IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p4751-d1090327.html
   My bibliography  Save this article

Damping of Frequency and Power System Oscillations with DFIG Wind Turbine and DE Optimization

Author

Listed:
  • Solomon Feleke

    (Department of Electrical and Computer Engineering, Debre Berhan University, Debre Berhan 445, Ethiopia)

  • Raavi Satish

    (Department of Electrical & Electronics Engineering, Anil Neerukonda Institute of Technology and Science, Visakhapatnam 531162, Andhra Pradesh, India)

  • Balamurali Pydi

    (Department of Electrical & Electronics Engineering, Aditya Institute of Technology & Management, Tekkali 532201, Andhra Pradesh, India)

  • Degarege Anteneh

    (Department of Electrical and Computer Engineering, Debre Berhan University, Debre Berhan 445, Ethiopia)

  • Almoataz Y. Abdelaziz

    (Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt)

  • Adel El-Shahat

    (Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA)

Abstract

Wind power is one of the most promising renewable energy resources and could become a solution to contribute to the present energy and global warming crisis of the world. The commonly used doubly fed induction generator (DFIG) wind turbines have a general trend of increasing oscillation damping. Unless properly controlled, the high penetration of wind energy will increase the oscillation and affect the control and dynamic interaction of the interconnected generators. This paper discusses power oscillation damping control in the automatic generation control (AGC) of two-area power systems with DFIG wind turbines and Matlab code/Simulink interfacing optimization methods. The differential evolution (DE) optimization technique is used to obtain the controller gain parameters. In the optimization process, a step load perturbation (SLP) of 1% has been considered in Area 1 only, and the integral of time weighted absolute error (ITAE) cost function is used. Three different test studies have been examined on the same power system model with non-reheat turbine thermal power plants. In the first case, the power system model is simulated without a controller. In Case Study 2, the system is simulated with the presence of DFIG and without a controller. In Case Study 3, the system is simulated with a PID controller and DFIG. Most of the studies available in the literature do not optimize the appropriate wind penetrating speed gain parameters for the system and do not consider the ITAE as an objective function to reduce area control error. In this regard, the main contribution and result of this paper is—with the proposed PID+DFIG optimized DE—the ITAE objective function error value in the case study without a controller being 6.7865, which is reduced to 1.6008 in the case study with PID+DFIG-optimized DE. In addition, with the proposed controller methods, the dynamic system time responses such as rise time, settling time, overshoot, and undershoot are improved for system tie-line power, change in frequency, and system area controller error. Similarly, with the proposed controller, fast system convergence and fast system oscillation damping are achieved. Generally, it is inferred that the incorporation of DFIG wind turbines in both areas has appreciably improved the dynamic performance and system stability under consideration.

