Abstract
| Original language | English |
|---|---|
| Title of host publication | Procedia Computer Science |
| Subtitle of host publication | International Conference on Computational Science (ICCS 2011) |
| Editors | Mitsuhisa Sato, Satoshi Matsuoka, G. Dick van Albada, Jack Dongarra, Peter M A Sloot |
| Place of Publication | Amsterdam, Netherlands |
| Publisher | Elsevier |
| Pages | 1373-1382 |
| Number of pages | 10 |
| Volume | 4 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | International Conference on Computational Science 2011: The Ascent of Computational Excellence - Nanyang, Singapore Duration: 1 Jun 2011 → 3 Jun 2011 Conference number: 11th http://www.iccs-meeting.org/iccs2011/index.html |
Conference
| Conference | International Conference on Computational Science 2011 |
|---|---|
| Abbreviated title | ICCS 2011 |
| Country | Singapore |
| City | Nanyang |
| Period | 1/06/11 → 3/06/11 |
| Other | The International Conference on Computational Science aims to bring together annually researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering advanced application of computational methods to sciences such as physics, chemistry, life sciences, and engineering, arts and humanitarian fields, along with software developers and vendors, to discuss problems and solutions in the area, to identify new issues, and to shape future directions for research, as well as to help industrial users apply various advanced computational techniques. |
| Internet address |
Keywords
- Stochastic control
- Optimal control
- Optimization problems
- Dynamic programming
- Markov decision problems
- Parallelization
Cite this
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Management of dam systems via optimal price control. / Miller, Boris M.; McInnes, Daniel.
Procedia Computer Science: International Conference on Computational Science (ICCS 2011). ed. / Mitsuhisa Sato; Satoshi Matsuoka; G. Dick van Albada; Jack Dongarra; Peter M A Sloot. Vol. 4 Amsterdam, Netherlands : Elsevier, 2011. p. 1373-1382.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Management of dam systems via optimal price control
AU - Miller, Boris M.
AU - McInnes, Daniel
PY - 2011
Y1 - 2011
N2 - This paper considers an optimal management strategy for a system of linked dams. The level of each dam is approximated by N discrete levels and each dam is then modeled as a continuous-time controlled Markov chain on a finite control period. The inflow processes for each dam are non-stationary as are the customer demands. We also consider non-stationary losses from each dam due to evaporation. The controls are a time and state dependent price control, the bounds of which are prescribed by regulators, and time and state dependent flow controls between dams. The innovation in this model is that the price control is a feedback control that takes into account the active sectoral demands of customers. The general approach to the solution is to consider the solution of this stochastic optimization problem in the average sense and solve it using the dynamic programming method. We consider some issues of the numerical procedures involved in this method and parallelization as a means to deal with higher dimension problems in reasonable time. We show that we can obtain optimal price controls for each joint state of the dam system using numerical methods. The result is illustrated by a numerical example.
AB - This paper considers an optimal management strategy for a system of linked dams. The level of each dam is approximated by N discrete levels and each dam is then modeled as a continuous-time controlled Markov chain on a finite control period. The inflow processes for each dam are non-stationary as are the customer demands. We also consider non-stationary losses from each dam due to evaporation. The controls are a time and state dependent price control, the bounds of which are prescribed by regulators, and time and state dependent flow controls between dams. The innovation in this model is that the price control is a feedback control that takes into account the active sectoral demands of customers. The general approach to the solution is to consider the solution of this stochastic optimization problem in the average sense and solve it using the dynamic programming method. We consider some issues of the numerical procedures involved in this method and parallelization as a means to deal with higher dimension problems in reasonable time. We show that we can obtain optimal price controls for each joint state of the dam system using numerical methods. The result is illustrated by a numerical example.
KW - Stochastic control
KW - Optimal control
KW - Optimization problems
KW - Dynamic programming
KW - Markov decision problems
KW - Parallelization
UR - http://www.scopus.com/inward/record.url?scp=79958289272&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2011.04.148
DO - 10.1016/j.procs.2011.04.148
M3 - Conference Paper
VL - 4
SP - 1373
EP - 1382
BT - Procedia Computer Science
A2 - Sato, Mitsuhisa
A2 - Matsuoka, Satoshi
A2 - van Albada, G. Dick
A2 - Dongarra, Jack
A2 - Sloot, Peter M A
PB - Elsevier
CY - Amsterdam, Netherlands
ER -