An evolutionary approach to improve efficiency for solving the electric dispatch problem

The consumption of electric energy for general supply of a country is increasing over the years. In Brazil, energy demand grows, on average, 5% per year and the power source is predominantly hydroelectric. Many of the power plants installed in Brazil do not operate efficiently, from the water consum...

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Bibliographic Details
Published in2014 IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES) pp. 163 - 170
Main Authors Marcelino, Carolina G., Wanner, Elizabeth F., Almeida, Paulo E. M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2014
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Summary:The consumption of electric energy for general supply of a country is increasing over the years. In Brazil, energy demand grows, on average, 5% per year and the power source is predominantly hydroelectric. Many of the power plants installed in Brazil do not operate efficiently, from the water consumption point of view. The normal mode of operation (NMO) equally divides power demand between existing generation units of a power plant, regardless if this individual demand represents or not a good operation point for each unit. The unit dispatch problem is defined as the attribution of operational values to each unit inside a power plant, given some criteria to be met. In this context, an optimal solution for the dispatch problem means production of electricity with minimal water consumption. This work proposes a multi-objective approach to solve the electric dispatch problem in which the objective functions considered are: maximization of hydroelectric productivity function and minimization of the distance between NMO and optimized control mode (OCM). The proposed approach is applied to a large hydroelectric plant operating in Brazil. Results indicate that it is possible to identify operating points near NMO that present productivity efficiency, saving in one month about 14.6 million m 3 of water. Moreover, higher productivity can be achieved with smaller differences between NMO and OCM in lower power demands. Finally, it is worth to mention that the simplicity and the nature of the proposed approach indicate that it can be easily applied to studies of similar power plants, and thus can potentially be used to provide further economy on water consumption to larger extents of the hydroelectric production.
DOI:10.1109/CIES.2014.7011846