IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7478-d939067.html
   My bibliography  Save this article

Optimal Allocation of Distributed Thyristor Controlled Series Compensators in Power System Considering Overload, Voltage, and Losses with Reliability Effect

Author

Listed:
  • Mohsen Khalili

    (CTIF Global Capsule, Department of Business Development and Technology, Aarhus University, Herning 7400, Denmark)

  • Touhid Poursheykh Aliasghari

    (School of Industrial and Information Engineering, Politecnico di Milano, 20133 Milan, Italy)

  • Ebrahim Seifi Najmi

    (Roshdieh Higher Institute of Education, Tabriz 5166616471, Iran)

  • Almoataz Y. Abdelaziz

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

  • A. Abu-Siada

    (Electrical and Computer Engineering Discipline, Curtin University, Perth, WA 6102, Australia)

  • Saber Arabi Nowdeh

    (Golestan Technical and Vocational Training Center, Golestan 87349-49318, Iran)

Abstract

In this paper, optimal allocation of a distributed thyristor-controlled series compensator (DTCSC) in a power system is presented to minimize overload, voltage deviations, and power losses while improving system reliability. The decision variable was defined as the optimal reactance of the DTCSC in the power system, which was determined using a new meta-heuristic algorithm named the improved equilibrium optimization algorithm (IEOA). A nonlinear inertia weight reduction strategy was used to improve the performance of traditional EOA in preventing premature convergence and facilitate a quick global optimum solution. The effect of system critical line outage was evaluated for each of the considered goals. To evaluate the effectiveness of the proposed methodology, IEOA capability was compared with particle swarm optimization (PSO) and manta ray foraging optimizer (MRFO) methods. Simulations were carried out considering different scenarios on 14- and 118-bus test systems. The results showed that, for all scenarios, optimal allocation of DTCSC could result in a significant reduction in overloading, voltage deviation of network buses, as well as power losses under the condition of line outage, due to the optimal injection of reactive power. In all investigated scenarios, our results attested to the superiority of the IEOA over the traditional EOA, PSO, and MRFO in achieving a better value for the objective function. In addition, the results showed that improving reliability in the objective function could eliminate overloading, and hence, introduce further improvement in each of the objectives.

Suggested Citation

  • Mohsen Khalili & Touhid Poursheykh Aliasghari & Ebrahim Seifi Najmi & Almoataz Y. Abdelaziz & A. Abu-Siada & Saber Arabi Nowdeh, 2022. "Optimal Allocation of Distributed Thyristor Controlled Series Compensators in Power System Considering Overload, Voltage, and Losses with Reliability Effect," Energies, MDPI, vol. 15(20), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7478-:d:939067
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7478/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/20/7478/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Naderipour, Amirreza & Abdul-Malek, Zulkurnain & Nowdeh, Saber Arabi & Ramachandaramurthy, Vigna K. & Kalam, Akhtar & Guerrero, Josep M., 2020. "Optimal allocation for combined heat and power system with respect to maximum allowable capacity for reduced losses and improved voltage profile and reliability of microgrids considering loading condi," Energy, Elsevier, vol. 196(C).
    2. Subrat Kumar Dash & Sivkumar Mishra & Almoataz Youssef Abdelaziz & Junhee Hong & Zong Woo Geem, 2022. "Optimal Planning of Multitype DGs and D-STATCOMs in Power Distribution Network Using an Efficient Parameter Free Metaheuristic Algorithm," Energies, MDPI, vol. 15(9), pages 1-35, May.
    3. Muhammad Nadeem & Kashif Imran & Abraiz Khattak & Abasin Ulasyar & Anamitra Pal & Muhammad Zulqarnain Zeb & Atif Naveed Khan & Malhar Padhee, 2020. "Optimal Placement, Sizing and Coordination of FACTS Devices in Transmission Network Using Whale Optimization Algorithm," Energies, MDPI, vol. 13(3), pages 1-24, February.
    4. Valeriya Tuzikova & Josef Tlusty & Zdenek Muller, 2018. "A Novel Power Losses Reduction Method Based on a Particle Swarm Optimization Algorithm Using STATCOM," Energies, MDPI, vol. 11(10), pages 1-15, October.
    5. Atif Naveed Khan & Kashif Imran & Muhammad Nadeem & Anamitra Pal & Abraiz Khattak & Kafait Ullah & Muhammad Waseem Younas & Muhammad Shahzad Younis, 2021. "Ensuring Reliable Operation of Electricity Grid by Placement of FACTS Devices for Developing Countries," Energies, MDPI, vol. 14(8), pages 1-21, April.
    6. Sun, Hongyue & Ebadi, Abdol Ghaffar & Toughani, Mohsen & Nowdeh, Saber Arabi & Naderipour, Amirreza & Abdullah, Aldrin, 2022. "Designing framework of hybrid photovoltaic-biowaste energy system with hydrogen storage considering economic and technical indices using whale optimization algorithm," Energy, Elsevier, vol. 238(PA).
    7. Tong Kang & Jiangang Yao & ThanhLong Duong & Shengjie Yang & Xiangqian Zhu, 2017. "A Hybrid Approach for Power System Security Enhancement via Optimal Installation of Flexible AC Transmission System (FACTS) Devices," Energies, MDPI, vol. 10(9), pages 1-32, September.
    Full references (including those not matched with items on IDEAS)

