Frequency Stability Enhancement of Microgrid Using Optimization Techniques-Based Adaptive Virtual Inertia Control

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dc.contributor.authorYegon, Philemon
dc.contributor.authorSingh, Mukhtiar
dc.date.accessioned2023-11-21T08:38:27Z
dc.date.available2023-11-21T08:38:27Z
dc.date.issued2023-11
dc.descriptionDescriptionen_US
dc.description.abstractIn recent years, a sharp increase in integration of renewable energy sources (RESs) in power system network has been observed. High penetration of RES interfaced with power electronics converters-inverters with reduced or no inherent inertia compromises modern power system’s overall stability. Due to low inertia, voltage and frequency deviations far of the allowable threshold occur. To overcome this challenge, an adaptive inertia control strategy based on optimization technique is proposed. Te improved particle swarm optimization (PSO) and genetic algorithm (GA) optimization techniques-based PID controller has been used to generate the appropriate virtual inertia coefcient for efective emulation of inertia in the presence of energy storage system. Te conventional PSO sufers local optima stagnation, resulting in premature convergence during searching process in order to achieve global and local position. To address this issue, the velocity update equation was modifed on inertia weight (w) using an additional exponential term with linear decreasing inertia weight PSO (LDIW-PSO). In this paper, exponential power is taken strategically instead of squaring it in order to reduce the number of iterations for faster convergence. Finally, a microgrid based on wind and solar energy is simulated using MATLAB/Simulink where three cases, 2% disturbance, 3% disturbance, and 4% disturbance, have been considered. Here, the evaluation of proposed system is carried out based on four main performance indices (ITAE, IAE, ISE, and ITSE). Furthermore, validation was done through hardware prototype to get experimental results in real time. Te results from MATLAB simulation and experimental setup are in sync.en_US
dc.identifier.citationYegon, P., & Singh, M. (2023). Frequency Stability Enhancement of Microgrid Using Optimization Techniques-Based Adaptive Virtual Inertia Control. International Transactions on Electrical Energy Systems, 2023.en_US
dc.identifier.urihttps://doi.org/10.1155/2023/2121721
dc.identifier.urihttp://ir-library.ku.ac.ke/handle/123456789/27162
dc.language.isoenen_US
dc.publisherHindawien_US
dc.titleFrequency Stability Enhancement of Microgrid Using Optimization Techniques-Based Adaptive Virtual Inertia Controlen_US
dc.typeArticleen_US
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