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Operation of pumped storage hydropower plants through optimization for power systems

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  • Alvarez, Gonzalo E.

Abstract

Worldwide, there is an increase in the number of energy storage systems that are installed as a result of several benefits. These systems bring uniformity and efficiency improvements to electrical grids by storing and returning energy to the grid. They help with the integration of the new renewable energy sources, mitigating the intermittency of these sources, which is the main problem to implement them on a large scale. One of the most widespread kinds of these systems is the Pumped Storage Hydropower Plant, with an installed power capacity of 153 GW at global level. This work presents a new Mixed Integer Linear Programming model to operate these plants by maximizing the received profits. The model is distinguished from others because it allows the inclusion of a greater number of breakpoints, which means that more realistic solutions can be obtained by reducing the computational effort. To prove the usefulness of the formulation, two real plants located in Argentine Republic are tested: Rio Grande and Los Reyunos power plants which have a total installed power capacity of 975 MW. Results indicate that the proposed model reaches feasible solutions with a sufficient level of accuracy with CPU times of less than 1 s.

Suggested Citation

  • Alvarez, Gonzalo E., 2020. "Operation of pumped storage hydropower plants through optimization for power systems," Energy, Elsevier, vol. 202(C).
    • Handle: RePEc:eee:energy:v:202:y:2020:i:c:s036054422030904x
    DOI: 10.1016/j.energy.2020.117797
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    Cited by:

    1. Alvarez, Gonzalo E., 2021. "A multi-objective formulation of improving flexibility in the operation of electric power systems: Application to mitigation measures during the coronavirus pandemic," Energy, Elsevier, vol. 227(C).
    2. Zhao, Zhigao & Yang, Jiandong & Chung, C.Y. & Yang, Weijia & He, Xianghui & Chen, Man, 2021. "Performance enhancement of pumped storage units for system frequency support based on a novel small signal model," Energy, Elsevier, vol. 234(C).
    3. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    4. Jang, Dohyung & Cho, Hyun-Seok & Kang, Sanggyu, 2021. "Numerical modeling and analysis of the effect of pressure on the performance of an alkaline water electrolysis system," Applied Energy, Elsevier, vol. 287(C).
    5. He, Xianghui & Yang, Jiandong & Yang, Jiebin & Zhao, Zhigao & Hu, Jinhong & Peng, Tao, 2023. "Evolution mechanism of water column separation in pump turbine: Model experiment and occurrence criterion," Energy, Elsevier, vol. 265(C).
    6. Abadie, Luis M. & Goicoechea, Nestor, 2022. "Optimal management of a mega pumped hydro storage system under stochastic hourly electricity prices in the Iberian Peninsula," Energy, Elsevier, vol. 252(C).

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