Abstract
With the development of the Energy Internet of Things (EIoT), it is of great practical significance to study the security strategy and intelligent control system for solar thermal utilization system to optimize the operation efficiency and carry out intelligent dynamic adjustment. For buildings integrated with solar water heating systems, computational fluid dynamics simulation was used in analyzing the process of solar energy output. A method based on machine learning is proposed to predict energy conversion. Besides, the simulation and analysis are carried out in combination with the possible safety problems such as the vibration of the control system. This paper proposed a novel platform of EIoT for machine learning-based cybersecurity study and implemented the platform for the temperature monitoring system. After the evaluation of the machine learning-based cybersecurity study, the EIoT system demonstrated a high performance with the Extreme Gradient Boosting (XGBoost) training algorithm.
Highlights
With the resonant coupling of multiple energy sources, the new energy supply system under the background of the Internet of ings will have the characteristics of multienergy complementation and synergy [1,2,3]. e traditional thermal and electric demand response will gradually develop into a comprehensive demand response suitable for integrated energy systems. e EIoT (Energy Internet of ings) has brought a better operation, monitoring, and management mode for the new energy utilization systems
When we develop a system that uses text data for classification, we can adopt the machine learning (ML) method to process the data and set our system according to the actual situation. e researchers above have given us an idea to use ML to design a new platform for the temperature monitoring system. e system is equipped with high security and privacy and can be applied to daily life
Discussion on Specific Temperature Control System Usage Scenarios and the Attack. e solar heating system is the most widely used solar energy utilization system. e dynamic modelling, characteristic analysis, and optimal control of solar heating systems play an essential role in promoting intelligent applications, safety, and convenience. e numerical calculation method of the dynamic thermal characteristics of the solar heating system is an effective means for the thermal dynamic modelling and analysis of the heating pipe network
Summary
With the resonant coupling of multiple energy sources, the new energy supply system under the background of the Internet of ings will have the characteristics of multienergy complementation and synergy [1,2,3]. e traditional thermal and electric demand response will gradually develop into a comprehensive demand response suitable for integrated energy systems. e EIoT (Energy Internet of ings) has brought a better operation, monitoring, and management mode for the new energy utilization systems. E EIoT (Energy Internet of ings) has brought a better operation, monitoring, and management mode for the new energy utilization systems. It uses advanced sensors, control, and software applications to connect a large number of equipment, machines, and systems at the energy production side, energy transmission side, and energy consumption side to form the “Internet of ings foundation” [4]. Erefore, in the solar water heating system, the sensor measurement technology, numerical simulation technology, Internet of ings technology, and machine learning technology can be used to remote monitoring of the control parameters, heat gain, and status of the solar water heating engineering system, so as to realize the saving, comfortable, efficient and reliable water, energy and heat consumption, which has strong practical application value [5]. When we develop a system that uses text data for classification, we can adopt the ML method to process the data and set our system according to the actual situation. e researchers above have given us an idea to use ML to design a new platform for the temperature monitoring system. e system is equipped with high security and privacy and can be applied to daily life
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