MULTIOBJECTIVE REAL‐TIME RESERVOIR OPERATION WITH A NETWORK FLOW ALGORITHM¹

Abstract

A network flow algorithm has been developed for the optimization of real‐time operation of a multiple reservoir system. Two purposes have been considered in the operation: flood control and hydropower generation. A special network structure was developed which allows the consideration of river routing. A multiobjective formulation is utilized thus allowing generation of a non‐dominated curve. The effect of imperfect forecast on the performance of the real‐time operation model is also evaluated. An application is made to a subsystem of the Brazilian hydroelectric system, located in the Paranapanema river basin. In this case study, the model showed good performance under the largest flood of the historical records.

Multireservoir real-time operations for flood control using balanced water level index method

“…The developed models are applied to the Tanshui River Basin reservoir system in northern Taiwan. Braga and Barbosa (2001) indicated that inflow forecast reliability decreases with the increase in the forecasting time horizon. Thus, the 6 h ahead hydrological forecast data are employed to determine releases from the reservoir in the case study.…”

“…Windsor (1973) and Braga and Barbosa (2001) described an application of deterministic optimization using a linear programming (LP) model to treat the flood control problem, and using the Muskingum method for channel routing and mass balance equation for reservoir operations. Wasimi and Kitanidis (1983) discrete-time linear quadratic Gaussian (LQG) stochastic control to the real-time daily operation under flood conditions.…”

Contrastive analysis of three parallel modes in multi-dimensional dynamic programming and its application in cascade reservoirs operation

“…Those traditional optimization methods include Linear Programming (LP) (Marino and Mohammadi, 1983;Jabr et al, 2000;Reis et al, 2006;Lu et al, 2011;Li et al, 2013), Nonlinear Programming (NLP) (Martin, 1983;Lund and Ferreira, 1996;Barros et al, 2003;Chen, 2007), Lagrangian Relaxation (LR) (Hindi and Ghani, 1991;EI-Keib et al, 1994), Quadratic Programming (QP) (Papageorgiou and Fraga, 2007), Network Flow Algorithm (NFA) (Braga and Barbosa, 2001), and Dynamic programming (DP) (Johnson et al, 1993;Raman and Chandramouli, 1996;Eum et al, 2010;Goor et al, 2011;Shokri et al, 2013), etc. They are all elitist algorithms, and have already received different degrees of success in solving CROO problems.…”

Multireservoir Flood-Control Optimization with Neural-Based Linear Channel Level Routing Under Tidal Effects

“…To develop a multireservoir operation model for a river basin system, Windsor (1973), Needham et al (2000), and Braga and Barbosa (2001) described an application of deterministic optimization using a linear programming (LP) model to treat the flood control problem, using the Muskingum method for channel routing and mass balance equation for reservoir operations. Wasimi and Kitanidis (1983) applied the discrete-time linear quadratic Gaussian (LQG) stochastic control for the real-time daily operation under flood conditions.…”