Wellington C. Conceicao, T. Ramos, A. Marcato, J. Filho, R. B. S. Brandi, P. David
{"title":"Stochastic dynamic programming with discretization of energy interchange between hydrothermal systems in the operation planning problem","authors":"Wellington C. Conceicao, T. Ramos, A. Marcato, J. Filho, R. B. S. Brandi, P. David","doi":"10.1109/PSCC.2014.7038351","DOIUrl":null,"url":null,"abstract":"This work presents an alternative strategy to solve hydrothermal systems operation planning by stochastic dynamic programming. Under the presented approach, the hydroelectric plants are grouped into equivalent subsystems of energy and the expected cost functions are modeled by a piecewise linear approximation, by means of the convex hull algorithm. Also, under this methodology, the problem is solved independently for each subsystem such that the state variables to be considered are the energy storage and energy net interchange of the subsystem. The presented results have shown that this subsystems separation technique reduces significantly the computation time when compared with the traditional techniques of stochastic dynamic programming, demonstrating the effectiveness of the proposed methodology.","PeriodicalId":155801,"journal":{"name":"2014 Power Systems Computation Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Power Systems Computation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PSCC.2014.7038351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work presents an alternative strategy to solve hydrothermal systems operation planning by stochastic dynamic programming. Under the presented approach, the hydroelectric plants are grouped into equivalent subsystems of energy and the expected cost functions are modeled by a piecewise linear approximation, by means of the convex hull algorithm. Also, under this methodology, the problem is solved independently for each subsystem such that the state variables to be considered are the energy storage and energy net interchange of the subsystem. The presented results have shown that this subsystems separation technique reduces significantly the computation time when compared with the traditional techniques of stochastic dynamic programming, demonstrating the effectiveness of the proposed methodology.