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New Hybrid Deep Neural Architectural Search-Based Ensemble Reinforcement Learning Strategy for Wind Power Forecasting
(IEEE, 2022-01)
- article
Wind power instability and inconsistency involve the reliability of renewable power energy, the safety of the transmission system, the electrical grid stability and the rapid developments of energy market. The study on ...
Solar irradiance forecasting using a novel hybrid deep ensemble reinforcement learning algorithm
(Elsevier, 2022-12-01)
- article
Solar irradiance forecasting is a major priority for the power transmission systems in order to generate and incorporate the performance of massive photovoltaic plants efficiently. As such, prior forecasting techniques ...
An advanced short-term wind power forecasting framework based on the optimized deep neural network models
(Elsevier, 2022-10)
- article
With the continued growth of wind power penetration into conventional power grid systems, wind power forecasting plays an increasingly competitive role in organizing and deploying electrical and energy systems. The wind ...
A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting
(IEEE, 2021-03-12)
- article
The problem of electricity load forecasting has emerged as an essential topic for power systems and electricity markets seeking to minimize costs. However, this topic has a high level of complexity. Over the past few years, ...
Towards novel deep neuroevolution models: chaotic levy grasshopper optimization for short-term wind speed forecasting
(Springer, 2022-08-01)
- article
High accurate wind speed forecasting plays an important role in ensuring the sustainability of wind power utilization. Although deep neural networks (DNNs) have been recently applied to wind time-series datasets, their ...