sensors

Most New Zealand schools are designed to be naturally ventilated, using openable windows (Ministry of Education Design Quality Standard Guidelines). Furthermore, they must meet the New Zealand Building Code Clause G4 - Ventilation. Clause G4 requires the “net openable area of windows in a classroom to be no less than 5% of the combined habitable floor area to achieve sufficient ventilation”. Although they are designed to code, there is no end-user operational or systems requirement for them to be opened.

Sensor errors have an important impact on the operation, control, and detection of building energy systems. Correct and reliable sensors can effectively reduce the energy consumption of building energy systems. Virtual in-situ calibration (VIC) based on Bayesian inference and Markov Chain Monte Carlo method that no need to increase extra or install new sensors can effectively reduce systematic error and random error of the sensor and increase the reliability.

Over the past few years there have been advances in sensing of some pollutants, primarily particles, that might lead to ventilation controls based on direct sensing of pollutants – particularly those relating to health. In this study we evaluated low-cost (about $200 US) IAQ monitors that measured PM2.5 - the most important health-related pollutant in indoor air. Controlled laboratory tests were carried out with known sources of particles (cooking, cleaning, candles, cigarettes) and by comparing the IAQ monitors response to research-grade and reference measurement methods.

The difficulty in measuring IAQ indicators like VOCs and particles, lies in the multiplicity of the composition of these pollutants. Analysis of the responses of some low cost IAQ sensors when subjected to real sources of pollution shows that they do not react homogeneously, due to their sensitivity and post-treatments. These sensors can be used by consumers to understand the effect of their actions on the evolution of IAQ indicators, not to rely directly on the values displayed.

In 2017, the Air Infiltration and Ventilation Centre (AIVC) identified smart ventilation for buildings as a new and important topic to be addressed. One of the tasks was to agree on a definition of smart ventilation, which was published in March 2018. The purpose of this presentation is to explain and illustrate the smart ventilation definition by AIVC.

Over the last decade, TVOC sensors have been touted as an interesting alternative to CO2 and RH sensors in DCV systems. Nevertheless, there is little evidence on the nature and the profile of TVOC concentrations in modern dwellings.

Although theoretical studies show that energy use for ventilation purposes can be reduced by more than 50% with DCV compared to CAV, evaluation of real energy use demonstrates that this potential is seldom met. DCV-based ventilation systems must become more reliable to close the gap between theoretical and real energy-performance.

In France, in non residential buildings, these systems are generally controlled by either a CO2 sensor or optical movement detection (infrared).The part of the study we present here was to determine :- laboratory tests methods to assess the performances of CO2 sensors for ventilation application.- the working performances of these sensors, and particularly the long term stability in a meeting room.- a methodology to assess the performances of CO2 DCV system in French technical agreementThe main results of this study are :- it is easy to characterize (to calibrate) the sensors- the long term

This paper presents the development of a simulation tool based on the Matlab computational environment for building temperature performance analysis with automatic control. The simulation tool contains mathematical models for buildings, HVAC (Heating, Ventilation and Air Conditioning) systems, sensors, weather data and control algorithms. The building mathematical model is described in terms of statespace variables, with a lumped approach for the room air governing equations energy and mass balances. In this context, the simulation tool structure and components are explained.

In the large space, for example in large-dome, the space is often divided into some zones without partition walls for air conditioning. In this case the following are problematic, The first problem is that it is difficult to control the temperature of the target zone considering the influence by the supply air temperature in the adjacent zone for air conditioning. The second problem is that it is difficult to set the temperature sensor for air conditioning control at the location in which the temperature means the average temperature in the target zone.