Aggregated inflows on stochastic dynamic programming for long term hydropower scheduling

2014 ◽  
Author(s):  
Ricardo O. Scarcelli ◽  
Monica S. Zambelli ◽  
Secundino. S. Filho ◽  
Adriano A. Carneiro
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Stochastic Dynamic ◽  
Hydropower Scheduling

scholarly journals A Stochastic Dynamic Programming Model for Hydropower Scheduling with State-dependent Maximum Discharge Constraints

2021 ◽  
Author(s):  
Linn Schäffer ◽  
Arild Helseth ◽  
Magnus Korpås
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Dynamic Programming Algorithm ◽  
Stochastic Dynamic ◽  
Environmental Constraint ◽  
Maximum Discharge ◽  
State Dependent ◽  
Hydropower System ◽  
Hydropower Scheduling ◽  
Water Values

<div>We present a medium-term hydropower scheduling model that includes state-dependent environmental constraints on maximum discharge. A stochastic dynamic programming algorithm is used to enable modelling of nonconvex relationships in the problem formulation. The model is applied in a case study of a Norwegian hydropower system with multiple reservoirs. We find that the maximum discharge constraint significantly impacts the water values and simulated operation of the hydropower system. A main finding is that the nonconvex characteristics of the environmental constraint is reflected in the water values, implying a nonconvex objective function. Operation according to the computed water values is simulated for cases with and without the environmental constraint. Even though operation of the system changes considerably when the environmental constraint is included, the total electricity generation over the year is kept constant, and the total loss in expected profit limited to less than 0.8%.</div>

scholarly journals A Stochastic Dynamic Programming Model for Hydropower Scheduling with State-dependent Maximum Discharge Constraints

2021 ◽  
Author(s):  
Linn Schäffer ◽  
Arild Helseth ◽  
Magnus Korpås
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Dynamic Programming Algorithm ◽  
Stochastic Dynamic ◽  
Environmental Constraint ◽  
Maximum Discharge ◽  
State Dependent ◽  
Hydropower System ◽  
Hydropower Scheduling ◽  
Water Values

<div>We present a medium-term hydropower scheduling model that includes state-dependent environmental constraints on maximum discharge. A stochastic dynamic programming algorithm is used to enable modelling of nonconvex relationships in the problem formulation. The model is applied in a case study of a Norwegian hydropower system with multiple reservoirs. We find that the maximum discharge constraint significantly impacts the water values and simulated operation of the hydropower system. A main finding is that the nonconvex characteristics of the environmental constraint is reflected in the water values, implying a nonconvex objective function. Operation according to the computed water values is simulated for cases with and without the environmental constraint. Even though operation of the system changes considerably when the environmental constraint is included, the total electricity generation over the year is kept constant, and the total loss in expected profit limited to less than 0.8%.</div>

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