Stochastic dynamic programming applied to hydrothermal power systems operation planning based on the convex hull algorithm

31Citations
Citations of this article
44Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

This paper presents a new approach for the expected cost-to-go functions modeling used in the stochastic dynamic programming (SDP) algorithm. The SDP technique is applied to the long-term operation planning of electrical power systems. Using state space discretization, the Convex Hull algorithm is used for constructing a series of hyperplanes that composes a convex set. These planes represent a piecewise linear approximation for the expected cost-to-go functions. The mean operational costs for using the proposed methodology were compared with those from the deterministic dual dynamic problem in a case study, considering a single inflow scenario. This sensitivity analysis shows the convergence of both methods and is used to determine the minimum discretization level. Additionally, the applicability of the proposed methodology for two hydroplants in a cascade is demonstrated. With proper adaptations, this work can be extended to a complete hydrothermal system. Copyright © 2010 Bruno H. Dias et al.

Cite

CITATION STYLE

APA

Dias, B. H., Marcato, A. L. M., Souza, R. C., Soares, M. P., Silva Junior, I. C., Oliveira, E. J. D., … Ramos, T. P. (2010). Stochastic dynamic programming applied to hydrothermal power systems operation planning based on the convex hull algorithm. Mathematical Problems in Engineering, 2010. https://doi.org/10.1155/2010/390940

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free