Optimization design of centralized and decentralized energy systems in regional building complexes based on geographical information system and load density

Optimization of regional energy systems is essential for improving efficiency and reducing emissions in the building sector, where the selection of supply modes directly shapes economic and environmental outcomes. This study proposes a comprehensive planning framework for regional building complexes, with load density as the primary criterion. A feasibility screening mechanism for centralized systems is developed by integrating building typologies with property management characteristics. Geographic information system–based kernel density estimation is then applied to identify demand aggregation patterns, thereby guiding optimal energy station siting and capacity allocation. In addition, a multi-dimensional evaluation model combining load density, economic performance, and carbon intensity establishes quantitative criteria for selecting decentralized systems. Results show that centralized energy stations are optimal for high load densities (q > 140 W/m2), integrated heat pump–chiller systems for moderately high densities (140 W/m2 ≥ q > 120 W/m2), and multi-split or split air conditioners for commercial and residential buildings under low densities (q ≤ 120 W/m2). An empirical case study in Huzhou, China, demonstrates reductions of 22.9% in annual cost per unit area and 10.9% in carbon intensity, validating the framework’s effectiveness. This research provides theoretical and technical support for decision-makers in the selection of energy systems.

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Publication Details

Journal
Energy Sources Part A Recovery Utilization and Environmental Effects
Published
2026-10-29
DOI
https://doi.org/10.1080/15567036.2026.2752110
Primary Topic
Integrated Energy Systems Optimization
Type
article
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article

Optimization design of centralized and decentralized energy systems in regional building complexes based on geographical information system and load density

Yingjun Ruan, Wenwen Zhang, Chengliang Lu, Yuting Yao et al.
Energy Sources Part A Recovery Utilization and Environmental Effects
Integrated Energy Systems Optimization
article

Optimization design of centralized and decentralized energy systems in regional building complexes based on geographical information system and load density

Yingjun Ruan, Wenwen Zhang, Chengliang Lu, Yuting Yao, Yueqiu Xia, Songsong Zheng, Tingting Xu, Jun Xu, Qingrong Liu, Hua Meng
article en

Abstract

Optimization of regional energy systems is essential for improving efficiency and reducing emissions in the building sector, where the selection of supply modes directly shapes economic and environmental outcomes. This study proposes a comprehensive planning framework for regional building complexes, with load density as the primary criterion. A feasibility screening mechanism for centralized systems is developed by integrating building typologies with property management characteristics. Geographic information system–based kernel density estimation is then applied to identify demand aggregation patterns, thereby guiding optimal energy station siting and capacity allocation. In addition, a multi-dimensional evaluation model combining load density, economic performance, and carbon intensity establishes quantitative criteria for selecting decentralized systems. Results show that centralized energy stations are optimal for high load densities (q > 140 W/m2), integrated heat pump–chiller systems for moderately high densities (140 W/m2 ≥ q > 120 W/m2), and multi-split or split air conditioners for commercial and residential buildings under low densities (q ≤ 120 W/m2). An empirical case study in Huzhou, China, demonstrates reductions of 22.9% in annual cost per unit area and 10.9% in carbon intensity, validating the framework’s effectiveness. This research provides theoretical and technical support for decision-makers in the selection of energy systems.

Energy Sources Part A Recovery Utilization and Environmental EffectsVol. 48(1)
Tongji University (CN), Shanghai University of Electric Power (CN), Robotics Research (United States) (US), State Grid Zhejiang Electric Power Company (China) (CN)
Openalex Percentile: Top 24%
Integrated Energy Systems Optimization
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