Suggested Citation

  • Solomon Feleke & Raavi Satish & Balamurali Pydi & Degarege Anteneh & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "Damping of Frequency and Power System Oscillations with DFIG Wind Turbine and DE Optimization," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:4751-:d:1090327
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/4751/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/6/4751/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghaboulian Zare, Sara & Alipour, Mohammad & Hafezi, Mehdi & Stewart, Rodney A. & Rahman, Anisur, 2022. "Examining wind energy deployment pathways in complex macro-economic and political settings using a fuzzy cognitive map-based method," Energy, Elsevier, vol. 238(PA).
    2. Aiguo Tan & Xiangning Lin & Jinwen Sun & Ran Lyu & Zhengtian Li & Long Peng & Muhammad Shoaib Khalid, 2016. "A Novel DFIG Damping Control for Power System with High Wind Power Penetration," Energies, MDPI, vol. 9(7), pages 1-15, July.
    3. Ping He & Seyed Ali Arefifar & Congshan Li & Fushuan Wen & Yuqi Ji & Yukun Tao, 2019. "Enhancing Oscillation Damping in an Interconnected Power System with Integrated Wind Farms Using Unified Power Flow Controller," Energies, MDPI, vol. 12(2), pages 1-16, January.
    4. Manu Centeno-Telleria & Ekaitz Zulueta & Unai Fernandez-Gamiz & Daniel Teso-Fz-Betoño & Adrián Teso-Fz-Betoño, 2021. "Differential Evolution Optimal Parameters Tuning with Artificial Neural Network," Mathematics, MDPI, vol. 9(4), pages 1-20, February.
    5. Jian Zuo & Yinhong Li & Dongyuan Shi & Xianzhong Duan, 2017. "Simultaneous Robust Coordinated Damping Control of Power System Stabilizers (PSSs), Static Var Compensator (SVC) and Doubly-Fed Induction Generator Power Oscillation Dampers (DFIG PODs) in Multimachin," Energies, MDPI, vol. 10(4), pages 1-23, April.
    6. Solomon Feleke & Raavi Satish & Workagegn Tatek & Almoataz Y. Abdelaziz & Adel El-Shahat, 2022. "DE-Algorithm-Optimized Fuzzy-PID Controller for AGC of Integrated Multi Area Power System with HVDC Link," Energies, MDPI, vol. 15(17), pages 1-21, August.
    7. Ahmed G. Abo-Khalil & Ali S. Alghamdi & Ali M. Eltamaly & M. S. Al-Saud & Praveen R. P. & Khairy Sayed & G. R. Bindu & Iskander Tlili, 2019. "Design of State Feedback Current Controller for Fast Synchronization of DFIG in Wind Power Generation Systems," Energies, MDPI, vol. 12(12), pages 1-26, June.
    8. Faza, Ayman, 2018. "A probabilistic model for estimating the effects of photovoltaic sources on the power systems reliability," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 67-77.
    9. Devlin, Joseph & Li, Kang & Higgins, Paraic & Foley, Aoife, 2016. "The importance of gas infrastructure in power systems with high wind power penetrations," Applied Energy, Elsevier, vol. 167(C), pages 294-304.
    10. Liu, Jizhen & Yao, Qi & Hu, Yang, 2019. "Model predictive control for load frequency of hybrid power system with wind power and thermal power," Energy, Elsevier, vol. 172(C), pages 555-565.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Solomon Feleke & Balamurali Pydi & Raavi Satish & Hossam Kotb & Mohammed Alenezi & Mokhtar Shouran, 2023. "Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    2. Weichao He & Yuemin Zheng & Jin Tao & Yujuan Zhou & Jiayan Wen & Qinglin Sun, 2023. "A Novel Fractional-Order Active Disturbance Rejection Load Frequency Control Based on An Improved Marine Predator Algorithm," Sustainability, MDPI, vol. 15(13), pages 1-23, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Panapakidis, Ioannis P., 2017. "Impact of the penetration of renewables on flexibility needs," Energy Policy, Elsevier, vol. 109(C), pages 360-369.
    2. Ping He & Seyed Ali Arefifar & Congshan Li & Fushuan Wen & Yuqi Ji & Yukun Tao, 2019. "Enhancing Oscillation Damping in an Interconnected Power System with Integrated Wind Farms Using Unified Power Flow Controller," Energies, MDPI, vol. 12(2), pages 1-16, January.
    3. Jun Dong & Shengnan Li & Shuijun Wu & Tingyi He & Bo Yang & Hongchun Shu & Jilai Yu, 2017. "Nonlinear Observer-Based Robust Passive Control of Doubly-Fed Induction Generators for Power System Stability Enhancement via Energy Reshaping," Energies, MDPI, vol. 10(8), pages 1-16, July.
    4. Zhao, Yongliang & Liu, Ming & Wang, Chaoyang & Li, Xin & Chong, Daotong & Yan, Junjie, 2018. "Increasing operational flexibility of supercritical coal-fired power plants by regulating thermal system configuration during transient processes," Applied Energy, Elsevier, vol. 228(C), pages 2375-2386.
