Quick calculation method for building representative temperature

Abstract

The invention relates to a quick calculation method for building representative temperature. According to the method, a user heat consumption weight reference value is calculated according to previoususer heat consumption data, the occupancy rate of a building is counted through thousands and tens of thousands of user room temperature collected by room temperature collectors, the occupancy rate can not change in a short time once the occupancy rate is determined, then typical user heat consumption weight values can be determined, most room temperature collectors can be in an unworking state at the moment, only the room temperature collectors of users at the typical positions are in a normally-opened state to collect the room temperature of the users at the typical positions in real time,then the building representative temperature capable of feeding back the system heat supply effect can be obtained in real time, and therefore the building representative temperature can serve as a feedback value to correct a heat supply system running control strategy while the building representative temperature supplies reference bases to the heat supply effect of a heat supply unit. Through running of the room temperature collectors of the users at the typical positions, the running cost of the room temperature collectors of the whole building is greatly reduced, and higher economical efficiency and higher efficiency are achieved.

Description

technical field [0001] The invention relates to the technical field of calculation of heating effect feedback parameters in a heating system, in particular to a fast calculation method of representative building temperature. Background technique [0002] The heating system regulates the entire system with reference to the outdoor temperature and room temperature. As a feedback parameter, the room temperature can reflect the heating effect of the building as a whole, correct the heating control curve, optimize the operation adjustment strategy, and achieve the purpose of optimizing operation management and fine regulation; In terms of primary network and heat source control, the existing technologies mostly process and analyze the user’s room temperature data based on experience. The workload is heavy and the timeliness is not high. At the same time, each room temperature collector is always in the working state, and there is a lot of energy waste. . [0003] Fu Qiang from B...

AI Technical Summary

Problems solved by technology

This division is to analyze the whole community. For the whole community, the buildings are divided into far, middle and near according to the distance from the heat exchange station. For the whole building, it is divided into three parts: high, medium and low according to the height of the building floors. Solve the representative temperature, there is a large amount of data and low accuracy in the selection of the user's location

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