Application of integrated centralized control systems in buildings has been shown to be a very promising option to reduce energy consumption. The focus of this paper is on automated day-lighting systems which can modulate window blinds and electrical interior lights for maintaining the proper illumination levels and saving significant electrical energy in buildings. The algorithm proposed involves developing a preliminary baseline strategy for near-optimal blind slat angle settings for venetian blinds. We describe the predictive algorithm and validate the algorithm through experimental studies in both a virtual test cell as well as in an actual test room which have three separate sets of venetian blinds. The baseline strategy involves using a detailed lighting simulation program to predict illumination levels during selected days of the year and specific times of the day. The simulations are done by modifying the angels of blinds individually by pre-selected increments. It is then shown that this baseline data when properly extrapolated is adequate to predict near-optimal blind angles for most of the hours during the rest of the year. The study presented in this paper lays the foundation towards the development of an innovative integrated lighting control algorithm for high performance buildings using distributed sensors which will be described in a subsequent paper.

Original languageEnglish (US)
Title of host publicationEnergy
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791850596
StatePublished - 2016
EventASME 2016 International Mechanical Engineering Congress and Exposition, IMECE 2016 - Phoenix, United States
Duration: Nov 11 2016Nov 17 2016


OtherASME 2016 International Mechanical Engineering Congress and Exposition, IMECE 2016
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Mechanical Engineering


Dive into the research topics of 'Development and validation of a predictive algorithm for near-optimal control of venetian blinds'. Together they form a unique fingerprint.

Cite this