Optimal management of a two dam system via stochastic control: parallel computing approach

Boris Miller, Daniel McInnes

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)

Abstract

In this paper we consider a model for the optimal management of a two dam system. Each dam is modelled via a continuous-time controlled Markov chain on a finite control period and linked to the other dam via a state and time dependent water transfer control. The consumption control for the dam system is provided by a time and state dependent price feedback control. This price feedback control takes into account the active seasonal demands of customers. We consider the case where inflow processes and evaporation for each dam are non-stationary as are the customer demands. The general approach to the solution of this problem is to consider this stochastic optimisation problem in the average case and solve it using the dynamic programming method. We show that the use of parallel computing techniques leads to substantial savings in calculation times for the solution of the optimal controls and demonstrate this via a numerical example.
Original languageEnglish
Title of host publicationProceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC)
EditorsMarios Polycarpou
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1417 - 1423
Number of pages7
DOIs
Publication statusPublished - 2011
EventIEEE Conference of Decision and Control (CDC)/European Control Conference (ECC) 2011 - Hilton Orlando Bonnet Creek, Orlando, United States of America
Duration: 12 Dec 201115 Dec 2011
Conference number: 50th
http://www.ieeecss.org/CAB/conferences/cdcecc2011/cfp.php
https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=15803

Conference

ConferenceIEEE Conference of Decision and Control (CDC)/European Control Conference (ECC) 2011
Abbreviated titleCDC-ECC 2011
CountryUnited States of America
CityOrlando
Period12/12/1115/12/11
Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Internet address

Cite this

Miller, B., & McInnes, D. (2011). Optimal management of a two dam system via stochastic control: parallel computing approach. In M. Polycarpou (Ed.), Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC) (pp. 1417 - 1423). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC.2011.6160566
Miller, Boris ; McInnes, Daniel. / Optimal management of a two dam system via stochastic control: parallel computing approach. Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC). editor / Marios Polycarpou. USA : IEEE, Institute of Electrical and Electronics Engineers, 2011. pp. 1417 - 1423
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Miller, B & McInnes, D 2011, Optimal management of a two dam system via stochastic control: parallel computing approach. in M Polycarpou (ed.), Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC). IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 1417 - 1423, IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC) 2011, Orlando, United States of America, 12/12/11. https://doi.org/10.1109/CDC.2011.6160566

Optimal management of a two dam system via stochastic control: parallel computing approach. / Miller, Boris; McInnes, Daniel.

Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC). ed. / Marios Polycarpou. USA : IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 1417 - 1423.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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Miller B, McInnes D. Optimal management of a two dam system via stochastic control: parallel computing approach. In Polycarpou M, editor, Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC). USA: IEEE, Institute of Electrical and Electronics Engineers. 2011. p. 1417 - 1423 https://doi.org/10.1109/CDC.2011.6160566