Macro-Level Energy Demand Model for Cellular Telecommunication Networks
The surge in digital services and video streaming has considerably increased wireless broadband traffic, prompting telecom operators to rapidly expand their network infrastructure. The infrastructure of base transceiver stations (BTSs) must be upgraded to meet the growing customer demand while ensur...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11127072/ |
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| Summary: | The surge in digital services and video streaming has considerably increased wireless broadband traffic, prompting telecom operators to rapidly expand their network infrastructure. The infrastructure of base transceiver stations (BTSs) must be upgraded to meet the growing customer demand while ensuring efficient energy use. To date, no macro-level framework has been established for calculating the energy demand in cellular networks using BTS site representations and stock composition variations as essential tools for monitoring energy management. This study proposes a framework for modeling the energy demand for cellular networks with such analytical capability. It includes two key modeling elements: 1) BTS site stock, including the composition of site types at the municipal level, differentiated by socioeconomic status and 2) energy demand at the BTS site level, estimated using archetypes that represent physical and technical characteristics. The framework was validated through a case study of the Indonesian cellular network using data from >8,500 BTS site samples across 20 municipalities. Results revealed the spatiotemporal characteristics of energy demand, with a total electricity demand of 5.37 TWh/year or 613.5 MW on average, equivalent to ~2% of the total Indonesian electricity demand in 2022. The proposed framework can be extended to other regions with limited data availability using the developed BTS site archetypes and statistical models of BTS site stock. Using the characteristic representation of BTS sites, the archetype-based approach can be used for quantifying the potential contribution of hybrid renewable energy systems, thereby accelerating the telecommunication industry’s clean energy transition and fostering implementation sustainability. |
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| ISSN: | 2169-3536 |