4.6 Article

Piecewise linear approximations for hydropower production function applied on the hydrothermal unit commitment problem

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2021.107464

关键词

Hydro Production Function; Piecewise-Linear Models; Hydrothermal Unit Commitment; Mixed-Integer Linear Programming

资金

  1. CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior)
  2. Norte Energia, via RD Project
  3. ANEEL (Agencia Nacional de Energia Eletrica) [PD-07427-0318/2018]

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In a centralized-based dispatch market, the NCHTUC determines generation decisions to minimize costs, with hydropower offering unique flexibility features. Simplifications on HPF modeling are necessary due to computational burden, with plant-based HPF piecewise linear approach being common.
In a centralized-based dispatch market, the network-constrained hydrothermal unit commitment (NCHTUC) determines generation decisions that minimize the expected operating cost, usually in a day-ahead planning horizon. In this context, hydropower offers unique flexibility features, and an adequate representation is crucial for overcoming operation challenges. However, due to computational burden, simplifications on hydropower production function (HPF) modeling are necessary since NCHTUC is a large-scale nonlinear discrete optimization problem. The plant-based HPF piecewise linear approach is the most common simplification presented for real life cases. In this case, the generating units (GUs) of a plant are aggregated and represented by a single equivalent generator. Although this approach reduces the size and the complexity of the NCHTUC significantly, several operating issues are not considered adequately, especially the forbidden zones and the nonlinearities of the GUs. In this paper, we present a new approach that considers the nonlinearities and forbidden zones of the HPF via aggregation of the GUs and piecewise mixed-integer linear approximation in an innovative way. Experiments are performed in a modified version of the IEEE 118-bus system to verify the approach's effectiveness, analyzed in terms of the relation between computation burden and the HPF approximation quality.

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