The Campus Intelligent Electricity Management System Based On The Internet Of Things

With the continuous advancement of modern technology,the concept of smart cities and smart homes has been deeply rooted in the hearts of the people,and the construction of smart campuses is rising day by day.Due to the expansion of colleges and universities,the number of electrical equipment and instruments within colleges and universities is increasing,and the existing power management system is not perfect,which makes campus power management overwhelmed and unable to achieve effective management of electrical equipment.The campus intelligent power management system based on the Internet of Things researched in this subject can better solve the above problems,and can systematically and intelligently manage the overall power consumption of the campus.This system integrates the electrical equipment scattered on the campus into the system for centralized management through the Internet of Things technology.Users can log in to the system through the PC or mobile phone APP to realize the intelligent management of campus electricity.This topic analyzes the electricity consumption of the two places with the most frequent student activities-student apartments and teaching buildings,and conducts in-depth research on its electricity management.The system selects STM32 as the main control chip of the power consumption terminal,and selects RN8209 as the power consumption measurement chip.The microprocessor circuit,power acquisition circuit,relay control circuit,temperature and humidity data acquisition circuit are designed to realize the control of electrical equipment and data collection.The room controller uses Raspberry Pi as the hardware platform and is equipped with Linux operating system to realize intelligent control of terminals such as smart switches,sockets,temperature and humidity sensors.Aiming at the unreasonable use of electricity for lighting in teaching buildings,this thesis proposes a personnel distribution detection method based on the YOLO model,builds an operating environment for the YOLO model,and realizes accurate and rapid positioning of indoor personnel.After precise positioning of the personnel,the system divides the layout of the lighting fixtures in the classroom,establishes the corresponding relationship between the lighting and the positions of the desks and chairs,controls the fixtures according to the intelligent lighting strategy,and realizes the regional management of classroom lighting.The top priority of the student apartment’s electricity consumption is safe electricity usage.This article mainly focuses on the identification of malignant loads and the control of electricity usage.Commonly used loads in college apartments include mobile phones,desk lamps,computers,etc.,and vicious loads include high-power electrical appliances such as electric kettles,rice cookers,and heaters.This subject researches and analyzes the current characteristics between various loads.Among them,malignant loads are mainly resistive loads,which are characterized by high fundamental current components and weak higher harmonics.This feature is used for identification.By collecting six types of data features of DC component,fundamental component,3rd harmonic,5th harmonic,7th harmonic and 9th harmonic of various load currents,a feature matrix is formed to complete the collection of data sets.According to the current data between the loads,the difference of the current components is analyzed through MATLAB,and the waveform diagram and the spectrum diagram of the load are intuitively depicted.And based on the BP neural network vicious load recognition algorithm proposed in this thesis,the collected data set is trained to build a recognition model.Experimental results show that the algorithm can solve the problem of vicious load identification,and complete the control of electrical equipment based on the identification results.The experiment concludes that the campus intelligent electricity management system based on the Internet of Things researched in this subject has realized the intelligent management and control of campus electricity,can intelligently manage the lighting of the teaching building,and complete the accurate identification of the vicious load of the student apartment and the control of the electricity terminal,creating a smart and comfortable campus environment for students.