Prediction of Effluent Temperature of Coolant in Cogeneration System Based on GA-BP Neural Network

The cogeneration system coolant is an antifreeze to ensure the effective operation of the cogeneration system. The coolant outlet temperature is too high or too low, which will affect the safe operation of the cogeneration system. Therefore, the cogeneration system coolant effluent Temperature research is very important. In the commonly used methods, the coolant effluent temperature is monitored without excessive prediction methods. To this end, this paper proposes a prediction model based on genetic algorithm to optimize BP neural network. Before establishing the prediction model of the effluent temperature of the GA-BP neural network cogeneration system, the genetic algorithm first optimizes the initial weight threshold of the BP neural network to reach the optimal weight threshold, and finally establishes the collected data pair. The validity and accuracy of the prediction model are verified.