Integrated energy solutions for airports and high-speed rail stations
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Through the national standard energy consumption real-time acquisition system, accurate monitoring and intelligent analysis of energy data are realized. The system dynamically adjusts the operation of lighting, fresh air, and heating and cooling equipment in combination with the traffic schedule and meteorological data; uses machine learning algorithms to generate predictive control strategies, breaking through the spatiotemporal delay effect of energy transmission and distribution; relies on AI to build a dynamic energy consumption model, corrects parameters in real time and generates fault prediction and prevention plans, simultaneously carrying out carbon emission trend deduction, providing multi-dimensional decision support for green and low-carbon operation.
- 产品描述
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- Commodity name: Integrated energy solutions for airports and high-speed rail stations
Through the national standard energy consumption real-time collection system, accurate monitoring and intelligent analysis of energy data are realized. The system combines traffic schedules and meteorological data to dynamically adjust the operation of lighting, fresh air, and heating and cooling source equipment; uses machine learning algorithms to generate predictive control strategies, breaking through the spatio-temporal delay effect of energy transmission and distribution; relies on AI to build a dynamic energy consumption model, corrects parameters in real time and generates fault warning and contingency plans, simultaneously carrying out carbon emission trend deduction, providing multi-dimensional decision support for green and low-carbon operation.
Through the national standard energy consumption real-time acquisition system, accurate monitoring and intelligent analysis of energy data are realized. The system dynamically adjusts the operation of lighting, fresh air, and heating and cooling equipment in combination with the traffic schedule and meteorological data; uses machine learning algorithms to generate predictive control strategies, breaking through the spatiotemporal delay effect of energy transmission and distribution; relies on AI to build a dynamic energy consumption model, corrects parameters in real time and generates fault prediction and prevention plans, simultaneously carrying out carbon emission trend deduction, providing multi-dimensional decision support for green and low-carbon operation.
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