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SIMULATION OF ELECTRIC HEATING PREDICTION MODEL BY INTERNET OF THINGS TECHNOLOGY AND ROOM THERMAL PERFORMANCE ANALYSIS

ABSTRACT
The fault diagnosis and fault-tolerant control of electric heating distributed control system are improved by the thermal performance analysis of rooms. The given values are tracked to meet the heating requirements, and the reliability of heating is increased without increasing hardware resources, which improves the reliability and economy of electric heating. From the perspective of energy conservation of electric heating for buildings and rooms, a predictive control model based on load-side three-phase power self-balance is proposed. A fault tolerance method for the electric heating distributed control system control system heating is designed. The load-side three-phase power self-balancing method of the electric heating control system is implemented by using the advantages of the Internet of Things and the heat storage performance of a room, which is its characteristics. Simulation results show that the performance of predictive control for non-minimum phase process is significantly better than that of conventional proportion integral differential control. For complex control problems, predictive control technology can provide better control performance than proportion integral differential control technology. Without increasing any hardware resources, reliable and economical heating is achieved through software.
KEYWORDS
predictive control algorithm, electric heating, DCS control system, fault tolerance rate, fault diagnosis efficiency
PAPER SUBMITTED: 2019-11-09
PAPER REVISED: 2019-12-17
PAPER ACCEPTED: 2020-01-18
PUBLISHED ONLINE: 2020-02-29
DOI REFERENCE: https://doi.org/10.2298/TSCI191109088Q
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2020, VOLUME 24, ISSUE Issue 5, PAGES [3139 - 3147]
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Simulation of electric heating prediction model by internet of things technology and room thermal performance analysis

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence