Influence of Inflow Nonstationarity on the Multipurpose Optimal Operation of Hydropower Plants Using Nonlinear Programming

Alan de Gois Barbosa (), Alcigeimes B. Celeste and Ludmilson Abritta Mendes
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Alan de Gois Barbosa: Federal University of Sergipe
Alcigeimes B. Celeste: Federal University of Sergipe
Ludmilson Abritta Mendes: Federal University of Sergipe

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2021, vol. 35, issue 8, No 4, 2343-2367

Abstract: Abstract One of the greatest challenges in the electricity generation sector is to operate hydrothermal plants in view of the randomness of hydrological events and climate change, that may impact the inflows into the systems. In several Brazilian watersheds, conflicts among water users are already registered, in addition to inflow changes that affect the electricity generation system. The São Francisco River Basin (SFRB) is an important source of water for the development of northeastern Brazil. In this context, this work aimed at carrying out a study on the statistical behavior of time series related to the management of the SFRB hydrosystem network, as well as to measure the performance of hydropower plants in supplying multiple users, in different critical periods. Historical records of natural streamflow, natural inflow energy and stored energy were used. Some statisctical tests were applied to detect trends and change-points. The Natural Energy method was applied to different subsamples to define critical periods. Next, a deterministic nonlinear operation optimization model was used to assess the supply to the multiple users for the different critical periods. The main contribution of this study is the impact of nonstationarity in planning and operation of hydrosystems. The results indicated that the natural inflow energy and the stored energy time series are predominantly non-stationary, with a trend change in the 1990s, which modifies the critical period of the basin to 2013–2019, significantly increasing the vulnerability of the system in about 35% when compared to the currently used critical period (1949–1956).

Keywords: Reservoir system operation; São Francisco river basin; Nonlinear programming; Trend detection; Nonstationarity (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11269-021-02812-8

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