Deep learning-based intelligent energy conservation for tunnel water fire-fighting electric heat tracing system

ObjectiveAiming at the common problems of low intelligent temperature control and high energy consumption in water fire-fighting electric heat tracing system for highway tunnel in alpine regions, this study proposes a deep learning-based intelligent energy conservation method for tunnel water fire-fighting electric heat tracing.MethodThe proposed method employed two-tier control architecture comprising local control and remote optimization decision-making. First, at the local control tier, a mathematical model of electric heat tracing system exhibiting large-inertia characteristics was derived based on the law of energy conservation and thermal balance equations. This model was used to design the fuzzy PID controller capable of adaptively adjusting control parameters to achieve precise temperature regulation. At the remote optimization decision-making tier, a complex nonlinear mapping model between key parameters (e.g., ambient temperature, electric heat tracing power, temperature setpoint, actual heat tracing system temperature) and heating efficiency was constructed by using one-dimensional convolutional neural networks (1DCNN) and XGBoost. A genetic optimization algorithm was then applied to perform single-objective optimization on temperature setpoint, ensuring system consistently operating in conditions of highest heating efficiency and optimal energy performance.ResultCompared with deep belief network model, 1DCNN-XGBoost combined prediction model demonstrates superior prediction accuracy for heating efficiency. The validation based on measured data from a highway tunnel in Hebei Province indicates that the proposed method achieves an average reduction in energy consumption of approximately 40% compared with traditional approaches.Conclusion1DCNN-XGBoost combined prediction model coupled with the genetic optimization algorithm substantially reduces energy consumption in tunnel water fire-fighting electric heat tracing system, and significantly enhances the intelligence of temperature control.The findings provide effective energy-saving control scheme for alpine tunnel water fire-fighting electric heating tracing system.