Fast prediction for multi-parameters (concentration, temperature and humidity) of indoor environment towards the online control of HVAC system

Abstract

Heating, ventilation and air conditioning (HVAC) systems are the most energy-consuming building implements for the improvement of indoor environmental quality (IEQ). We have developed the optimal control strategies for HVAC system to respectively achieve the optimal selections of ventilation rate and supplied air temperature with consideration of energy conservation, through the fast prediction methods by using low-dimensional linear ventilation model (LLVM) based artificial neural network (ANN) and low-dimensional linear temperature model (LLTM) based contribution ratio of indoor climate (CRI(T)). To be continued for integrated control of multi-parameters, we further developed the fast prediction model for indoor humidity by using low-dimensional linear humidity model (LLHM) and contribution ratio of indoor humidity (CRI(H)), and thermal sensation index (TS) for assessment. CFD was used to construct the prediction database for CO2, temperature and humidity. Low-dimensional linear models (LLM), including LLVM, LLTM and LLHM, were adopted to expand database for the sake of data storage reduction. Then, coupling with ANN, CRI(T) and CRI(H), the distributions of indoor CO2 concentration, temperature, and humidity were rapidly predicted on the basis of LLVM-based ANN, LLTM-based CRI(T) and LLHM-based CRI(H), respectively. Finally, according to the self-defined indices (i.e., EV, ET, EH), the optimal balancing between IEQ (indicated by CO2 concentration, PMV and TS) and energy consumption (indicated by ventilation rate, supplied air temperature and humidity) were synthetically evaluated. The total HVAC energy consumption could be reduced by 35% on the strength of current control strategies. This work can further contribute to development of the intelligent online control for HVAC systems.

Impact of ionizers on prevention of airborne infection in classroom

“…The impact of ionizer on removing the aerosol particles settling on the surfaces (walls and floors) should be also investigated in future work, because of the reflection effects of particles. The evaporation of exhaled droplets by infected occupants and the influence of various environmental factors, such as temperature and humidity (Zhu et al 2021), should be further considered in the simulations. The releasing time of ionizers, life span of negative ions and dynamic property of natural ventilation affect the suspended negative ion concentration in the air.…”

Proposal and application of indexes for dynamic evaluation of indoor humidity and thermal environment

“…Due to the effectiveness of CRI (H) in detailed humidity environment design 27 , Huang et al used it to simulate the transient humidity eld and combined it with the genetic algorithm to establish an e cient optimization design system 28 . In addition, Zhu et al 29…”

“…From to refers to the ratio of the rise (or fall) in humidity at a point from an individual moisture source to the rise (or fall) in humidity under perfect mixing conditions for the same moisture source 29 . It indicates the spatial distribution of humidity in uenced by the moist components of the source.…”

Indices for dynamic evaluation of indoor humidity and thermal environment

“…Due to the effectiveness of in detailed humidity environment design 29 , Huang et al used it to simulate the humidity field and combined it with the genetic algorithm to establish an efficient optimization design system 31 . In addition, Zhu et al 32 realized the rapid prediction of indoor humidity by combining with a low-dimensional linear humidity model and optimized the balance between the personal perception of humidity and air-conditioning humidity loads. Nevertheless, and , the spatial description indexes of the sources affecting the indoor environment at a certain moment, have limitations in reflecting the dynamic characteristics of transient evaporation and diffusion of wet-components produced by the source influencing the indoor temperature and humidity.…”