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Due to new European standards and requirements for energy performance in non-residential buildings, it is important to explore and quantify the benefits of intelligent (automated) energy-efficient operating systems relative to conventional (manual) systems. This paper explores the energy performance of an automated lighting control system under realistic conditions in two groups of lecture rooms that have the same shape, dimensions and exposure. The results demonstrate that the use of automated systems for electric lighting control can improve the energy performance of the system between 40% and 65% depending on the complexity of the system and the parameters under control.

Buildings in Europe account for 40% of total primary energy consumption and 36% of CO 2 emissions. Nearly one-half of the building stock was built before modern energy efficiency standards and need urgent renovation. Urban retrofitting has emerged as a crucial factor for bringing about a radical change, the new construction rate being lower than 1%. Nevertheless, an accepted and consolidated methodology for refurbishing the existing housing stock is still lacking. The study presents an operating methodology for the optimization of the retrofitting process, based on energy efficiency and cost-effectiveness, as well as users' comfort, in the building asset of ITEA SpA, the social housing institute for the Province of Trento (Italy), which manages more than 600 buildings. The research consists of the following stages: (1) definition of building classes, similar in age, dimension, typology, construction system and location; (2) analysis of plant systems and recognition of cases significant for classifying buildings in term of energy class; (3) identification of possible improvements and related cost-benefits; and (4) extension of the results to the whole building class. A tool is here proposed, intended for use by ITEA in order to set medium-and long-term plans. The tool does not consider only the effective sustainability of the controlling body intervention but also the final users' full satisfaction.

Electric lighting is one of the major energy loads in non-residential buildings. It is strategic to examine the real behaviour of available lighting control systems for practical applications so as to allow the development of strategies that can improve the reliability of measured data (in terms of illuminance at the desktop) and the consequent response of the control system. This paper presents a case study of an office where lighting data measured at the desktop and read by the automation system have been analysed. It also investigates the consequent response of the control system. In particular, we extrapolate data on the system's improvement margins and suggest suitable correction functions to be applied to the illumination data measured by ceiling-mounted sensors.

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