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基于随机森林算法的不同使用场景5G基站电量预测研究

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为实现在电网规划中考虑 5G基站的大规模建设所带来的电能需求,针对该负荷的长期负荷预测问题,提出了随机森林预测方法和用电预测流程.通过超参数修正,改进了随机森林模型.在考虑技术进步对能耗的影响以及未来发展饱和趋势的条件下,给出了 5G基站电量预测流程,实现了 5G基站短期电量预测,并给出不同使用场景的预测结果,为电网规划中考虑信息基础设施电能需求提供了依据.
Research on 5G base station electricity prediction based on random forest algorithm
In order to consider the electricity demand brought by the large-scale construction of 5G base stations in power grid planning,a random forest prediction method and electricity consumption prediction process are proposed for the long-term load forecasting problem of this load.The random forest model has been improved through hyperparameter correction.Taking into account the impact of technological progress on energy consumption and the saturation trend of future development,a 5G base station electricity consumption prediction process was proposed,achieving short-term electricity consumption prediction for 5G base stations and providing prediction results,providing a basis for considering information infrastructure electricity demand in power grid planning.

5G base stationrandom forestenergy utilization planning

姜山、窦家本、申通、赵英鹏

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国网北京延庆供电公司,北京 102100

5G基站 随机森林 用能规划

2024

中国高新科技
中华预防医学会,国家食品安全风险评估中心

中国高新科技

ISSN:
年,卷(期):2024.(18)
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