Climate model based test workbench for daylight-artificial light integration

Abstract

Energy efficiency strategies based on daylight-artificial light integration have grown exponentially in recent years. Taking into account the dynamics to be considered for control and the dependence on natural and occupancy factors, it is better to use a test workbench prior to setting up the final control scheme. This work describes a climate model based test workbench for the real time testing of the control of luminaires and window blinds in a daylight-artificial light integrated scheme. The established climate model based control scheme suitable for the optimum integration of visual comfort, thermal comfort, and energy consumption can be tested for any ecological conditions. The input irradiance from a BF5 sensor, the internal temperature from a Micro DAQ logger, the occupancy and photo sensors associated with the luminaire all provide input data for the test workbench. A fuzzy logic based motorized window blind controller and look-up table based dimming of LED luminaires are used to set the required illuminance with reduced load on the heating, ventilation, and air conditioning system. The anticipated synergetic effects of the test workbench have been validated using real time climate data. The test work bench is established on a Labview platform and developed as a standalone system using myRIO.

A data-driven approach for the control of a daylight–artificial light integrated scheme

“…These are also used to examine the light level for the developed predictive models and the baseline fuzzy-based model. 21 Finally, we found that both the GPR and the BSVR models performed well for all the cases, but when the models were cross-validated for the east, west and north side windows, the BSVR performed well, and for the south side window, both the BSVR and the GPR models performed well. These models work from the industrial point of view to implement controllers in a real-time environment by reducing the complexity.…”

“…Some studies have shown that automated control of shading helps to improve the energy efficiency and gives comfort to the occupants. 21,22 Also, other studies have suggested that a modelbased predictive control of shading devices using real-time data and robust control schemes has the potential to improve the indoor environment and reduce lighting energy use. [23][24][25][26][27] Nowadays, adaptive predictive control strategies for shading and lighting control based on the occupant's preference are gaining popularity in research.…”

“…[28][29][30][31] Some have proposed the real-time implementation of a blind control system based on climatic conditions so that the position of the shading device will help to improve the visual comfort by operating the artificial lights accoding to the daylight availability in the room. 21 This data-driven approach for a daylight-artificial light integration scheme is getting more preference these days. The data-driven approach for daylight estimation on the work plane for the open plan office condition helps to control the luminaires to maintain the illuminance on the work plane.…”

“…The window blind position and real-time daylight estimation models help to develop a control strategy to adjust the operation of the luminaires to off, on or somewhere in between. This study considered the preliminary test workbench set up 21 for data acquisition and to develop a predictive control strategy for blind operation and daylight estimation models on the work plane. The data obtained from the test workbench set up are continuous so, here, the regression-based predictive models are developed for the blind position system.…”

Cluster based Routing Protocols for IOT Application

“…The proposed system shown in Fig.2 consists of 100 sensor nodes installed in a floor of a building. The network is divided into four occupancy zones, each with its own Passive Infrared [PIR] Occupancy Sensors, two LED Luminaires and motorized window blinds [17,18]. One of the luminaires in each zone is placed close to a window, thus is exposed to more natural light than the other.…”