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Campus energy efficiency and electrical safety management method and system based on artificial intelligence technology

An artificial intelligence, electrical safety technology, applied in neural learning methods, artificial life, data processing applications, etc., can solve the lack of scene power consumption, it is difficult to uniformly monitor the actual use, the electrical fire warning and automatic management technology is not perfect, etc. problem, to achieve the effect of convenient energy consumption

Pending Publication Date: 2022-03-25
广州汇锦能效科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, its energy management and fire prevention work has the following limitations: There are many devices in the school, it is difficult to monitor the actual usage in a unified manner, and it is difficult to locate the main cause of abnormal power consumption. , There are many school personnel, and it is difficult to control high-power dangerous equipment, so many schools do not have reasonable energy management and electrical fire prevention systems
[0003] At present, the existing school energy consumption and safety management systems and methods have the following defects: energy consumption indicators are not clear, real-time indicators cannot be dynamically monitored, operability is poor, energy-saving space has not been further developed, and electrical fire early warning and automatic management Imperfect technology
This patent also has defects such as imperfect automatic management technology

Method used

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  • Campus energy efficiency and electrical safety management method and system based on artificial intelligence technology
  • Campus energy efficiency and electrical safety management method and system based on artificial intelligence technology
  • Campus energy efficiency and electrical safety management method and system based on artificial intelligence technology

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0087] This embodiment provides a campus energy efficiency and electrical safety management method based on artificial intelligence technology, such as figure 1 shown, including the following steps:

[0088] S1: Collect front-end real-time energy consumption data and environmental information;

[0089] S2: Classify and store the front-end real-time energy consumption data, environmental information and historical energy consumption data collected in step S1;

[0090] S3: Establish a BP neural network model based on the real-time energy consumption data, and use the particle swarm optimization algorithm to optimize the BP neural network model to predict the energy consumption of the campus. According to the prediction of the energy consumption of the campus, the energy waste location and reason;

[0091] S4: Find the corresponding energy-consuming equipment according to the location of energy waste, and automatically control the working status of the energy-consuming equipmen...

Embodiment 2

[0112] The basis of this embodiment in Embodiment 1 is that step S3 also includes establishing a prediction error estimation model, and when the error of the prediction of campus energy consumption is within the allowable range, the current campus energy consumption situation and the working mode with the lowest campus energy consumption Comparing and forming the energy cost report to obtain the location and cause of energy waste; when the error of the campus energy consumption prediction is not within the allowable range, re-collect the front-end real-time energy consumption data and environmental information, re-establish the BP neural network model, and use the particle swarm algorithm Optimizing the BP neural network model.

[0113] The prediction error estimation model is specifically:

[0114] S221: The predicted data result s of the BP neural network model optimized by the particle swarm optimization algorithm f and historical energy use data s q For comparison, calcu...

Embodiment 3

[0149] A campus energy efficiency and electrical safety management system based on artificial intelligence technology, such as image 3 As shown, it includes front-end data acquisition module, system data platform, energy analysis module, historical energy consumption analysis module, automatic supervision module and electricity safety warning module, among which:

[0150] The front-end data acquisition module collects front-end real-time energy consumption data and environmental information, and transmits them to the system data platform in real time;

[0151] The system data platform classifies and stores the front-end real-time energy consumption data and environmental information collected in real time together with historical energy consumption data;

[0152] The energy analysis module uses the real-time energy consumption data stored on the system data platform to establish a BP neural network model, and uses the particle swarm optimization algorithm to optimize the BP neu...

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PUM

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Abstract

The invention discloses a campus energy efficiency and electrical safety management method and system based on an artificial intelligence technology. The method comprises the following steps that S1, front-end real-time energy consumption data and environment information are collected; s2, performing classified storage on the front-end real-time energy consumption data and the environment information collected in the step S1 and historical energy consumption data; s3, establishing a BP neural network model according to the real-time energy consumption data, optimizing the BP neural network model by adopting a particle swarm algorithm to predict the campus energy consumption, and obtaining an energy waste position and a reason according to the prediction of the campus energy consumption; and S4, corresponding energy consumption equipment is found according to the energy waste position, and the working state of the energy consumption equipment is automatically controlled. According to the invention, intelligent energy management technologies such as energy dynamic monitoring information, energy consumption data analysis and information release, equipment energy-saving analysis, electric power safety protection and the like are provided for school management departments.

Description

technical field [0001] The present invention relates to the field of campus energy and electrical safety issues, and more specifically, to a campus energy efficiency and electrical safety management method and system based on artificial intelligence technology. Background technique [0002] With the change of the teaching environment and the development of teaching technology, the total energy consumption of the school continues to rise, and there is a serious waste of energy resources, and the school is a place with a relatively high population density, so electrical safety must be highly valued. Therefore, the work of energy saving, emission reduction and safety prevention is very important for schools. However, due to the large number and types of buildings in the school and the large area, the campus not only has public buildings such as teaching buildings, scientific research buildings, and administrative office buildings, but also residential buildings such as dormitor...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/10G06Q50/06G06N3/00G06N3/08G01D21/02
CPCG06Q10/04G06Q10/103G06Q50/06G06N3/006G06N3/084G01D21/02
Inventor 谭福太谢方静余昭胜林海陈庆文张渊晟马晓茜
Owner 广州汇锦能效科技有限公司
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