Summary Alternative sources of electricity have been growing recently despite their intermittence, which makes it impossible for these sources to guarantee constant and uninterrupted supply of electricity. Energy storage systems, such as pumped‐storage (PS) power plants, can help to mitigate the intermittence of these sources. In Brazil, intense growth of intermittent sources has led the generation sector to high exposure to the spot market. Thus, Brazilian electricity sector has recently turned its attention to energy storage methods as a way of diminishing such exposure. However, Brazilian electricity‐sector regulatory framework is not prepared for energy storage systems remuneration. This paper proposes a regulatory framework to insert hybrid electric generation units composed of PS and intermittent sources in Brazilian energy market. A linear optimization model exemplifies the operation of such system by minimizing costs for 1 day. The model was tested in three different scenarios, allowing comparison of operational costs and other aspects of the operation. The results demonstrate how a PS can help covering peak demand by storing energy to be used at moments when generation from intermittent sources is not sufficient. In the proposed regulatory framework for hybrid plants, expenses with spot market purchases can be diminished either by completely avoiding it or by purchasing only during lower demand level periods.
This paper presents the application of a methodology for daily reservoir inflow forecasting in Brazilian hydroelectric plants. The methodology is based on Fuzzy Inference Systems (FIS) and the technique used for adjusting of the model parameters is an offline version of the Expectation Maximization (EM) algorithm. In order to automate the application of the methodology and facilitate the analysis of the results, a tool that allows managing streamflow forecasting studies and visualizing their information in graphical form was developed. A case study was applied to the data from three Brazilian hydroelectric plants whose operation is under the coordination of the Electric System National Operator. They are located in the Grande basin, a part of the Parana basin with two main rivers: the Grande and the Pardo. The benefits of the model are analyzed using statistics calculations, such as: root mean square error, mean absolute percentage error, mean absolute error and mass curve coefficient. Besides that, graphics that compare the registered and predicted streamflow are presented. The results show an adequate performance of the model, leading to a promising alternative for daily streamflow forecasting.
Changes in the climate system and the hydrologic regime strongly affect all water uses and human activity. The main goal of this study is to evaluate the impact of rainfall pattern change on streamflow for 26 Brazilian basins with hydropower plants. More precisely, the goal is to estimate the trends on average streamflow for the 2011–2100 period. The estimated trends result from the analysis of rainfall obtained from a possible climate scenario, among others. The annual average streamflow for this 90-year period is simulated and compared with records from 83 years of observations (1931–2013). Simulations were carried out using two rainfall-to-streamflow hydrological models: Soil Moisture Accounting Procedure (SMAP) and Stochastic Linear Model (SLM). Results from simulations show important impacts, namely, an increase of streamflow in the southern basins and a decrease in the northern basins. Such changes can lead to disastrous consequences, considering the historical exposure to floods and droughts in the southern and northeast regions, respectively. These findings, in addition to the recent severe drought events that have occurred in such regions, provide awareness of a new cycle of reform to the existing water policies and Brazilian institutional framework, which saw the completion of its first 20 years in 2017.
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