Control Design and Parameter Tuning for Islanded Microgrids by Combining Different Optimization Algorithms

Seyedamin Valedsaravi, Abdelali El Aroudi, Jose A. Barrado-Rodrigo, Walid Issa and Luis Martínez-Salamero
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Seyedamin Valedsaravi: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain
Abdelali El Aroudi: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain
Jose A. Barrado-Rodrigo: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain
Walid Issa: Electrical Engineering Department, Sheffield Hallam University, Pond Street, Sheffield S1 1WB, UK
Luis Martínez-Salamero: Department of Electrical Electronics and Automatic Control Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain

Energies, 2022, vol. 15, issue 10, 1-25

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.

Keywords: islanded microgrid; voltage-source inverter; state-space modelling; particle swarm optimization; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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