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Dynamic modelling and operational optimization of district heating systems

Abstract

This study deals with the developing and testing of methods for dynamic simulation and operational optimization of district heating systems. The performance of a number of models for simulating or predicting the heat load of consumers on a substation level was investigated through regression analysis, estimating the constants of the models on the basis of measured data. It was found that if the value of the most important climate variables were known, then the heat load could be simulated or predicted with reasonable accuracy in several ways, the actual purpose of it`s application being decisive for selection of model category. If the consumers` real supply temperature was known, then the return temperature could be estimated with accuracy on the basis of a linear combination of the heat load and the supply temperature only. For dynamic simulation of transient temperatures a new method was much faster and more accurate than the conventional method, and it was found capable of simulating transient temperatures in a district heating network built up of preinsulated pipes. One method for searching for optimum by comparing series of simulations, and another optimization based on determining the time delays and the temperature drop in the network iteratively by  More>>
Authors:
Publication Date:
Sep 01, 1991
Product Type:
Thesis/Dissertation
Report Number:
NEI-DK-776
Reference Number:
SCA: 320106; PA: DK-92:001172; SN: 92000700247
Resource Relation:
Other Information: DN: EFP-91; TH: Thesis (Ph.D.).; PBD: Sep 1991
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; DISTRICT HEATING; OPTIMIZATION; COMPUTERIZED SIMULATION; FORECASTING; HEATING LOAD; 320106; BUILDING EQUIPMENT
OSTI ID:
10133561
Research Organizations:
Danmarks Tekniske Hoejskole, Lyngby (Denmark). Lab. for Varme- og Klimateknik
Country of Origin:
Denmark
Language:
English
Other Identifying Numbers:
Other: ON: DE92793303; CNN: Contract ENS-1323/91-0010; ISBN 87-88038-24-6; TRN: DK9201172
Availability:
OSTI; NTIS (US Sales Only)
Submitting Site:
DK
Size:
234 p.
Announcement Date:
Jul 04, 2005

Citation Formats

Benonysson, A. Dynamic modelling and operational optimization of district heating systems. Denmark: N. p., 1991. Web.
Benonysson, A. Dynamic modelling and operational optimization of district heating systems. Denmark.
Benonysson, A. 1991. "Dynamic modelling and operational optimization of district heating systems." Denmark.
@misc{etde_10133561,
title = {Dynamic modelling and operational optimization of district heating systems}
author = {Benonysson, A}
abstractNote = {This study deals with the developing and testing of methods for dynamic simulation and operational optimization of district heating systems. The performance of a number of models for simulating or predicting the heat load of consumers on a substation level was investigated through regression analysis, estimating the constants of the models on the basis of measured data. It was found that if the value of the most important climate variables were known, then the heat load could be simulated or predicted with reasonable accuracy in several ways, the actual purpose of it`s application being decisive for selection of model category. If the consumers` real supply temperature was known, then the return temperature could be estimated with accuracy on the basis of a linear combination of the heat load and the supply temperature only. For dynamic simulation of transient temperatures a new method was much faster and more accurate than the conventional method, and it was found capable of simulating transient temperatures in a district heating network built up of preinsulated pipes. One method for searching for optimum by comparing series of simulations, and another optimization based on determining the time delays and the temperature drop in the network iteratively by applying a standard optimization method for constrained problems were discussed. When formulating the problem as a standard constrained optimization problem applying a Lagrange minimization method available in a commecial program package, it was found that optimum could in most cases be located through an iterative process. Only in cases where the saving potential was very small, the method failed. (AB) 58 refs.}
place = {Denmark}
year = {1991}
month = {Sep}
}