Analysis of Photoelectric Dimming Control Performance for Lighting Energy Savigns in a Small Office

Abstract

This study investigates control performance of daylight dimming control system under various sky conditions in order to examine the influence of daylight conditions on dimming performance. Field measurements were conducted in a full-scale mock-up model to collect actual data and computer simulations were performed to determine light output of fixtures. Results indicate that the variation patterns of desktop illuminance were similar to those of illuminance arriving at window. The direct component of daylight affected photosensor illuminance generating strong reflected components from wall surfaces. Relationship between desktop and photosensor illuminance was stronger than that of between window and photosensor. This implies that desktop illuminance was effective to predict the variation of photosensor illuminance. Compared to overcast sky conditions, dimming control was effective under clear sky and achieved good energy savings. Under overcast sky conditions, excessive dimming occurred due to the influence of electric lighting. It appears that control algorithm or photosensor conditions should be reset in order to block light input to photosensor and generate less dimming from lighting fixtures.

Analysis of Lighting Control System for Applications of Lightshelf Conditions to Office Space

“…라이트스케이 프 알고리즘에 적용된 장점 및 제한점은 기존의 연구 에서 이론적으로 고찰되었다 (Ashdown, 1994;Refro & Guglielmetti, 1999). 또한, 라이트스케이프는 기존의 연구에 적용되어 조명환경 분석에 효율적으로 활용되 었다 (Kim, 2005;Baik & Kim, 2014) 컴퓨터 시뮬레이션에 적용된 공간은 사무실이며, 폭 과 깊이의 비율은 1:2 로 가정되었다. 공간에 대한 세 부사항은 Figure 양한 주광조건에서 시뮬레이션이 실시되었다.…”

Advancing Smart Lighting: A Developmental Approach to Energy Efficiency through Brightness Adjustment Strategies

“…Smart lighting enables the use of big data to enhance the efficiency of energy consumption for light usage. For example, weather data have been utilized for further analysis to understand household behavioral energy consumption [6], and weather condition data, particularly daylight data, have been used to enhance smart lighting management systems for energy efficiency [7,8]. The predominant method for handling large amounts of data involves the use of Internet of Things (IoT) sensing devices, such as light, motion, relay, LCD display, lux meter, occupancy, and photocell sensors [9,10].…”