    5. Perez, Alex & Garcia-Rendon, John J., 2021. "Integration of non-conventional renewable energy and spot price of electricity: A counterfactual analysis for Colombia," Renewable Energy, Elsevier, vol. 167(C), pages 146-161.
    6. Francesco Bonavolontà & Luigi Pio Di Noia & Davide Lauria & Annalisa Liccardo & Salvatore Tessitore, 2019. "An Optimized HT-Based Method for the Analysis of Inter-Area Oscillations on Electrical Systems," Energies, MDPI, vol. 12(15), pages 1-22, July.
    7. Devine, Mel T. & Russo, Marianna, 2019. "Liquefied natural gas and gas storage valuation: Lessons from the integrated Irish and UK markets," Applied Energy, Elsevier, vol. 238(C), pages 1389-1406.
    8. Ali Mohamed Eltamaly & Mamdooh Al-Saud & Khairy Sayed & Ahmed G. Abo-Khalil, 2020. "Sensorless Active and Reactive Control for DFIG Wind Turbines Using Opposition-Based Learning Technique," Sustainability, MDPI, vol. 12(9), pages 1-14, April.
    9. Youssef Ait Ali & Mohammed Ouassaid & Zineb Cabrane & Soo-Hyoung Lee, 2023. "Enhanced Primary Frequency Control Using Model Predictive Control in Large-Islanded Power Grids with High Penetration of DFIG-Based Wind Farm," Energies, MDPI, vol. 16(11), pages 1-24, May.
    10. Chen, Qian & He, Peng & Yu, Chuanjin & Zhang, Xiaochi & He, Jiayong & Li, Yongle, 2023. "Multi-step short-term wind speed predictions employing multi-resolution feature fusion and frequency information mining," Renewable Energy, Elsevier, vol. 215(C).
    11. Omar Alrumayh & Khairy Sayed & Abdulaziz Almutairi, 2023. "LVRT and Reactive Power/Voltage Support of Utility-Scale PV Power Plants during Disturbance Conditions," Energies, MDPI, vol. 16(7), pages 1-20, April.
    12. Ahmed Sobhy & Ahmed G. Abo-Khalil & Dong Lei & Tareq Salameh & Adel Merabet & Malek Alkasrawi, 2022. "Coupling DFIG-Based Wind Turbines with the Grid under Voltage Imbalance Conditions," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    13. Stover, Oliver & Karve, Pranav & Mahadevan, Sankaran, 2023. "Reliability and risk metrics to assess operational adequacy and flexibility of power grids," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    14. Danko Vidović & Elis Sutlović & Matislav Majstrović, 2021. "A Unique Electrical Model for the Steady-State Analysis of a Multi-Energy System," Energies, MDPI, vol. 14(18), pages 1-23, September.
    15. Khaled Alshuaibi & Yi Zhao & Lin Zhu & Evangelos Farantatos & Deepak Ramasubramanian & Wenpeng Yu & Yilu Liu, 2022. "Forced Oscillation Grid Vulnerability Analysis and Mitigation Using Inverter-Based Resources: Texas Grid Case Study," Energies, MDPI, vol. 15(8), pages 1-13, April.
    16. Firouzi, Mohsen & Samimi, Abouzar & Salami, Abolfazl, 2022. "Reliability evaluation of a composite power system in the presence of renewable generations," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    17. Md. Shafiul Alam & Tanzi Ahmed Chowdhury & Abhishak Dhar & Fahad Saleh Al-Ismail & M. S. H. Choudhury & Md Shafiullah & Md. Ismail Hossain & Md. Alamgir Hossain & Aasim Ullah & Syed Masiur Rahman, 2023. "Solar and Wind Energy Integrated System Frequency Control: A Critical Review on Recent Developments," Energies, MDPI, vol. 16(2), pages 1-31, January.
    18. Lunz, Benedikt & Stöcker, Philipp & Eckstein, Sascha & Nebel, Arjuna & Samadi, Sascha & Erlach, Berit & Fischedick, Manfred & Elsner, Peter & Sauer, Dirk Uwe, 2016. "Scenario-based comparative assessment of potential future electricity systems – A new methodological approach using Germany in 2050 as an example," Applied Energy, Elsevier, vol. 171(C), pages 555-580.
    19. Solomon Feleke & Balamurali Pydi & Raavi Satish & Degarege Anteneh & Kareem M. AboRas & Hossam Kotb & Mohammed Alharbi & Mohamed Abuagreb, 2023. "DE-Based Design of an Intelligent and Conventional Hybrid Control System with IPFC for AGC of Interconnected Power System," Sustainability, MDPI, vol. 15(7), pages 1-23, March.
    20. Aliyu Sabo & Noor Izzri Abdul Wahab & Mohammad Lutfi Othman & Mai Zurwatul Ahlam Mohd Jaffar & Hakan Acikgoz & Hamzeh Beiranvand, 2020. "Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers," Sustainability, MDPI, vol. 12(22), pages 1-42, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:4751-:d:1090327. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.