Frequency regulation in a microgrid integrating redox flow battery by utilizing an optimal predictive control approach

When considering the frequency stability issues brought on by load shifts in a microgrid ( μ G) due to a significant integration of fluctuating renewable energy source-based generators and an inherent low inertia, energy storage units (ESUs) are unavoidable. The ESUs can immediately charge or discha...

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Bibliographic Details
Published in:Electrical engineering Vol. 106; no. 4; pp. 4257 - 4275
Main Authors: Khokhar, Bhuvnesh, Singh Parmar, K. P.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024
Springer Nature B.V
Subjects:
Closed loops
Controllers
Cost function
Distributed generation
Dynamic response
Economics and Management
Effectiveness
Electrical Engineering
Electrical loads
Electrical Machines and Networks
Energy Policy
Engineering
Frequency stability
Optimization algorithms
Original Paper
Power Electronics
Predictive control
Renewable energy sources
Robust control
Statistical analysis
Storage units
Cyclical parthenogenesis algorithm
Intelligent model predictive control
Load frequency control
Standalone microgrid
Redox flow battery
ISSN:0948-7921, 1432-0487
Online Access:Get full text
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Summary:When considering the frequency stability issues brought on by load shifts in a microgrid ( μ G) due to a significant integration of fluctuating renewable energy source-based generators and an inherent low inertia, energy storage units (ESUs) are unavoidable. The ESUs can immediately charge or discharge to make up for any shifts in load in the μ G since they react more quickly. This research investigates how a redox flow battery unit (RFBU) impacts the dynamic responses of a standalone μ G (S μ G) in this respect. As the secondary controller, an optimal intelligent model predictive control (iMPC) approach is presented. The cyclical parthenogenesis algorithm is implemented to improve the tuning parameter ( τ w ) in the iMPC cost function to demonstrate an optimal performance of the recommended control approach. The effectiveness of the iMPC approach is contrasted with that of other well-known control approaches. The simulation findings clearly demonstrate the impact of RFBU integration in the S μ G and the capability of the recommended iMPC approach in terms of improved dynamic responses and their transient characteristics. As a consequence, the peak value of the S μ G dynamic response improves by 70.53%, and the settling time improves by 82.26%. The suggested control approach’s sensitivity to the S μ G parametric uncertainties is also justified. The closed-loop stability of the suggested approach is also established. The effectiveness of the proposed iMPC approach and the impact of the RFBU integration are then confirmed by statistical analysis.
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ISSN:0948-7921
1432-0487
DOI:10.1007/s00202-023-02222-6