Coordination of hydro-thermal generation in two river basins

By: Call Number: AIT Thesis no.ET-85-12 Contributor(s): Material type: TextSeries: Asian Institute of Technology. Thesis ; no. ET-85-12Publication details: Bangkok : Asian Institute of Technology, 1985Description: 77 pSubject(s): Online resources: Dissertation note: Thesis (M.Sc.) - Asian Institute of Technology, 1985 Summary: The present study analyses the coordination of hydro-thermal power generation in two river basins through an example implementation. It summarizes a conglomerate model treating the problem. The main portion of the study, however, is devoted to the presentation of a working manual, showing the application of the quadratic minimization stochastic dynamic programming (QMSDP) which has been developed in the study. For this portion of the study, the brief theoretical background of the QMSDP methodology and a review of the principal aspects of its theory are included. Then, a detailed description of the QMSDP methodology is given, emphasizing the key steps of its procedure. The QMSDP algorithm as a means of solving already formulated stochastic dynamic programming problem is proposed. For testing purposes, one example is given to demonstrate its application to the solution of a cost minimization problem arising from the operation of hydro-thermal power system. The concepts of composite basin representation and probabilistic simulation of load duration curves are employed in the example. The results obtained show the competitive potential in computation time requirement with other stochastic dynamic programming approaches. Unfortunately that the accuracy of the algorithm could not been proven by comparison with that of the others
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A thesis submitted in partial fulfillment of requirements for the degree of Master of Science, School of Environment, Resources and Development

Thesis (M.Sc.) - Asian Institute of Technology, 1985

The present study analyses the coordination of hydro-thermal power generation in two river basins through an example implementation. It summarizes a conglomerate model treating the problem. The main portion of the study, however, is devoted to the presentation of a working manual, showing the application of the quadratic minimization stochastic dynamic programming (QMSDP) which has been developed in the study. For this portion of the study, the brief theoretical background of the QMSDP methodology and a review of the principal aspects of its theory are included. Then, a detailed description of the QMSDP methodology is given, emphasizing the key steps of its procedure. The QMSDP algorithm as a means of solving already formulated stochastic dynamic programming problem is proposed. For testing purposes, one example is given to demonstrate its application to the solution of a cost minimization problem arising from the operation of hydro-thermal power system. The concepts of composite basin representation and probabilistic simulation of load duration curves are employed in the example. The results obtained show the competitive potential in computation time requirement with other stochastic dynamic programming approaches. Unfortunately that the accuracy of the algorithm could not been proven by comparison with that of the others

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