A comprehensive review of the load forecasting techniques using single and hybrid predictive models
A Al Mamun, M Sohel, N Mohammad… - IEEE …, 2020 - ieeexplore.ieee.org
Load forecasting is a pivotal part of the power utility companies. To provide load-shedding
free and uninterrupted power to the consumer, decision-makers in the utility sector must …
free and uninterrupted power to the consumer, decision-makers in the utility sector must …
Electrical load forecasting models for different generation modalities: a review
The intelligent management of power in electrical utilities depends on the high significance
of load forecasting models. Since the industries are digitalized, power generation is …
of load forecasting models. Since the industries are digitalized, power generation is …
An efficient deep learning framework for intelligent energy management in IoT networks
T Han, K Muhammad, T Hussain… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Green energy management is an economical solution for better energy usage, but the
employed literature lacks focusing on the potentials of edge intelligence in controllable …
employed literature lacks focusing on the potentials of edge intelligence in controllable …
Green energy aware and cluster based communication for future load prediction in IoT
Green energy management has become a critical economic solution for efficient energy
consumption; however, the available literature is deficient in emphasising the importance of …
consumption; however, the available literature is deficient in emphasising the importance of …
Short-term load forecasting of multi-energy in integrated energy system based on multivariate phase space reconstruction and support vector regression mode
In order to alleviate the energy crisis and improve the energy utilization rate, the integrated
energy system (IES) has become an important way of energy utilization. IES integrates …
energy system (IES) has become an important way of energy utilization. IES integrates …
A novel short receptive field based dilated causal convolutional network integrated with Bidirectional LSTM for short-term load forecasting
Abstract The Short-Term Load Forecasting (STLF) is a pre-eminent task for reliable power
generation and electrical load dispatching in the power system. Numerous machine …
generation and electrical load dispatching in the power system. Numerous machine …
A reinforcement learning-based network traffic prediction mechanism in intelligent internet of things
Intelligent Internet of Things (IIoT) is comprised of various wireless and wired networks for
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
A short-term load forecasting model based on mixup and transfer learning
Y Lu, G Wang, S Huang - Electric Power Systems Research, 2022 - Elsevier
When the amount of historical load data is insufficient, the use of deep learning for load
forecasting is prone to overfitting. This paper proposes a short-term electric load forecasting …
forecasting is prone to overfitting. This paper proposes a short-term electric load forecasting …
Intelligent load forecasting and renewable energy integration for enhanced grid reliability
The integration of Renewable Energy Resources (RERs) into electrical grids introduces
significant challenges concerning the reliability and stability of the grid. This paper focuses …
significant challenges concerning the reliability and stability of the grid. This paper focuses …
[HTML][HTML] Short-term load and price forecasting using artificial neural network with enhanced Markov chain for ISO New England
Nowadays, forecasting methods have gained significant attention, particularly with the
design and development of energy systems. In fact, accurate load and price forecasting is …
design and development of energy systems. In fact, accurate load and price forecasting is …