Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm
The intelligent upgrade of heating systems faces the challenge of accurately identifying high-dimensional pipe-network resistance coefficients; difficulties in accomplishing this can lead to hydraulic imbalance and redundant energy consumption. To address the limitations of traditional Differential...
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MDPI AG
2025-07-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/15/15/2701 |
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| author | Enze Zhou Yaning Liu Minjia Du Junli Yu Wenxiao Xu |
| author_facet | Enze Zhou Yaning Liu Minjia Du Junli Yu Wenxiao Xu |
| author_sort | Enze Zhou |
| collection | DOAJ |
| description | The intelligent upgrade of heating systems faces the challenge of accurately identifying high-dimensional pipe-network resistance coefficients; difficulties in accomplishing this can lead to hydraulic imbalance and redundant energy consumption. To address the limitations of traditional Differential Evolution (DE) algorithms under high-dimensional operating conditions, this paper proposes an Improved Differential Evolution Algorithm (SDEIA) incorporating chaotic mapping, adaptive mutation and crossover strategies, and an immune mechanism. Furthermore, a multi-constrained identification model is constructed based on Kirchhoff’s laws. Validation with actual engineering data demonstrates that the proposed method achieves a lower average relative error in resistance coefficients and exhibits a more concentrated error distribution. SDEIA provides a high-precision tool for multi-heat-source networking and dynamic regulation in heating systems, facilitating low-carbon and intelligent upgrades. |
| format | Article |
| id | doaj-art-a30e74b8d3c447d48367f20a5cd429bd |
| institution | Kabale University |
| issn | 2075-5309 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj-art-a30e74b8d3c447d48367f20a5cd429bd2025-08-20T03:36:31ZengMDPI AGBuildings2075-53092025-07-011515270110.3390/buildings15152701Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution AlgorithmEnze Zhou0Yaning Liu1Minjia Du2Junli Yu3Wenxiao Xu4College of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, ChinaDiehl Metering (Jinan) Co., Ltd., Jinan 250100, ChinaThe intelligent upgrade of heating systems faces the challenge of accurately identifying high-dimensional pipe-network resistance coefficients; difficulties in accomplishing this can lead to hydraulic imbalance and redundant energy consumption. To address the limitations of traditional Differential Evolution (DE) algorithms under high-dimensional operating conditions, this paper proposes an Improved Differential Evolution Algorithm (SDEIA) incorporating chaotic mapping, adaptive mutation and crossover strategies, and an immune mechanism. Furthermore, a multi-constrained identification model is constructed based on Kirchhoff’s laws. Validation with actual engineering data demonstrates that the proposed method achieves a lower average relative error in resistance coefficients and exhibits a more concentrated error distribution. SDEIA provides a high-precision tool for multi-heat-source networking and dynamic regulation in heating systems, facilitating low-carbon and intelligent upgrades.https://www.mdpi.com/2075-5309/15/15/2701heating networkresistance coefficient identificationdifferential evolution algorithmimmune mechanismadaptivealgorithm optimization |
| spellingShingle | Enze Zhou Yaning Liu Minjia Du Junli Yu Wenxiao Xu Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm Buildings heating network resistance coefficient identification differential evolution algorithm immune mechanism adaptive algorithm optimization |
| title | Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm |
| title_full | Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm |
| title_fullStr | Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm |
| title_full_unstemmed | Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm |
| title_short | Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm |
| title_sort | identification method for resistance coefficients in heating networks based on an improved differential evolution algorithm |
| topic | heating network resistance coefficient identification differential evolution algorithm immune mechanism adaptive algorithm optimization |
| url | https://www.mdpi.com/2075-5309/15/15/2701 |
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