Improved small signal stability of microgrid—a droop control scheme with SMC

The power electronic interface is a significant part of the energy conversion systems based on renewable sources. Due to the extensive infiltration of renewable sources into power systems, it is essential to study the droop control methods used for the control of inverters that are operated in paral...

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Bibliographic Details
Published in:Electrical engineering 2022-08, Vol.104 (4), p.2569-2587
Main Authors: Krishnan, U. Binu, Mija, S. J., Cheriyan, Elizabeth P.
Format: Article
Language:English
Subjects:
Communications systems
Control methods
Distributed generation
Economics and Management
Electrical Engineering
Electrical Machines and Networks
Energy conversion
Energy Policy
Engineering
Maximum power
Original Paper
Parameters
Particle swarm optimization
Performance enhancement
Perturbation
Power Electronics
Sliding mode control
Transient performance
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Summary:The power electronic interface is a significant part of the energy conversion systems based on renewable sources. Due to the extensive infiltration of renewable sources into power systems, it is essential to study the droop control methods used for the control of inverters that are operated in parallel. The droop controllers are simple and require no communication system. However, they offer poor transient performance in its conventional form. In this paper, a strategy is propounded to improve the performance of the droop control method by combining it with virtual impedance, dynamic droop gains, and sliding mode control. The small signal model of a droop-controlled microgrid system is developed in the standard state space form. The controller parameters are optimally tuned by particle swarm optimization, ensuring stability. These parameters are also optimized for achieving maximum power sharing capability without affecting stability. The performance of the put forward control strategy is validated by examining the system response when there is a small perturbation in load current.
ISSN:0948-7921
1432-0487
DOI:10.1007/s00202-022-01494-8