Heat supply system supply and return water temperature prediction method and device

Abstract

The invention provides a heat supply system supply and return water temperature prediction method and device. The method comprises the steps of obtaining historical data of the heat supply system, wherein the historical data at least comprise the heat source water supply temperature, the heat source water return temperature, the average indoor temperature of a user in a heat supply area and the outdoor temperature; establishing a relation model between the water supply temperature and the return water temperature and the average indoor temperature and the outdoor temperature of the user based on a physics principle, and training parameters of the model by utilizing historical data so as to obtain a prediction model of the water supply temperature and the return water temperature; and obtaining outdoor temperature and expected indoor average temperature of a prediction date, wherein water supply temperature and water return temperature of the prediction date are calculated according to the prediction model. Compared with non-physical models such as a neural network and a support vector machine established in the prior art, the prediction model of the supply water temperature and the return water temperature is established based on the physics principle, and the method has the advantages of simple model structure, high training and operation speed, high prediction precision and the like.

Description

technical field [0001] The invention belongs to the technical field of heating systems, and in particular relates to a method and device for predicting the temperature of supply and return water in a heating system. Background technique [0002] Common heat sources for central heating systems include thermal power plants, regional boiler rooms and centralized boiler rooms. The regional boiler room includes a direct supply system (only the primary network) and an indirect supply system (including the primary network and the secondary network). The intermittent supply system generally sends the steam or hot water generated by the heat source to the primary network; then transfers the heat of the steam or hot water from the primary network to the secondary network through the heat exchanger of the heat exchange station; finally passes through the secondary network The heat is sent to the user, and the user dissipates the heat to the room through the indoor radiator, so that th...

AI Technical Summary

Problems solved by technology

Since the heating system is a very complex nonlinear network, the structure of non-physical models such as neural network and support vector machine must also be very complex, and the complex model structure will seriously affect the training and running speed of the model, predicting Accuracy is also difficult to meet the requirements

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