The Application of Machine Learning in Electrical Drive Renewable Energy Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".
Deadline for manuscript submissions: closed (20 January 2022) | Viewed by 3176
Special Issue Editor
Special Issue Information
Dear Colleagues,
Machine learning in electrical drive renewable energy systems has been broadly implemented in forecasting of energy in power systems and various industrial applications. During the past few decades, there has been a vast increase in the development and implementation of different types of machine learning models in energy systems. Machine learning models are also broadly applied in power-electronic-based industrial drive systems. This includes speed and torque control of various dc and ac drives, feedback control of converter, tuning of offline P-I and P-I-D, nonlinearity compensation, online and offline computing, modeling, estimation of parameters, performance optimization of drive systems based on online finding, assessment for distorted waves, and many more. There is also a development in the accuracy, robustness, precision of the machine learning models in the energy systems by using various hybrid models. Hybridization is found to be more beneficial for the development of estimation of various models, specifically for implementing various renewable energy technologies. Depending on the seasonal condition, machine learning has the capability to provide sensible and necessary assessment for a residence or building for power generation and it can report on when it will have to access the power from the grid. However, estimations of the demand of energy by implementing hybrid models using methods of machine learning have largely impacted the energy efficiency, controllability along with sustainability.
Dr. Manoj Kumar Sahu
Guest Editor
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Keywords
- power system
- solar energy
- wind energy
- industrial drives
- electrical machines
- machine learning
- hybrid model
- energy system
- multi-level inverter
