Dynamic heating control measured and simulated effects on power reduction, energy and indoor air temperature in an old apartment building with district heating

Hajian, Hatef; Ahmed, Kaiser; Kurnitski, Jarek

doi:10.1016/j.enbuild.2022.112174

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…The dynamic heating control implementation is shown in Figure 6. [10]. To be able to compare the SH and total heat exchanger power in different scenarios with the conventional model, the design DHW heat exchanger power was computed based on the Finnish design guidelines for water installation (D1/2007 Annex 2) [21].…”

Section: Conventional and Dynamic Heating Curve With Ideal Plantmentioning

confidence: 99%

“…Moreover, an online structural and parametric learning method was utilized by Ionesi et al (2015) to develop a heating curve that increased thermal comfort and reduced space heating energy by 5% [9]. Hajian et al (2021) attempted to develop a dynamic heating control method, which resulted in significant power savings [10]. Their proposed dynamic heating control algorithm was performed according to the following criteria: (a) minimum indoor air temperature across all zones, (b) heating curve supply temperature based on outdoor temperature, and (c) Domestic Hot Water (DHW) compensation temperature at high DHW flow rate usage.…”

Section: Introductionmentioning

confidence: 99%

“…Hajian et al (2021) validated and calibrated the conventional model against the onsite data with high accuracy [16]. Subsequently, Hajian et al verified the dynamic heating control model against measured data[10]. To be able to compare the SH and total heat exchanger power in different scenarios with the conventional model, the design DHW heat exchanger power was computed based on the Finnish design guidelines for water installation (D1/2007 Annex 2)[21].…”

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confidence: 99%

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Heating Sizing Power Reduction in Buildings Connected to District Heating with Dynamically Controlled DHW Setback and Flow Limiters

2022

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Space Heating (SH) substations in District Heating-based (DH) systems are typically dimensioned at the design outdoor temperature without accounting for internal and solar heat gains. In residential buildings, the total required DH power typically also includes the need for Domestic Hot Water (DHW). This practice results in oversized substations and high DH design flow rates, which, due to heat gains and building thermal mass utilization in building operation, rarely, if ever, occur. Modern buildings maintain the desired indoor temperature with lower heating power by controlling the SH supply temperature with an outdoor-air-dependent heating curve and heating water flow with room unit thermostats. Applying a dynamic heating control algorithm can be considered one option to reduce the required DH power and optimize the DH network. Another possibility to decrease the needed power is controlling the DH flow by prioritizing DHW production and limiting the DH flow for SH. This study proposed a novel sizing method for the DH substation that quantifies the effects of dynamic control and flow limiters. Building models with detailed hydronic plants, accounting for internal heat gains, and using conventional and dynamic heating controls were developed in the IDA Indoor Climate and Energy simulation tool. The results show a potential DH side power reduction of up to 25%.

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Section: Conventional and Dynamic Heating Curve With Ideal Plantmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Heating Sizing Power Reduction in Buildings Connected to District Heating with Dynamically Controlled DHW Setback and Flow Limiters

2022

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“…It should be emphasized here that in Poland, nearly all buildings are equipped with heat meters. However, it is required that energy consumption should be monitored in detail, technical systems should be properly managed and their performance parameters controlled, which should ultimately lead to rational energy management in the building [17,18].…”

Section: Introductionmentioning

confidence: 99%

“…The value of the PE H index depends on the value of the building indicators of usable, final energy and primary energy factor [3,[19][20][21]. The building usable energy demand, expressed through the usable energy demand, is influenced by: climatic conditions related to the location of the building, its orientation relative to world directions, internal heat gains and building envelope parameters, such as thermal insulation of building partitions, protection properties against wind, building glazing, shading of transparent partitions and their ability to transmit solar radiation [18,[22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of the Variability of Energy Efficiency Indicators for a Multi-Family Residential Building

et al. 2022

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During the building design phase, a lot of attention is paid to the thermal properties of the external envelopes. New regulations are introduced to improve energy efficiency of a building and impose a reduction of the overall heat transfer coefficient; meanwhile, this efficiency is more influenced by the efficiency of the heating system and the type of fuels used. This article presents a complex analysis including the impact of: heat transfer coefficient of the envelope, efficiency of building service systems, the type of energy source, and the fuel. The analysis was based on the results of simulation tests obtained for an exemplary multi-family residential building located in Poland that is not equipped with a cooling system. The conducted calculations gave quantitative evaluation of the influence of particular parameters on building energy performance and showed that the decrease of heat transfer coefficient of building boundaries, in accordance to the Polish regulation for 2017 and 2021, gave only 11% of reduction on usable energy demand index. On the other hand, it was found that modification of the heating system and heat source can significantly influence the values of the final and primary energy consumption at the level of 70%. The application of heat pumps has a greater influence on the final and primary energy consumption for heating indices than other parameters, such as the building’s envelopes.

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Temperature Control Technology in Heating Room Based on Multi-channel Temperature Signal Denoising

Liu,

Chen,

Yin

et al. 2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Dynamic heating control measured and simulated effects on power reduction, energy and indoor air temperature in an old apartment building with district heating

Cited by 10 publications

References 19 publications

Heating Sizing Power Reduction in Buildings Connected to District Heating with Dynamically Controlled DHW Setback and Flow Limiters

Heating Sizing Power Reduction in Buildings Connected to District Heating with Dynamically Controlled DHW Setback and Flow Limiters

Statistical Analysis of the Variability of Energy Efficiency Indicators for a Multi-Family Residential Building

Temperature Control Technology in Heating Room Based on Multi-channel Temperature Signal Denoising

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