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Stochastic Modeling and Operational Optimization in District Heating Systems

Arvastson, Lars LU (2001) In Doctoral theses in mathematical sciences 2001:3.
Abstract
Operation of a district heating system is accomplished via a sequence of decisions by the operators controlling the system. These decisions are based on expectations of conditions in the system that are not known at decision time. The operators could be helped by a decision support system that computes predictions of future system variables and suggests appropriate control actions given the available information.



This thesis presents a new model that gives a both physical and stochastic description of a district heating system. The model describes both technical and economical information of the system that are important for the control decisions. It is easy to calculate predictions based on this model as well as... (More)
Operation of a district heating system is accomplished via a sequence of decisions by the operators controlling the system. These decisions are based on expectations of conditions in the system that are not known at decision time. The operators could be helped by a decision support system that computes predictions of future system variables and suggests appropriate control actions given the available information.



This thesis presents a new model that gives a both physical and stochastic description of a district heating system. The model describes both technical and economical information of the system that are important for the control decisions. It is easy to calculate predictions based on this model as well as performing simulations.



The ambient temperature is the single most important explanatory variable for the heat demand in a district heating network. A model that can be used to calculate reliable temperature predictions are presented where the full advantage of both local measurements and forecasts from a meteorological institute are utilized.



A heuristic approach to the operational optimization problem is presented and it is shown in simulations to be superior to a traditional control, based on a priority scheme. The operational optimization problem is a complex stochastic optimization problem and the heuristic approach gives a solution that can be calculate instantly.



An online computer program, EnerPlan, is developed where the described models are used to calculate predictions and simulate alternative future scenarios. The program is currently used in the control room at the Heleneholm power plant in Malmö, Sweden. (Less)
Please use this url to cite or link to this publication:
author
opponent
  • Prof Egardt, Bo, Chalmers
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Statistik, actuarial mathematics, programming, operations research, Statistics, Matematik, optimization, Mathematics, simulation, prediction, District heating, grey-box modeling, operationsanalys, programmering, aktuariematematik, Systems engineering, computer technology, Data- och systemvetenskap
in
Doctoral theses in mathematical sciences
volume
2001:3
pages
240 pages
publisher
Centre for Mathematical Sciences, Lund University
defense location
MH:C
defense date
2001-06-15 13:15
ISSN
1404-0034
ISBN
91-628-4855-0
language
English
LU publication?
yes
id
a705f393-e777-42bd-8d9a-be5e085f8e5f (old id 20194)
date added to LUP
2007-05-28 08:27:43
date last changed
2016-09-19 08:44:52
@phdthesis{a705f393-e777-42bd-8d9a-be5e085f8e5f,
  abstract     = {Operation of a district heating system is accomplished via a sequence of decisions by the operators controlling the system. These decisions are based on expectations of conditions in the system that are not known at decision time. The operators could be helped by a decision support system that computes predictions of future system variables and suggests appropriate control actions given the available information.<br/><br>
<br/><br>
This thesis presents a new model that gives a both physical and stochastic description of a district heating system. The model describes both technical and economical information of the system that are important for the control decisions. It is easy to calculate predictions based on this model as well as performing simulations.<br/><br>
<br/><br>
The ambient temperature is the single most important explanatory variable for the heat demand in a district heating network. A model that can be used to calculate reliable temperature predictions are presented where the full advantage of both local measurements and forecasts from a meteorological institute are utilized.<br/><br>
<br/><br>
A heuristic approach to the operational optimization problem is presented and it is shown in simulations to be superior to a traditional control, based on a priority scheme. The operational optimization problem is a complex stochastic optimization problem and the heuristic approach gives a solution that can be calculate instantly.<br/><br>
<br/><br>
An online computer program, EnerPlan, is developed where the described models are used to calculate predictions and simulate alternative future scenarios. The program is currently used in the control room at the Heleneholm power plant in Malmö, Sweden.},
  author       = {Arvastson, Lars},
  isbn         = {91-628-4855-0},
  issn         = {1404-0034},
  keyword      = {Statistik,actuarial mathematics,programming,operations research,Statistics,Matematik,optimization,Mathematics,simulation,prediction,District heating,grey-box modeling,operationsanalys,programmering,aktuariematematik,Systems engineering,computer technology,Data- och systemvetenskap},
  language     = {eng},
  pages        = {240},
  publisher    = {Centre for Mathematical Sciences, Lund University},
  school       = {Lund University},
  series       = {Doctoral theses in mathematical sciences},
  title        = {Stochastic Modeling and Operational Optimization in District Heating Systems},
  volume       = {2001:3},
  year         = {2001},
}