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Demand response (DR) programs seek to adjust the normal consumption patterns of electric power consumers in response to incentive payments that are offered by utility companies in order to induce lower consumption at peak hours and when the power system reliability is at risk. Given the fact that lighting systems consume about 20-35% of the total energy used in buildings, addressing this shortcoming is an important research problem. Therefore, we propose to take a systematic optimization-based approach to assess demand response capacity of automatic lighting control systems in commercial and residential buildings. Our model takes into account a variety of important systems parameters, such as the building layout, the location, power consumption, and illumination level of luminaires, information collected from daylight and occupancy sensors, illumination requirements of each spot on the layout based on the type of consumer usage, user comfort that is modeled in form of user-specific utility functions, and finally the on/off as well as dimming control capabilities of the installed luminaires. We show that, under some practical conditions, the formulated optimization problems are convex; therefore, computationally tractable. Using a variety of simulations we will investigate the optimal demand response capacities for various building layouts and different distributions of luminaires. We will also investigate the financial advantages of participating in demand response programs using automatic lighting control for both commercial and residential buildings.

Publication Date


Project Designation

Independent Research

Primary Advisor

Charles E. Ebeling

Primary Advisor's Department

Engineering Management and Systems


Stander Symposium poster

Assessment of Alternatives Effects and Choosing the Optimized Demand Response Capacity of Automatic Lighting System