Performance analysis of buck converter with fractional PID controller using hybrid technique

Sangeetha, S.; Revathi, B. Sri; Balamurugan, K.; G., Suresh

doi:10.1016/j.robot.2023.104515

Cited by 12 publications

(3 citation statements)

References 33 publications

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“…is all considered when determining the vehicle density and traffic flow. [18,19] Depending on the traditional statistics of region-wise vehicle density under night and day, the entire area is separated into three zones. [20,21] Zone-wise allocation distributes the CS to serve the greatest user count in urban regions equally.…”

Section: Structure Of Locating the Fcs And Pv With Bes In Distributio...mentioning

confidence: 99%

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Ranjith Kumar,

Vallimurugan

2023

Energy Tech

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Proper planning for electric vehicle (EV) charging stations, as well as the necessary network development, is critical for the continued growth of EVs and conventional loads. This article proposes a hybrid method for the allocation of fast‐charging stations (FCSs) and photovoltaic (PV) with battery energy storage (BES) and scheduling. The proposed hybrid technique is the wrapper of golden jackal optimization (GJO) and random forest algorithms (RFA), commonly named the GJO–RFA technique. Using the GJO approach, the allocation and EV assignment problems are resolved. RFA is used to address EV, traffic flow, and PV‐related uncertainties. The objective of the proposed approach is to minimize the loss of energy, investments, index of voltage deviation, and operation and maintenance costs of FCS, PV, and BES. The associated important factors are also assessed, including the number of charging ports, FCS capacity, and EV flow caught using a FCS. As a test example, a 33‐node radial distribution network with the appropriate traffic network is used. For the final problem, the proposed approach to minimal energy loss is 2622.7270 kWh. By then, the performance of the proposed approach is executed in MATLAB, and it is contrasted with other existing techniques. The result shows that the proposed method‐related energy loss is less than existing approaches.

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Section: Structure Of Locating the Fcs And Pv With Bes In Distributio...mentioning

confidence: 99%

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Ranjith Kumar,

Vallimurugan

2023

Energy Tech

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“…While PID controllers offer desirable advantages and excel in systems resistant to measurement noise, they prove insufficient in applications demanding higher precision across a broader frequency range [ 19 , 20 ]. Additionally, PID controllers struggle to handle unexpected conditions effectively, such as rapid load changes, input voltage changes, and parametric fluctuations.…”

Section: Introductionmentioning

confidence: 99%

Disturbance rejecting PID-FF controller design of a non-ideal buck converter using an innovative snake optimizer with pattern search algorithm

Ersali,

Hekimoglu,

Yilmaz

et al. 2024

Heliyon

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“…Similarly, in Sangeetha et al (2023), a FOPID controller has been optimized for a DC-DC buck converter using a hybrid of Golden Jackal Optimization (GJO) and Capuchin Search Algorithm (CapSA), which they proposed in their study. They managed to improve the efficiency by 12.9% compared to the second-best method in their study, which is the genetic algorithm (GA).…”

Section: Introductionmentioning

confidence: 99%

FOPID Controller Design for a Buck Converter System Using a Novel Hybrid Cooperation Search Algorithm with Pattern Search for Parameter Tuning

ERSALI,

HEKİMOĞLU

2023

Gazi University Journal of Science Part A: Engineering and Innovation

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This research introduces a novel metaheuristic algorithm, OCSAPS, representing an upgraded cooperation search algorithm (CSA) version. OCSAPS incorporates opposition-based learning (OBL) and pattern search (PS) algorithms. The proposed algorithm's application aims to develop a fractional order proportional-integral-derivative (FOPID) controller tailored for a buck converter system. The efficacy of the proposed algorithm is assessed by statistical boxplot and convergence response analyses. Furthermore, the performance of the OCSAPS-based FOPID-controlled buck converter system is benchmarked against CSA, Harris hawk optimization (HHO), and genetic algorithm (GA). This comparative analysis encompasses transient and frequency responses, performance indices, and robustness analysis. The outcomes of this comparison highlight the distinctive advantages of the proposed approach-based system. Moreover, the proposed approach's performance was compared with six other approaches used to control buck converter systems similarly regarding both time and frequency domain responses. Overall, the findings underscore the efficacy of the OCSAPS algorithm as a robust solution for designing FOPID controllers in buck converter systems.

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Performance analysis of buck converter with fractional PID controller using hybrid technique

Cited by 12 publications

References 33 publications

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

A Hybrid Technique for Optimal Placement of Fast‐Charging Stations of Electric Vehicles for the Reliability of Distribution Network

Disturbance rejecting PID-FF controller design of a non-ideal buck converter using an innovative snake optimizer with pattern search algorithm

FOPID Controller Design for a Buck Converter System Using a Novel Hybrid Cooperation Search Algorithm with Pattern Search for Parameter Tuning

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