Efficient Implementation of Sampling Stochastic Dynamic Programming Algorithm for Multireservoir Management in the Hydropower Sector

2019 ◽  
Vol 145 (4) ◽  
pp. 05019005 ◽  
Author(s):  
Pascal Côté ◽  
Richard Arsenault
Top ◽  
2015 ◽  
Vol 23 (3) ◽  
pp. 703-742 ◽  
Author(s):  
Unai Aldasoro ◽  
Laureano F. Escudero ◽  
María Merino ◽  
Juan F. Monge ◽  
Gloria Pérez

2005 ◽  
Vol 25 (3) ◽  
pp. 479-492 ◽  
Author(s):  
Franklina Maria Bragion de Toledo ◽  
André Luís Shiguemoto

In this paper, a case study is carried out concerning the lot-sizing problem involving a single item production planning in several production centers that do not present capacity constraints. Demand can be met with backlogging or not. This problem results from simplifying practical problems, such as the material requirement planning (MRP) system and also lot-sizing problems with multiple items and limited production capacity. First we propose an efficient implementation of a forward dynamic programming algorithm for problems with one single production center. Although this does not reduce its complexity, it has shown to be rather effective, according to computational tests. Next, we studied the problem with a production environment composed of several production centers. For this problem two algorithms are implemented, the first one is an extension of the dynamic programming algorithm for one production center and the second one is an efficient implementation of the first algorithm. Their efficiency are shown by computational testing of the algorithms and proposals for future research are presented.


2021 ◽  
Author(s):  
Linn Schäffer ◽  
Arild Helseth ◽  
Magnus Korpås

<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>


2021 ◽  
Author(s):  
Linn Schäffer ◽  
Arild Helseth ◽  
Magnus Korpås

<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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