Abstract
In this paper the authors propose a global–local methodology for optimizing the short-term operation of hydroelectric plants. The authors determine the tradeoffs between minimizing the daily release from the plant and minimizing the number of startups and shutdowns of the generating units. The model is formulated as a mixed integer, nonlinear programming optimization problem with multiple objectives. The authors consider the nonlinearities of the generating units without simplifications or approximations. The authors develop a solution method that combines an evolutionary algorithm for the global search of the integer variables and a gradient-based local optimizer for the continuous variables. The local optimizer is embedded in the global search algorithm. Convergence is achieved by iterating between the global search and the local optimizer. The proposed methodology is applied to a moderately sized Brazilian hydroelectric plant that belongs to the national interconnected system. Additionally, a comparative study was conducted using historical operational records. The results demonstrate that the proposed methodology is feasible for online daily operations and delivers two specific benefits. The first is the efficiency gained, as the model seeks to operate the generating units as close as possible to their most efficient operating points. The second benefit is reduction of the units’ maintenance costs, as the model minimizes switching on/off of the generating units.
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Acknowledgments
The research reported herein was supported by CNPq, a Brazilian government agency dedicated to the development of science and technology (Process: 200759/2012-4) and by CESP, one of Brazil’s largest power generators (Process: 01-P-26974/2011). We would like to thank three anonymous reviewers for their in-depth reviews and constructive comments.
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© 2014 American Society of Civil Engineers.
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Received: Jul 15, 2013
Accepted: Feb 11, 2014
Published online: Feb 13, 2014
Discussion open until: Dec 18, 2014
Published in print: Mar 1, 2015
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