This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system...
Multi-reservoir systems management is complex because of the uncertainty on future events and the va...
Implicit stochastic reservoir optimization (ISO) typically utilizes nonlinear regression to correlat...
The reservoir operations model developed in this thesis is a stochastic dynamic programming decision...
This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly...
This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly...
Este artigo investiga a aplicação de Otimização Estocástica Implícita (OEI) para determinar regras d...
Deriving optimal release policies for dams and corresponding reservoirs is crucial for the sustainab...
A real-time operation model primarily useful for daily operation of reservoirs is developed. This mo...
Drought is a creeping phenomenon, making its onset and end difficult to determine. Damages from drou...
Stochastic programming is a mathematical model used to resolve the uncertainty of random variables i...
A new approach to the determination of reservoir operating rules is presented. The implicitly stocha...
Optimal reservoir operating policy should consider the uncertainty associated with the uncontrolled ...
ABSTRACT. In this study, the reservoir operating rules for satisfying reliable water releases under ...
A mean-variance stochastic optimization algorithm is developed for long-term operation of multi-rese...
A seasonal, chance-constrained linear programing model, which facilitates the development of reservo...
Multi-reservoir systems management is complex because of the uncertainty on future events and the va...
Implicit stochastic reservoir optimization (ISO) typically utilizes nonlinear regression to correlat...
The reservoir operations model developed in this thesis is a stochastic dynamic programming decision...
This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly...
This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly...
Este artigo investiga a aplicação de Otimização Estocástica Implícita (OEI) para determinar regras d...
Deriving optimal release policies for dams and corresponding reservoirs is crucial for the sustainab...
A real-time operation model primarily useful for daily operation of reservoirs is developed. This mo...
Drought is a creeping phenomenon, making its onset and end difficult to determine. Damages from drou...
Stochastic programming is a mathematical model used to resolve the uncertainty of random variables i...
A new approach to the determination of reservoir operating rules is presented. The implicitly stocha...
Optimal reservoir operating policy should consider the uncertainty associated with the uncontrolled ...
ABSTRACT. In this study, the reservoir operating rules for satisfying reliable water releases under ...
A mean-variance stochastic optimization algorithm is developed for long-term operation of multi-rese...
A seasonal, chance-constrained linear programing model, which facilitates the development of reservo...
Multi-reservoir systems management is complex because of the uncertainty on future events and the va...
Implicit stochastic reservoir optimization (ISO) typically utilizes nonlinear regression to correlat...
The reservoir operations model developed in this thesis is a stochastic dynamic programming decision...