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Frequency Excursion Mitigation in a Multi-source Islanded Energy System Using Meta-Heuristic Optimization Strategies

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dc.contributor.author Mathur, Hitesh Dutt
dc.date.accessioned 2023-02-17T04:50:10Z
dc.date.available 2023-02-17T04:50:10Z
dc.date.issued 2020
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/9182006
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9297
dc.description.abstract Distributed Energy Resources and Electric vehicles are getting more popular in the energy market. They are emerging as promising concepts that can bring a revolution in the field of energy resources and transportation systems. The integration of different renewable energy resources and electric vehicles leads to a comprehensive microgrid (MG). It is a fact that an increase in power demand leads to a drop in power frequency and vice-versa, which adversely affects the power quality of the system. Therefore, the primary idea of this research work is to regulate frequency by controlling the wind power and available EV power. In this paper, a detailed MG model is simulated in MATLAB/Simulink with wind and EV as one of the sources using fractional order PID (FOPID) controller. Further, parameters of FOPID controller is optimized by using Ant Colony Optimization(ACO) and Particle Swarm Optimization (PSO). The frequency responses, wind power, and EV power results are compared for three cases; FOPID without optimization, ACO based FOPID, and PSO based FOPID. The generalized wind model and total energy model (TEM) are used for simulating wind source and EV, respectively. Optimizer based FOPID controller provides a better response for the defined objective function. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Microgrid en_US
dc.subject Electric vehicles en_US
dc.subject Frequency Regulation en_US
dc.subject Ant Colony Optimization (ACO) en_US
dc.subject Particle Swarm Optimization en_US
dc.subject FOPID controller en_US
dc.title Frequency Excursion Mitigation in a Multi-source Islanded Energy System Using Meta-Heuristic Optimization Strategies en_US
dc.type Article en_US


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