Energy-saving building micro-region staff interactive thermal comfort degree adjusting method

Abstract

The invention discloses an energy-saving building micro-region staff interactive thermal comfort degree adjusting method. The energy-saving building micro-region staff interactive thermal comfort degree adjusting method comprises the steps that a building is divided into micro-regions; a plurality of user thermal comfort degree intention temperatures in the micro-regions are collected; each user thermal comfort degree intention temperature plus a user thermal sensation calibration to serve as feedback input, training and learning are performed, and the user average thermal comfort degree intention temperature in each micro-region is obtained and subjected to variance calculation; and the environment temperatures of the micro-regions are monitored, the environment temperatures, the user average thermal comfort degree intention temperatures and the variances of the user average thermal comfort degree intention temperatures serve as input of a built thermal comfort behavioral model, the thermal gain function and thermal cost in the model are subjected to optimal balance solution calculation through a united convex optimization algorithm, a optimal solution is obtained, and HVAC self-adaption adjustment is conducted according to the optimal solution till the user thermal comfort gain reaches the set threshold value. According to the energy-saving building micro-region staff interactive thermal comfort degree adjusting method, electric energy can be effectively used while the user thermal comfort benefit is optimized, and the energy saving purpose is achieved.

Description

technical field [0001] The invention relates to an energy-saving building micro-region personnel interactive thermal comfort adjustment method, which belongs to the technical field of HVAC adjustment systems. Background technique [0002] Smart buildings can effectively improve the quality of life of users and improve the environment. A basic feature of smart buildings is that they can monitor the smart devices inside them for various purposes, one of which is to provide decision support tools to assist users in making effective energy-saving decisions when using electrical energy. The user's thermal comfort depends on many factors, including subjective aspects (such as wearing clothes, expected attitudes towards the environment, etc.) and objective aspects (such as indoor and outdoor temperature, humidity), and the general thermal comfort model is difficult to meet everyone's requirements. Incorporating the dynamic process of user willingness into the thermal comfort model...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art, provide an energy-saving building micro-area personnel interactive thermal comfort adjustment method...

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