District heating temperature control algorithm based on short term weather forecast and consumption predictions

Nikolaos Papakonstantinou, Jouni Savolainen, Jarmo Koistinen, Antti Aikala, Valeriy Vyatkin

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

3 Citations (Scopus)

Abstract

District heating grids are complex systems where energy production has to match the consumption load while key system parameters like temperatures and pressures through the grid have to be kept within limits. The choice of a control strategy for the grid depends on the selected key performance indicators. The scientific contribution of this paper is a methodology for controlling the supply water temperature setpoint of a heat power plant using heat consumption predictions. The proposed algorithm aims to provide more heat energy to the difficult consumers when they need it the most. The required input information are the short term weather forecast, the supply hot water temperature propagation delays of the district heating grid as a function of the grid load level and consumption profiles based on historical data or heat consumption models. The methodology is applied on a simplified case study of a 120MW district heating grid. The results showed that within a specific supply water temperature range the performance of the grid in terms of minimum pressure difference at the consumers over a year was significantly better using the proposed proactive algorithm compared to simple reactive and constant temperature control strategies.
Original languageEnglish
Title of host publicationEmerging Technologies and Factory Automation (ETFA), 2016 IEEE 21st International Conference on
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages1-8
ISBN (Electronic)978-1-5090-1314-2, 978-1-5090-1313-5
ISBN (Print)978-1-5090-1315-9
Publication statusPublished - 7 Nov 2016
MoE publication typeA4 Article in a conference publication
Event21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2016 - Berlin, Germany
Duration: 6 Sep 20169 Sep 2016
Conference number: 21

Conference

Conference21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2016
Abbreviated titleETFA 2016
CountryGermany
CityBerlin
Period6/09/169/09/16

Fingerprint

District heating
Temperature control
Water supply
Temperature
Large scale systems
Power plants
Hot Temperature
Water

Keywords

  • district heating
  • apros
  • control
  • CHP

Cite this

Papakonstantinou, N., Savolainen, J., Koistinen, J., Aikala, A., & Vyatkin, V. (2016). District heating temperature control algorithm based on short term weather forecast and consumption predictions. In Emerging Technologies and Factory Automation (ETFA), 2016 IEEE 21st International Conference on (pp. 1-8). IEEE Institute of Electrical and Electronic Engineers .
Papakonstantinou, Nikolaos ; Savolainen, Jouni ; Koistinen, Jarmo ; Aikala, Antti ; Vyatkin, Valeriy. / District heating temperature control algorithm based on short term weather forecast and consumption predictions. Emerging Technologies and Factory Automation (ETFA), 2016 IEEE 21st International Conference on. IEEE Institute of Electrical and Electronic Engineers , 2016. pp. 1-8
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abstract = "District heating grids are complex systems where energy production has to match the consumption load while key system parameters like temperatures and pressures through the grid have to be kept within limits. The choice of a control strategy for the grid depends on the selected key performance indicators. The scientific contribution of this paper is a methodology for controlling the supply water temperature setpoint of a heat power plant using heat consumption predictions. The proposed algorithm aims to provide more heat energy to the difficult consumers when they need it the most. The required input information are the short term weather forecast, the supply hot water temperature propagation delays of the district heating grid as a function of the grid load level and consumption profiles based on historical data or heat consumption models. The methodology is applied on a simplified case study of a 120MW district heating grid. The results showed that within a specific supply water temperature range the performance of the grid in terms of minimum pressure difference at the consumers over a year was significantly better using the proposed proactive algorithm compared to simple reactive and constant temperature control strategies.",
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Papakonstantinou, N, Savolainen, J, Koistinen, J, Aikala, A & Vyatkin, V 2016, District heating temperature control algorithm based on short term weather forecast and consumption predictions. in Emerging Technologies and Factory Automation (ETFA), 2016 IEEE 21st International Conference on. IEEE Institute of Electrical and Electronic Engineers , pp. 1-8, 21st IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2016, Berlin, Germany, 6/09/16.

District heating temperature control algorithm based on short term weather forecast and consumption predictions. / Papakonstantinou, Nikolaos; Savolainen, Jouni; Koistinen, Jarmo; Aikala, Antti; Vyatkin, Valeriy.

Emerging Technologies and Factory Automation (ETFA), 2016 IEEE 21st International Conference on. IEEE Institute of Electrical and Electronic Engineers , 2016. p. 1-8.

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

TY - GEN

T1 - District heating temperature control algorithm based on short term weather forecast and consumption predictions

AU - Papakonstantinou, Nikolaos

AU - Savolainen, Jouni

AU - Koistinen, Jarmo

AU - Aikala, Antti

AU - Vyatkin, Valeriy

N1 - Project : 106498

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Y1 - 2016/11/7

N2 - District heating grids are complex systems where energy production has to match the consumption load while key system parameters like temperatures and pressures through the grid have to be kept within limits. The choice of a control strategy for the grid depends on the selected key performance indicators. The scientific contribution of this paper is a methodology for controlling the supply water temperature setpoint of a heat power plant using heat consumption predictions. The proposed algorithm aims to provide more heat energy to the difficult consumers when they need it the most. The required input information are the short term weather forecast, the supply hot water temperature propagation delays of the district heating grid as a function of the grid load level and consumption profiles based on historical data or heat consumption models. The methodology is applied on a simplified case study of a 120MW district heating grid. The results showed that within a specific supply water temperature range the performance of the grid in terms of minimum pressure difference at the consumers over a year was significantly better using the proposed proactive algorithm compared to simple reactive and constant temperature control strategies.

AB - District heating grids are complex systems where energy production has to match the consumption load while key system parameters like temperatures and pressures through the grid have to be kept within limits. The choice of a control strategy for the grid depends on the selected key performance indicators. The scientific contribution of this paper is a methodology for controlling the supply water temperature setpoint of a heat power plant using heat consumption predictions. The proposed algorithm aims to provide more heat energy to the difficult consumers when they need it the most. The required input information are the short term weather forecast, the supply hot water temperature propagation delays of the district heating grid as a function of the grid load level and consumption profiles based on historical data or heat consumption models. The methodology is applied on a simplified case study of a 120MW district heating grid. The results showed that within a specific supply water temperature range the performance of the grid in terms of minimum pressure difference at the consumers over a year was significantly better using the proposed proactive algorithm compared to simple reactive and constant temperature control strategies.

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KW - control

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Papakonstantinou N, Savolainen J, Koistinen J, Aikala A, Vyatkin V. District heating temperature control algorithm based on short term weather forecast and consumption predictions. In Emerging Technologies and Factory Automation (ETFA), 2016 IEEE 21st International Conference on. IEEE Institute of Electrical and Electronic Engineers . 2016. p. 1-8