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Reducing the impact of wind farms on the electric power system by the use of energy storage

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  • Simla, Tomasz
  • Stanek, Wojciech

Abstract

The deployment of wind power is rapidly growing worldwide. Intermittent, unpredictable availability of wind energy destabilizes the work of the whole power system, which causes additional consumption of resources. When fossil fuel power plants are affected by this phenomenon, they are forced to cycle (change their load) more often, which results in higher consumption of fuel. This negative effect, expressed by means of thermo-ecological cost (TEC) can be significant in comparison to the TEC of construction phase of wind turbines. TEC is defined as the cumulative consumption of non-renewable exergy connected with the fabrication of a particular product. Power plant cycling could be minimized by applying an energy storage system responding to variations in wind power availability. In the present work, several scheduling strategies for cooperation of an energy storage system with wind turbines are investigated. The effect is assessed in local and global balance boundaries. Employing energy storage reduces the energy losses in thermal power plants, but at the same time, energy losses appear in the storage itself. However, depending on the strategy of energy storage scheduling, in some cases the overall consumption of primary exergy in the whole system may be lower.

Suggested Citation

  • Simla, Tomasz & Stanek, Wojciech, 2020. "Reducing the impact of wind farms on the electric power system by the use of energy storage," Renewable Energy, Elsevier, vol. 145(C), pages 772-782.
    • Handle: RePEc:eee:renene:v:145:y:2020:i:c:p:772-782
    DOI: 10.1016/j.renene.2019.06.028
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    Citations

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    Cited by:

    1. Gang Zhang & Yaning Zhu & Tuo Xie & Kaoshe Zhang & Xin He, 2022. "Wind Power Consumption Model Based on the Connection between Mid- and Long-Term Monthly Bidding Power Decomposition and Short-Term Wind-Thermal Power Joint Dispatch," Energies, MDPI, vol. 15(19), pages 1-25, September.
    2. Ma, Mingtao & Huang, Huijun & Song, Xiaoling & Peña-Mora, Feniosky & Zhang, Zhe & Chen, Jie, 2022. "Optimal sizing and operations of shared energy storage systems in distribution networks: A bi-level programming approach," Applied Energy, Elsevier, vol. 307(C).
    3. Komorowska, Aleksandra & Olczak, Piotr, 2024. "Economic viability of Li-ion batteries based on the price arbitrage in the European day-ahead markets," Energy, Elsevier, vol. 290(C).
    4. Zeinalnezhad, Masoomeh & Chofreh, Abdoulmohammad Gholamzadeh & Goni, Feybi Ariani & Hashemi, Leila Sadat & Klemeš, Jiří Jaromír, 2021. "A hybrid risk analysis model for wind farms using Coloured Petri Nets and interpretive structural modelling," Energy, Elsevier, vol. 229(C).
    5. Tadeusz Mączka & Halina Pawlak-Kruczek & Lukasz Niedzwiecki & Edward Ziaja & Artur Chorążyczewski, 2020. "Plasma Assisted Combustion as a Cost-Effective Way for Balancing of Intermittent Sources: Techno-Economic Assessment for 200 MW el Power Unit," Energies, MDPI, vol. 13(19), pages 1-16, September.
    6. Urbanowska, Agnieszka & Niedzwiecki, Lukasz & Wnukowski, Mateusz & Aragon-Briceño, Christian & Kabsch-Korbutowicz, Małgorzata & Baranowski, Marcin & Czerep, Michał & Seruga, Przemysław & Pawlak-Krucze, 2023. "Recovery of chemical energy from retentates from cascade membrane filtration of hydrothermal carbonisation effluent," Energy, Elsevier, vol. 284(C).
    7. Fan, Man & Luan, Zhaoyang & Li, Han & Kong, Xiangfei & Kang, Yiting, 2024. "Experimental investigation on thermal performance of porous composite phase change storage device under different operating modes and parameters," Energy, Elsevier, vol. 294(C).
    8. Ramin Sakipour & Hamdi Abdi, 2020. "Optimizing Battery Energy Storage System Data in the Presence of Wind Power Plants: A Comparative Study on Evolutionary Algorithms," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    9. Oh, Eunsung & Son, Sung-Yong, 2020. "Theoretical energy storage system sizing method and performance analysis for wind power forecast uncertainty management," Renewable Energy, Elsevier, vol. 155(C), pages 1060-1069.
    10. Diana Enescu & Gianfranco Chicco & Radu Porumb & George Seritan, 2020. "Thermal Energy Storage for Grid Applications: Current Status and Emerging Trends," Energies, MDPI, vol. 13(2), pages 1-21, January.
    11. Stanek, Wojciech, 2022. "Thermo-Ecological Cost (TEC) –comparison of energy-ecological efficiency of renewable and non-renewable energy technologies," Energy, Elsevier, vol. 261(PA).
    12. Nissim Amar & Aaron Shmaryahu & Michael Coletti & Ilan Aharon, 2021. "Sizing Procedure for System Hybridization Based on Experimental Source Modeling in Grid Application," Energies, MDPI, vol. 14(15), pages 1-19, August.

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