Digitalization and Advanced Control Techniques of Integrated Photovoltaic Systems
Deadline for manuscript submissions: closed (15 February 2023) | Viewed by 2441
Interests: photovoltaic (PV) systems modeling and optimization; renewable energy integration; power quality; microgrids; smart grids; artificial intelligence and machine learning applications for solar energy and PV systems
Interests: power electronics converters; renewable energy generation and integration in power systems; microgrids; energy storage and management systems; adaptive control
Interests: renewable energy integration and stabilization; voltage stability; micro grids and smart grids; robust control; electric vehicles; building energy management systems; battery energy storage systems and distributed generations
Special Issues, Collections and Topics in MDPI journals
The rapid increase in photovoltaic (PV) installation at small and large scales can pose significant technical issues related to the voltage levels and capacity of the network assets in distribution networks. Most of the equipment in energy systems is still hardwired and analogue. Therefore, limited data acquisition, and many related control actions, must be performed manually. This presents several challenges when it comes to ensuring similar system quality and efficient operations. Therefore, new solutions and digitalization of energy systems, especially PV systems, must be developed to support decision making and improve generation capacity and efficiency. Furthermore, accurate predictions and control of PV systems pave the way for digitalization of these systems. Here, machine-learning and artificial intelligence (AI)-based techniques are the main drivers of the rapid advancements in digitalization and control of PV systems.
This Special Issue aims to apply intelligence to the PV systems to create a digitalized, automated, integrated, and optimized PV systems, including (but not limited to) the following topics:
- State-of-the-art reviews on integrated PV systems and applications.
- PV systems modeling and characterization.
- On-line and off-line PV system performance forecasting methods.
- PV system sizing and optimization.
- Energy management of PV systems.
- AI, machine-learning and deep-learning applications for PV systems.
- Tools for modeling, optimizing, and controlling PV systems.
- Cybersecurity of Digital PV Systems.
- Power converter topologies for PV systems.
- Smart inverter technical standards.
- Intelligent and adaptive control methods of power converters for PV systems.
- Voltage and reactive power support using PV systems.
- Grid-following inverter controls.
- Grid monitoring and synchronization techniques for 1ph/3ph PV systems
- Fault ride-through enhancement for grid-tied PV systems
- Integration of storage batteries with PV systems.
- Integration of electrical vehicles with PV systems.
Dr. Ibrahim Anwar Ibrahim
Dr. Nabil Mohammed
Prof. Dr. Jahangir Hossain
Manuscript Submission Information
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- PV system modeling
- PV system forecasting
- PV system monitoring
- PV system controlling
- energy management
- digital PV Systems
- storage batteries
- electrical vehicles
- power converters and control
- inverter standards
- smart inverters
- voltage support
- reactive power