Enhancement of Frequency Control for Stand-Alone Multi-Microgrids

This paper presents dual-stage fractional order PID controller to enhance the primary frequency regulation of interconnected multi- \mu grids in standalone mode. A rational, non-integer ordered calculus-based controller is assessed via a single-area microgrid system pursued by a two-area microgrid t...

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Bibliographic Details
Published in:IEEE access 2021, Vol.9, p.79128-79142
Main Authors: Singh, Kavita, Amir, Mohammad, Ahmad, Furkan, Refaat, Shady S.
Format: Article
Language:English
Subjects:
Algorithms
Blades
Controllers
Damping
Deloaded tidal turbines
Diesel engines
Distributed generation
Electric power generation
Evolutionary algorithms
fractional order controller
Frequency control
Generators
Genetic algorithms
microgrid
Microgrids
Particle swarm optimization
Power generation
Power plants
Proportional integral derivative
Regulation
System effectiveness
Tidal energy
Tidal power
tidal power plant
Tidal power plants
Turbines
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Summary:This paper presents dual-stage fractional order PID controller to enhance the primary frequency regulation of interconnected multi- \mu grids in standalone mode. A rational, non-integer ordered calculus-based controller is assessed via a single-area microgrid system pursued by a two-area microgrid to integrate a tidal power plant (TPP). Additionally, it is employed with conventional units in frequency control to certify system steadiness. Thus, a strategy to showcase the contribution of TPP in frequency regulation with the integration of the diesel engine power plant is proposed. Also, the proposed methodology shows the support of TPP in primary frequency regulation strategies such as inertia, damping control, and supplementary control with deloading activity. For getting superior outcomes and enhanced steadiness of the microgrid, the controller gains are streamlined utilizing an imperialist competitive algorithm (ICA). To demonstrate the efficiency of ICA, The obtained results are compared with the genetic algorithm and particle swarm optimization algorithm. The proposed investigation is conducted in single-area and two-area microgrid systems through MATLAB simulation verification. The obtained results prove the effectiveness of the proposed methodology.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3083960