonization of electric power
systems. An important part of this decarbonization process, along with the incorporation of …

Surface defect detection using deep learning approaches has become a promising area of
research, but the difficulty of accurately locating and segmenting various forms of defects …

Accurate day-ahead peak load forecasting is crucial not only for power dispatching but also
has a great interest to investors and energy policy maker as well as government. Literature …

Short term power load forecasting plays an important role in the management and
development of power systems with a focus on the reduction in power wastes and economic …

Evaluating and forecasting stability across different conditions is essential since smart grid
stabilization is among the most significant characteristics that could be employed to assess …

Short-term load forecasting (STLF) is critical for ensuring smooth and efficient functioning of
power systems. In this study, a prediction approach, combining ensemble empirical mode …

Accurately forecasting power load is essential for utilities to effectively manage their
resources, reduce operational costs, and provide improved customer service. However, the …

This paper proposes a novel clustering and dynamic recognition–based auto-reservoir
neural network (CDbARNN) for short-term load forecasting (STLF) of industrial park …