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An analysis of the impacts of wind power penetration in the power system of southern Brazil

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  • Diuana, Fabio A.
  • Viviescas, Cindy
  • Schaeffer, Roberto

Abstract

This paper analyzes the main impacts of high penetration levels of wind power in the power system of Southern Brazil. For this, an hourly operation of the Brazilian Southern power system is simulated using an Economic Dispatch Model. Two main scenarios are explored: a baseline and a wind penetration case, both for 2030 and 2050. To create these scenarios, results from an Integrated Energy Model are used as inputs for the dispatch model. The economic dispatch modeling led to some expected outcomes, such as a reduction in the system generation cost, a reduction in greenhouse-gas emissions, and a greater need for transmission expansion in the wind-power scenarios. Results also show that, even for a power system as flexible as the one in Southern Brazil, wind power penetration impacts can be observed. Moreover, results show that setting thermal power plants to provide secondary reserve can potentially improve the balancing management in hydropower-based systems. Finally, results from linking the Economic Dispatch Model and the Integrated Energy Model showed the need for better combining energy expansion models with power dispatch models that consider both the operation and the transmission system restrictions, in order to have stable and feasible unit commitment schedules.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:186:y:2019:i:c:s0360544219315415
    DOI: 10.1016/j.energy.2019.115869
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    Cited by:

    1. He, Ke-Lun & Zhao, Tian & Ma, Huan & Chen, Qun, 2023. "Optimal operation of integrated power and thermal systems for flexibility improvement based on evaluation and utilization of heat storage in district heating systems," Energy, Elsevier, vol. 274(C).
    2. Chris Matthew & Catalina Spataru, 2021. "Scottish Islands Interconnections: Modelling the Impacts on the UK Electricity Network of Geographically Diverse Wind and Marine Energy," Energies, MDPI, vol. 14(11), pages 1-21, May.
    3. Hu, Jinxing & Li, Hongru, 2022. "A transfer learning-based scenario generation method for stochastic optimal scheduling of microgrid with newly-built wind farm," Renewable Energy, Elsevier, vol. 185(C), pages 1139-1151.
    4. Deng, Xu & Lv, Tao & Xu, Jie & Hou, Xiaoran & Liu, Feng, 2022. "Assessing the integration effect of inter-regional transmission on variable power generation under renewable energy consumption policy in China," Energy Policy, Elsevier, vol. 170(C).
    5. Zhao, Shihao & Li, Kang & Yang, Zhile & Xu, Xinzhi & Zhang, Ning, 2022. "A new power system active rescheduling method considering the dispatchable plug-in electric vehicles and intermittent renewable energies," Applied Energy, Elsevier, vol. 314(C).
    6. Nascimento da Silva, Gabriela & Rochedo, Pedro R.R. & Szklo, Alexandre, 2022. "Renewable hydrogen production to deal with wind power surpluses and mitigate carbon dioxide emissions from oil refineries," Applied Energy, Elsevier, vol. 311(C).
    7. Abu-Rayash, Azzam & Dincer, Ibrahim, 2020. "Development of an integrated energy system for smart communities," Energy, Elsevier, vol. 202(C).
    8. Howard, D.B. & Soria, R. & Thé, J. & Schaeffer, R. & Saphores, J.-D., 2020. "The energy-climate-health nexus in energy planning: A case study in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    9. Kim, Gyeongmin & Hur, Jin, 2021. "Probabilistic modeling of wind energy potential for power grid expansion planning," Energy, Elsevier, vol. 230(C).
    10. Chi, Lixun & Su, Huai & Zio, Enrico & Qadrdan, Meysam & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Yang, Zhaoming & Zhang, Jinjun, 2021. "Data-driven reliability assessment method of Integrated Energy Systems based on probabilistic deep learning and Gaussian mixture Model-Hidden Markov Model," Renewable Energy, Elsevier, vol. 174(C), pages 952-970.
    11. 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).

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