Prospective methodologies in hybrid renewable energy systems for energy prediction using artificial neural networks
This paper presents a comprehensive review of machine learning (ML) based approaches,
especially artificial neural networks (ANNs) in time series data prediction problems …
especially artificial neural networks (ANNs) in time series data prediction problems …
Internet of things (IOT) based machine learning techniques for wind energy harvesting
R Kalpana, SV, R Lokanadham… - Electric Power …, 2023 - Taylor & Francis
Abstract The Internet of Things (IoT) is a significant avenue for research in renewable
energy, particularly in enhancing windmill performance, reducing wind energy costs, and …
energy, particularly in enhancing windmill performance, reducing wind energy costs, and …
Electrical power generation forecasting from renewable energy systems using artificial intelligence techniques
M Abdul Baseer, A Almunif, I Alsaduni, N Tazeen - Energies, 2023 - mdpi.com
Renewable energy (RE) sources, such as wind, geothermal, bioenergy, and solar, have
gained interest in developed regions. The rapid expansion of the economies in the Middle …
gained interest in developed regions. The rapid expansion of the economies in the Middle …
Effective Stability Improvement of Multi-Microgrids Assisted Diversified Wind Energy Resources
Instability of multi-microgrids is a challenging issue for sustainable power delivery. Wind is
considered as a renewable energy resource which has abundant intermittencies. Voltage …
considered as a renewable energy resource which has abundant intermittencies. Voltage …
Micro-Grid Stability Improvement Using Static Synchronous Compensator Assisted with Battery Energy Storage System
Integration of distributed generation (DG) with a distribution network is essential for the best
utilization of renewable resources in better economics and clean environmental aspect …
utilization of renewable resources in better economics and clean environmental aspect …