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Optimization of regional distributed energy systems using a P-median model based on energy distance
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DOI：10.1080/15567249.2026.2647241.png)
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Abstract
En 中文
Regional distributed energy systems (RDES) are promising for improving energy efficiency and reducing carbon emissions in cities and industrial parks. Yet, in many planning studies, station siting and network routing are optimized separately, and distance is often approximated by geometry or heuristics, making it hard to quantify supply-demand effective distance on a unified annualized-cost basis and to obtain reproducible global optima. This work develops a source-network-load topological graph model and proposes an energy-distance metric that incorporates annualized pipeline investment, pumping electricity consumption, transmission/distribution losses, and operation-and-maintenance depreciation. Based on this metric, an improved P-median formulation enables coordinated optimization of energy-station siting and cooling/heating/electricity network layouts. The Floyd shortest-path algorithm and a minimum spanning tree method are integrated, while candidate station-location combinations are exhaustively enumerated to guarantee a globally optimal solution within the finite search space. A case study in the western area of Songshan Lake (Guangdong Province, China) validates the framework: the selected configuration achieves an energy distance of $843M. Compared with a conventional centralized scheme, total investment cost is reduced by 33.4% and annual operating cost by 46.0%. Relative to peer optimization methods, overall cost decreases by 8.9-16.8%, and energy utilization efficiency increases by 4.0-13.8%. The proposed approach links annualized cost, network structure, and station-location combinations, providing a practical and reliable decision framework for low-carbon RDES planning under coverage and implementability constraints.
Keywords:
Determining locations and pipelines algorithm
energy distance
energy efficiency
P-median model
regional distributed energy system (RDES)
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2.2
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1.1K
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1.5K
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