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Adaptive Synthetic Inertia Control Framework for Distributed Energy Resources in Low-Inertia Microgrid (CROSBI ID 310306)

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Nema, Sumit ; Prakash, Vivek ; Pandžić, Hrvoje Adaptive Synthetic Inertia Control Framework for Distributed Energy Resources in Low-Inertia Microgrid // IEEE access, 10 (2022), 54969-54979. doi: 10.1109/ACCESS.2022.3177661

Podaci o odgovornosti

Nema, Sumit ; Prakash, Vivek ; Pandžić, Hrvoje

engleski

Adaptive Synthetic Inertia Control Framework for Distributed Energy Resources in Low-Inertia Microgrid

Bulk integration of Distributed Energy Resources (DERs) into the power grids reduces the system’s inherent inertial response.The reduced inertial response causes a high Rate-of-Change-of-Frequency (RoCoF) and poses formidable operational challenges for the grid frequency stability. Interconnections around the world comprehend the role and value of the Synthetic Inertia Control (SIC), which is considered as a subset of the Fast Frequency Response (FFR) and as one of the potential solutions to arrest high RoCoF in low- inertia power systems. This paper proposes an intelligent SIC model with an adaptive Fuzzy Logic Controller for a low-inertia microgrid. The proposed Fuzzy-SIC (FSIC) design optimizes the DER output to fulfill the FFR requirements of the system for various operating conditions. The particle swarm optimization algorithm is applied to tune the SIC unit parameters along with the secondary Proportional-Integral-Derivative control. The proposed approach is examined in a control area with distinct degrees of DERs and load. Case studies and numerical results demonstrate about 87% improvement in RoCoF and frequency nadir in comparison to the system without a synthetic inertia emulation. Furthermore, the robustness of the proposed approach is evaluated using various case studies and a time-domain analysis is conducted to demonstrate the impact of incremental SIC parameters on the system parameters.

Distributed energy resources ; dynamic frequency control ; fast frequency response ; fuzzy-logic ; low-inertia microgrid ; particle-swarm optimization ; synthetic inertia

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Podaci o izdanju

10

2022.

54969-54979

objavljeno

2169-3536

10.1109/ACCESS.2022.3177661

Povezanost rada

Elektrotehnika

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