Fuzzy Hysteresis Current Controller for Power Quality Enhancement in Renewable Energy Integrated Clusters

Kumar, Yellapragada Venkata Pavan; Rao, Sivakavi Naga Venkata Bramareswara; Padma, K.; Reddy, Challa Pradeep; Pradeep, Darsy John; Aymen, Flah; Kraiem, Habib; Jasiński, Michał; Nikolovski, Srete

doi:10.3390/su14084851

Cited by 19 publications

(12 citation statements)

References 32 publications

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“…The hysteresis controller's input is confine within a predefined hysteresis band (h), which is accomplished by alternating the VSI states (+Vdc/−Vdc). The reference load voltages (vLaref, vLbref, vLcref) and PCC voltages (vsa, vsb, vsc) as written in equation (7) are used to provide reference signals for the hysteresis controller [154].…”

Section: Hysteresis Controlmentioning

confidence: 99%

A review on the state of the art of dynamic voltage restorer: topologies, operational modes, compensation methods, and control algorithms

Shah,

Ullah,

Nouman

et al. 2024

Eng. Res. Express

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The state-of-the-art dynamic voltage restorers (DVRs) have advanced significantly in recent years. Modern DVRs can detect voltage sags or dips on the power line in real-time and are able to rapidly inject a compensating voltage to maintain a constant voltage at the load. This helps to improve the power quality of the electrical distribution system and to protect sensitive electronic equipment from voltage fluctuations. One key development in the field of DVRs has been the use of advanced control algorithms that enable the DVR to track the voltage more accurately on the power line and to inject a compensating voltage more accurately. These algorithms can be implemented using digital signal processors (DSPs) or field-programmable gate arrays (FPGAs), which allow for fast and precise control of the DVR. Another important development has been the use of high-frequency inverters in DVRs. These inverters can operate at much higher frequencies than traditional inverters, which allows them to switch on and off more quickly and to inject a more precise compensating voltage. This can help to further improve the power quality of the electrical distribution system. Overall, the state-of-the-art DVR technology continues to evolve, and new advances are being made all the time to improve the performance and reliability of these devices.

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Section: Hysteresis Controlmentioning

confidence: 99%

A review on the state of the art of dynamic voltage restorer: topologies, operational modes, compensation methods, and control algorithms

Shah,

Ullah,

Nouman

et al. 2024

Eng. Res. Express

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show abstract

“…Each green building is considered as a single microgrid associated with its locally available renewable energy sources. This work has adopted the mathematical modeling of renewable energy sources and the conventional inverter from [19,20]. Each microgrid is designed with a controller called the local agent controller of the said microgrid.…”

Section: Description and Modeling Of The Proposed System And Its Cons...mentioning

confidence: 99%

An Adaptive Neuro-Fuzzy Control Strategy for Improved Power Quality in Multi-Microgrid Clusters

Rao¹,

Kumar

Amir

et al. 2022

IEEE Access

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Microgrids are being evolved as a potential alternative to reduce unrelenting dependency on central utility grids. Moreover, integrated multi-microgrid based clusters are forming in closed vicinities to enhance the benefits of microgrids. However, the power quality problem is one of the key issues to be solved in such systems, which is mainly caused by the rising penetration of nonlinear loads and interfacing of power electronic converters. To address this issue, this paper proposes a new control technique, named "adaptive neuro-fuzzy control strategy". This controls the inverter of each microgrid in the cluster as well as the voltage source converter based distribution static compensator located at the point of common coupling between the cluster and the utility grid. This proposed control strategy uses the advantages of both fuzzy logic and artificial neural networks, thereby effectively controls the system. The proposed technique is modelled in MATLAB/Simulink software 2021a. For the analysis, various power quality indices such as voltage sag/swell, voltage unbalance, frequency deviations, power characteristics, total harmonic distortion, and neutral current compensation are measured. These indices of the proposed controller are compared with conventional PI and fuzzy logic-based controllers in view of various key IEEE/IEC standard tolerances. From these results, the proposed controller has proved its superiority. postdoctoral fellow. He has authored/co-authored more than 60 research articles. His research interests include microgrids, electric vehicle, charging infrastructure, grid integration, energy management systems, etc.

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“…In this mathematical model, for the proposed dynamic metaheuristic FLC, the inertia weight ω is computed according to (27) and continuously optimized through the TSK-FLC as described in Section 7.…”

Section: Optimization Of the Dynamic Pso Mechanism To Tune The Propos...mentioning

confidence: 99%

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

2022

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This paper presents a systematic approach to designing a dynamic metaheuristic fuzzy logic controller (FLC) to control a piece of non-linear plant. The developed controller is a multiple-input–multiple-output (MIMO) system. However, with the proposed control mechanism is possible to adapt it to single-input–single-output (SISO) systems as well. During real-time operation, the dynamic behavior of the proposed fuzzy controller is influenced by a metaheuristic particle swarm optimization (PSO) mechanism. Nevertheless, to analyze the performance of the developed dynamic metaheuristic FLC as a piece of non-linear plant, a 1 kW four-wheel independent-drive electric rover is controlled under different road constraints. The test results show that the proposed dynamic metaheuristic FLC maintains the wheel slip ratio of all four wheels to less than 0.35 and a top recorded translational speed of 90 km/h is maintained for a fixed orientation.

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Fuzzy Hysteresis Current Controller for Power Quality Enhancement in Renewable Energy Integrated Clusters

Cited by 19 publications

References 32 publications

A review on the state of the art of dynamic voltage restorer: topologies, operational modes, compensation methods, and control algorithms

A review on the state of the art of dynamic voltage restorer: topologies, operational modes, compensation methods, and control algorithms

An Adaptive Neuro-Fuzzy Control Strategy for Improved Power Quality in Multi-Microgrid Clusters

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

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