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Improvement of system strength under high wind penetration: A techno-economic assessment using synchronous condenser and SVC

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  • Masood, Nahid-Al-
  • Mahmud, Sajjad Uddin
  • Ansary, Md Nazmuddoha
  • Deeba, Shohana Rahman

Abstract

Variable speed wind turbine generators (WTGs) are replacing traditional fossil fuel based synchronous generators in the generation fleet as wind penetration increases. These variable speed WTGs are decoupled from the grid by power electronics inverters and usually generate less fault current compared to synchronous generators. As a result, system strength (indicates the fault recovery capability) at the point of common coupling (PCC) of wind power plants may reduce. A minimum value level of system strength is essential for wind power plants to properly identify and overcome a fault. To enhance system strength at wind PCC buses, supplementary devices such as synchronous condenser and Static VAR Compensator (SVC) can be deployed to have additional fault current. Since these devices are expensive, their optimal allocation considering economic feasibility is a major concern. In the existing literature, locations and ratings of the optimally allocated synchronous condenser are reported. However, this approach may cause oversizing of synchronous condensers. In addition, a SVC can be utilised instead of a synchronous condenser to enhance system strength. However, no detailed study is carried out yet to find the optimal size of SVCs. Evidently, both synchronous condenser and SVC can be installed to improve system strength. However, no comprehensive techno-economic assessment is performed for selecting an appropriate choice between them. To address these research gaps, this paper develops a framework to find the optimal sizes of synchronous condensers and SVCs by taking into account the long-term financial viability. Also, to ensure the maximum possible fault contribution, synchronous condensers/SVCs are connected directly to those wind PCC buses where system strength is below the acceptable limit. Afterwards, a detailed techno-economic assessment using synchronous condenser and SVC is performed in a wind dominated grid. In addition, post-fault voltage recovery characteristics with optimally sized synchronous condenser and SVC are explored. The developed methodology is applied to the IEEE 39 bus test system considering 45% wind power penetration scenario. Also, the performance of the proposed approach is compared to that of an existing technique. Finally, based on the technical and economic aspects, a better choice between synchronous condenser and SVC is recommended to improve system strength under high wind penetration.

Suggested Citation

  • Masood, Nahid-Al- & Mahmud, Sajjad Uddin & Ansary, Md Nazmuddoha & Deeba, Shohana Rahman, 2022. "Improvement of system strength under high wind penetration: A techno-economic assessment using synchronous condenser and SVC," Energy, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222003292
    DOI: 10.1016/j.energy.2022.123426
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    1. Diuana, Fabio A. & Viviescas, Cindy & Schaeffer, Roberto, 2019. "An analysis of the impacts of wind power penetration in the power system of southern Brazil," Energy, Elsevier, vol. 186(C).
    2. Song, Dongran & Yang, Jian & Dong, Mi & Joo, Young Hoon, 2017. "Model predictive control with finite control set for variable-speed wind turbines," Energy, Elsevier, vol. 126(C), pages 564-572.
    3. Naderipour, Amirreza & Abdul-Malek, Zulkurnain & Heidari Gandoman, Foad & Nowdeh, Saber Arabi & Shiran, Mohsen Aghazadeh & Hadidian Moghaddam, Mohammad Jafar & Davoodkhani, Iraj Faraji, 2020. "Optimal designing of static var compensator to improve voltage profile of power system using fuzzy logic control," Energy, Elsevier, vol. 192(C).
    4. Okonkwo, Eric C. & Wole-Osho, Ifeoluwa & Bamisile, Olusola & Abid, Muhammad & Al-Ansari, Tareq, 2021. "Grid integration of renewable energy in Qatar: Potentials and limitations," Energy, Elsevier, vol. 235(C).
    5. Xiang, Yue & Zhou, Lili & Huang, Yuan & Zhang, Xin & Liu, Youbo & Liu, Junyong, 2021. "Reactive coordinated optimal operation of distributed wind generation," Energy, Elsevier, vol. 218(C).
    6. Famous O. Igbinovia & Ghaeth Fandi & Ibrahim Ahmad & Zdenek Muller & Josef Tlusty, 2018. "Modeling and Simulation of the Anticipated Effects of the Synchronous Condenser on an Electric-Power Network with Participating Wind Plants," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    7. Mc Garrigle, E.V. & Deane, J.P. & Leahy, P.G., 2013. "How much wind energy will be curtailed on the 2020 Irish power system?," Renewable Energy, Elsevier, vol. 55(C), pages 544-553.
    8. Mehrjerdi, Hasan, 2019. "Simultaneous load leveling and voltage profile improvement in distribution networks by optimal battery storage planning," Energy, Elsevier, vol. 181(C), pages 916-926.
    9. Li, Rong & Guo, Su & Yang, Yong & Liu, Deyou, 2020. "Optimal sizing of wind/ concentrated solar plant/ electric heater hybrid renewable energy system based on two-stage stochastic programming," Energy, Elsevier, vol. 209(C).
    10. Johnson, Samuel C. & Papageorgiou, Dimitri J. & Mallapragada, Dharik S. & Deetjen, Thomas A. & Rhodes, Joshua D. & Webber, Michael E., 2019. "Evaluating rotational inertia as a component of grid reliability with high penetrations of variable renewable energy," Energy, Elsevier, vol. 180(C), pages 258-271.
    11. Elattar, Ehab E. & ElSayed, Salah K., 2019. "Modified JAYA algorithm for optimal power flow incorporating renewable energy sources considering the cost, emission, power loss and voltage profile improvement," Energy, Elsevier, vol. 178(C), pages 598-609.
    12. 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).
    13. Ciupăgeanu, Dana-Alexandra & Lăzăroiu, Gheorghe & Barelli, Linda, 2019. "Wind energy integration: Variability analysis and power system impact assessment," Energy, Elsevier, vol. 185(C), pages 1183-1196.
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