LAPSE:2023.13246
Published Article

LAPSE:2023.13246
Control Design and Parameter Tuning for Islanded Microgrids by Combining Different Optimization Algorithms
March 1, 2023
Abstract
Load and supply parameters may be uncertain in microgrids (MGs) due for instance to the intermittent nature of renewable energy sources among others. Guaranteeing reliable and stable MGs despite parameter uncertainties is crucial for their correct operation. Their stability and dynamical features are directly related to the controllers’ parameters and power-sharing coefficients. Hence, to maintain power good quality within the desirable range of system parameters and to have a satisfactory response to sudden load changes, careful selection of the controllers and power-sharing coefficients are necessary. In this paper, a simple design approach for the optimal design of controllers’ parameters is presented in an islanded MG. To that aim, an optimization problem is formulated based on a small-signal state-space model and solved by three different optimization techniques including particle swarm optimization (PSO), genetic algorithm (GA), and a proposed approach based on the combination of both PSO and GA. The optimized coefficients are selected to guarantee desirable static and dynamic responses in a wide range of operations regardless of the number of inverters, system configuration, output impedance differences, and load types. Through the proposed design and tuning method, the performance of the MG is improved as compared to those obtained using state-of-art techniques. This fact is demonstrated by using numerical simulations performed on a detailed model implemented in PSIM© software.
Load and supply parameters may be uncertain in microgrids (MGs) due for instance to the intermittent nature of renewable energy sources among others. Guaranteeing reliable and stable MGs despite parameter uncertainties is crucial for their correct operation. Their stability and dynamical features are directly related to the controllers’ parameters and power-sharing coefficients. Hence, to maintain power good quality within the desirable range of system parameters and to have a satisfactory response to sudden load changes, careful selection of the controllers and power-sharing coefficients are necessary. In this paper, a simple design approach for the optimal design of controllers’ parameters is presented in an islanded MG. To that aim, an optimization problem is formulated based on a small-signal state-space model and solved by three different optimization techniques including particle swarm optimization (PSO), genetic algorithm (GA), and a proposed approach based on the combination of both PSO and GA. The optimized coefficients are selected to guarantee desirable static and dynamic responses in a wide range of operations regardless of the number of inverters, system configuration, output impedance differences, and load types. Through the proposed design and tuning method, the performance of the MG is improved as compared to those obtained using state-of-art techniques. This fact is demonstrated by using numerical simulations performed on a detailed model implemented in PSIM© software.
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Keywords
Genetic Algorithm, islanded microgrid, Particle Swarm Optimization, state-space modelling, voltage-source inverter
Subject
Suggested Citation
Valedsaravi S, El Aroudi A, Barrado-Rodrigo JA, Issa W, Martínez-Salamero L. Control Design and Parameter Tuning for Islanded Microgrids by Combining Different Optimization Algorithms. (2023). LAPSE:2023.13246
Author Affiliations
Valedsaravi S: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
El Aroudi A: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
Barrado-Rodrigo JA: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
Issa W: Electrical Engineering Department, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK [ORCID]
Martínez-Salamero L: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
El Aroudi A: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
Barrado-Rodrigo JA: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
Issa W: Electrical Engineering Department, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK [ORCID]
Martínez-Salamero L: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain [ORCID]
Journal Name
Energies
Volume
15
Issue
10
First Page
3756
Year
2022
Publication Date
2022-05-19
ISSN
1996-1073
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Original Submission
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PII: en15103756, Publication Type: Journal Article
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LAPSE:2023.13246
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https://doi.org/10.3390/en15103756
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