2024 : 2 : 23
Hassan Bevrani

Hassan Bevrani

Academic rank: Professor
Education: PhD.
ScopusId: 55913436700
Faculty: Faculty of Engineering
Address: Dept. Of Electrical and Computer Eng, University of Kurdistan, Allameh Hamdi Blvd, Sanandaj PO Box 416, P. C: 66177-15175, Kurdistan, Iran
Phone: +98-87-33624001


Designing a Self-Tuning Frequency Controller Based on ANN for an Isolated Microgrid
Artificial neural network, Selftuning Microgrid, Distributed Generation
Researchers Hassan Bevrani ، Shoresh shokoohi ، Farshid Habibi


Increasing electrical energy demand, as well as fossil fuel shortages and environmental concerns have caused to use uncommon sources such as distributed generations (DGs) and renewable energy sources (RESs) into modern power systems. A Microgrid (MG) system consists of several DGs and RESs which is responsible to provide both electrical and heat powers for local loads. Due to the MGs nonlinearity/complexity which is imposed to the conventional power systems, classical and nonflexible control structures may not represent desirable performance over a wide range of operating conditions. Therefore, more flexible/intelligent control methods are needed most of the past. Hence, in this paper addresses to design an online/self-tuning PIcontroller based on artificial neural networks (ANNs) for optimal regulating the MG systems frequency.