Daylight performance metrics provide a promising approach for the design and optimization of lighting strategies in buildings and their management. Smart controls for electric lighting can reduce power consumption and promote visual comfort using different control strategies, based on affordable technologies and low building impact. The aim of this research is to assess the energy efficiency of these smart controls by means of dynamic daylight performance metrics, to determine suitable solutions based on the geometry of the architecture and the weather conditions. The analysis considers different room dimensions, with variable window size and two mean surface reflectance values. DaySim 3.1 lighting software provides the simulations for the study, determining the necessary quantification of dynamic metrics to evaluate the usefulness of the proposed smart controls and their impact on energy efficiency. The validation of dynamic metrics is carried out by monitoring a mesh of illuminance-meters in test cells throughout one year. The results showed that, for most rooms more than 3.00 m deep, smart controls achieve worthwhile energy savings and a low payback period, regardless of weather conditions and for worst-case situations. It is also concluded that dimming systems provide a higher net present value and allow the use of smaller window size than other control solutions.Smart control strategies require the assessment of different variables: the window size is essential to determine electricity consumption [9], as are the reflectance of the room surfaces and the location of the building [10]. The illuminance controls also have a significant impact on the thermal comfort of occupants, mainly due to solar heat gain, so that algorithms should take all possible variables into account [11]. One of the most common smart controls is that of dimming systems [12,13], which adjust the electricity power of the luminaires. The dimmer can be controlled by illuminance-meters which significantly reduce the power consumption in electric lighting [14,15].According to the latest studies [16][17][18], the strategies for lighting control can reduce power consumption by up to 50% when using dimming systems and close to 30% using occupant detectors. However, these technologies are not widespread, given the difficulties in installation, the limitations of the prediction algorithms, and the individual management preferences of occupants [19][20][21]. It is therefore important to emphasize the benefits from all these strategies, quantifying their energy efficiency and economic profitability, and avoiding an overestimation of the savings or overly optimistic analysis. Hence, the use of dynamic daylight metrics will provide a better whole-year fit. Unlike daylight static concepts, dynamic metrics allow the accurate quantification of energy savings in electric lighting, including variables not considered by static metrics, such as weather conditions, occupancy hours or illuminance thresholds required by the task being carried out [22-24].
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