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Predictive management approach for the coordination of wind and water-based power supplies

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  • Levieux, Luis Ignacio
  • Ocampo-Martinez, Carlos
  • Inthamoussou, Fernando A.
  • De Battista, Hernán

Abstract

This paper addresses the coordinated operation between wind farms and reservoir hydropower plants in networks with weak transmission capacity. The joint operation of the energy sources is captured by a Virtual Power Plant (VPP) representation. With the aim of maximising renewable energy penetration while ensuring a suitable VPP integration, a supervisory controller for the energy dispatch layer is proposed. To deal with the variable nature of both resources, the controller has been designed into a model predictive control framework including mixed-integer quadratic programming (given the hybrid considered model) for solving the related optimisation problem, and complementary techniques as constraints softening and time-varying weighting. The results indicate that the predictive control approach achieves a better Independent System Operator (ISO) reference tracking that, together with reservoir management, are the most important factors to ensure a suitable VPP incorporation to the main grid. As a case study, a sub-network of the Argentinian power system is tackled. The controller performance is quantitatively and qualitatively assessed under uncertain conditions and compared with other approaches over a nine-year period. By means of the proposed power management policy, the ISO’s effort to balance the sub-network is reduced 56% with regard to other approaches without any water spillage.

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  • Levieux, Luis Ignacio & Ocampo-Martinez, Carlos & Inthamoussou, Fernando A. & De Battista, Hernán, 2021. "Predictive management approach for the coordination of wind and water-based power supplies," Energy, Elsevier, vol. 219(C).
  • Handle: RePEc:eee:energy:v:219:y:2021:i:c:s0360544220326426
    DOI: 10.1016/j.energy.2020.119535
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    1. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2023. "Predictive operation optimization of multi-energy virtual power plant considering behavior uncertainty of diverse stakeholders," Energy, Elsevier, vol. 280(C).

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