    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. Zhou, Jianguo & Xu, Zhongtian, 2023. "Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China," Renewable Energy, Elsevier, vol. 202(C), pages 1110-1137.
    2. Feng, Li & Liu, Jiajun & Lu, Haitao & Liu, Bingzhi & Chen, Yuning & Wu, Shenyu, 2022. "Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches," Energy, Elsevier, vol. 261(PB).
    3. Saman Shahrokhi & Adel El-Shahat & Fatemeh Masoudinia & Foad H. Gandoman & Shady H. E. Abdel Aleem, 2021. "Sizing and Energy Management of Parking Lots of Electric Vehicles Based on Battery Storage with Wind Resources in Distribution Network," Energies, MDPI, vol. 14(20), pages 1-21, October.
    4. Sohrab Mirsaeidi & Subash Devkota & Xiaojun Wang & Dimitrios Tzelepis & Ghulam Abbas & Ahmed Alshahir & Jinghan He, 2022. "A Review on Optimization Objectives for Power System Operation Improvement Using FACTS Devices," Energies, MDPI, vol. 16(1), pages 1-24, December.
    5. Ismail Marouani & Tawfik Guesmi & Badr M. Alshammari & Khalid Alqunun & Ahmed S. Alshammari & Saleh Albadran & Hsan Hadj Abdallah & Salem Rahmani, 2023. "Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods," Sustainability, MDPI, vol. 15(12), pages 1-58, June.
    6. Hana Merah & Abdelmalek Gacem & Djilani Ben Attous & Abderezak Lashab & Francisco Jurado & Mariam A. Sameh, 2022. "Sizing and Sitting of Static VAR Compensator (SVC) Using Hybrid Optimization of Combined Cuckoo Search (CS) and Antlion Optimization (ALO) Algorithms," Energies, MDPI, vol. 15(13), pages 1-20, July.
    7. Qiu, Rui & Zhang, Haoran & Wang, Guotao & Liang, Yongtu & Yan, Jinyue, 2023. "Green hydrogen-based energy storage service via power-to-gas technologies integrated with multi-energy microgrid," Applied Energy, Elsevier, vol. 350(C).
    8. Masoud Zahedi Vahid & Ziad M. Ali & Ebrahim Seifi Najmi & Abdollah Ahmadi & Foad H. Gandoman & Shady H. E. Abdel Aleem, 2021. "Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm," Energies, MDPI, vol. 14(16), pages 1-25, August.
    9. Shi, Mengshu & Wang, Weiye & Han, Yaxuan & Huang, Yuansheng, 2022. "Research on comprehensive benefit of hydrogen storage in microgrid system," Renewable Energy, Elsevier, vol. 194(C), pages 621-635.
    10. Tong Kang & Jiangang Yao & Min Jin & Shengjie Yang & ThanhLong Duong, 2018. "A Novel Improved Cuckoo Search Algorithm for Parameter Estimation of Photovoltaic (PV) Models," Energies, MDPI, vol. 11(5), pages 1-31, April.
    11. Ali Elkamel, 2018. "Energy Production Systems," Energies, MDPI, vol. 11(10), pages 1-4, September.
    12. Davoudkhani, Iraj Faraji & Dejamkhooy, Abdolmajid & Nowdeh, Saber Arabi, 2023. "A novel cloud-based framework for optimal design of stand-alone hybrid renewable energy system considering uncertainty and battery aging," Applied Energy, Elsevier, vol. 344(C).
    13. Ewaoche John Okampo & Nnamdi Nwulu & Pitshou N. Bokoro, 2022. "Optimal Placement and Operation of FACTS Technologies in a Cyber-Physical Power System: Critical Review and Future Outlook," Sustainability, MDPI, vol. 14(13), pages 1-26, June.
    14. Umme Mumtahina & Sanath Alahakoon & Peter Wolfs, 2023. "A Literature Review on the Optimal Placement of Static Synchronous Compensator (STATCOM) in Distribution Networks," Energies, MDPI, vol. 16(17), pages 1-38, August.
    15. Morteza Nazari-Heris & Atefeh Tamaskani Esfehankalateh & Pouya Ifaei, 2023. "Hybrid Energy Systems for Buildings: A Techno-Economic-Enviro Systematic Review," Energies, MDPI, vol. 16(12), pages 1-15, June.
    16. Fernando García-Muñoz & Miguel Alfaro & Guillermo Fuertes & Manuel Vargas, 2022. "DC Optimal Power Flow Model to Assess the Irradiance Effect on the Sizing and Profitability of the PV-Battery System," Energies, MDPI, vol. 15(12), pages 1-16, June.
    17. Hosseini Dehshiri, Seyyed Shahabaddin, 2022. "A new application of multi criteria decision making in energy technology in traditional buildings: A case study of Isfahan," Energy, Elsevier, vol. 240(C).
    18. Ashish Dandotia & Mukesh Kumar Gupta & Malay Kumar Banerjee & Suraj Kumar Singh & Bojan Đurin & Dragana Dogančić & Nikola Kranjčić, 2023. "Optimal Placement and Size of SVC with Cost-Effective Function Using Genetic Algorithm for Voltage Profile Improvement in Renewable Integrated Power Systems," Energies, MDPI, vol. 16(6), pages 1-20, March.
    19. Abdulaziz Alanazi & Mohana Alanazi, 2022. "Artificial Electric Field Algorithm-Pattern Search for Many-Criteria Networks Reconfiguration Considering Power Quality and Energy Not Supplied," Energies, MDPI, vol. 15(14), pages 1-27, July.
    20. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.

    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:jeners:v:15:y:2022:i:20:p:7478-:d:939067. 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.