Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM
The stability of the control grid is a critical prerequisite for a safe and efficient power system service. A thorough knowledge of the effects of the power system volatility is essential for the effective study and control of power systems. This paper presents the simulation outcome of a multimachi...
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MDPI AG
2020-09-01
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Series: | Energies |
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Online Access: | https://www.mdpi.com/1996-1073/13/18/4707 |
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author | Varun Kumar Ajay Shekhar Pandey Sunil Kumar Sinha |
author_facet | Varun Kumar Ajay Shekhar Pandey Sunil Kumar Sinha |
author_sort | Varun Kumar |
collection | DOAJ |
description | The stability of the control grid is a critical prerequisite for a safe and efficient power system service. A thorough knowledge of the effects of the power system volatility is essential for the effective study and control of power systems. This paper presents the simulation outcome of a multimachine power network implemented by a wind farm (WF) utilizing a static synchronous compensator (STATCOM) for better stability control objectives. A similarly aggregated double-fed induction generator (DFIG) powered by a gearbox analogy with an equally aggregated wind turbine (WT) determines the operating output of the wind farm. A proportional–integral–derivative controller (PID)-based damping controller, PID including Fuzzy Logic Controller (FLC), and an adaptive network-based fuzzy inference system (ANFIS) controller of the proposed SATCOM are intended to add sufficient damping properties to the dominating modes of the examined system during diverse working circumstances. To assess the feasibility of the suggested control schemes, a frequency-domain method concentrated on a linearized mathematical structure layout utilizing a time-domain strategy centered on a nonlinear configuration of the device that is subjected to severe fault on the attached bus was carried out consistently. A STATCOM damping controller is configured using the ANFIS method to apply appropriate damping properties to the device’s decisive modes being evaluated under various test conditions. From the findings of the comparative simulation, it can be inferred that the suggested STATCOM along with the planned ANFIS is seen as comparable to STATCOM with PID and STATCOM with PID plus FLC to increase the stability of the studied device. |
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institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-03-10T16:26:39Z |
publishDate | 2020-09-01 |
publisher | MDPI AG |
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series | Energies |
spelling | doaj.art-994927f81e1d467097683bf93075fba12023-11-20T13:10:06ZengMDPI AGEnergies1996-10732020-09-011318470710.3390/en13184707Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOMVarun Kumar0Ajay Shekhar Pandey1Sunil Kumar Sinha2Electrical Engineering Department, KNIT, Sultanpur 228118, IndiaElectrical Engineering Department, KNIT, Sultanpur 228118, IndiaElectrical Engineering Department, KNIT, Sultanpur 228118, IndiaThe stability of the control grid is a critical prerequisite for a safe and efficient power system service. A thorough knowledge of the effects of the power system volatility is essential for the effective study and control of power systems. This paper presents the simulation outcome of a multimachine power network implemented by a wind farm (WF) utilizing a static synchronous compensator (STATCOM) for better stability control objectives. A similarly aggregated double-fed induction generator (DFIG) powered by a gearbox analogy with an equally aggregated wind turbine (WT) determines the operating output of the wind farm. A proportional–integral–derivative controller (PID)-based damping controller, PID including Fuzzy Logic Controller (FLC), and an adaptive network-based fuzzy inference system (ANFIS) controller of the proposed SATCOM are intended to add sufficient damping properties to the dominating modes of the examined system during diverse working circumstances. To assess the feasibility of the suggested control schemes, a frequency-domain method concentrated on a linearized mathematical structure layout utilizing a time-domain strategy centered on a nonlinear configuration of the device that is subjected to severe fault on the attached bus was carried out consistently. A STATCOM damping controller is configured using the ANFIS method to apply appropriate damping properties to the device’s decisive modes being evaluated under various test conditions. From the findings of the comparative simulation, it can be inferred that the suggested STATCOM along with the planned ANFIS is seen as comparable to STATCOM with PID and STATCOM with PID plus FLC to increase the stability of the studied device.https://www.mdpi.com/1996-1073/13/18/4707DFIG-based wind farmthree-machine nine-bus systemSTATCOMstabilityfuzzy logic controlleradaptive network-based fuzzy inference system (ANFIS) |
spellingShingle | Varun Kumar Ajay Shekhar Pandey Sunil Kumar Sinha Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM Energies DFIG-based wind farm three-machine nine-bus system STATCOM stability fuzzy logic controller adaptive network-based fuzzy inference system (ANFIS) |
title | Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM |
title_full | Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM |
title_fullStr | Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM |
title_full_unstemmed | Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM |
title_short | Stability Improvement of DFIG-Based Wind Farm Integrated Power System Using ANFIS Controlled STATCOM |
title_sort | stability improvement of dfig based wind farm integrated power system using anfis controlled statcom |
topic | DFIG-based wind farm three-machine nine-bus system STATCOM stability fuzzy logic controller adaptive network-based fuzzy inference system (ANFIS) |
url | https://www.mdpi.com/1996-1073/13/18/4707 |
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