There is a large quantity of lamps and luminaires that present their on characteristics, such as the amount oflumens and life time. Thus, there are several possible combinations of lamps and luminaires that can be employed as a solution to adapt the lighting of a given indoor environment. What will differentia teach solution will be the cost of investment and the time of financial return. This work presents the development of a tool that provides the user with the possibility to carry out lighting studies for any internal business environment ,considering multiple scenarios and following the regulations set by the NBRISO/CIE 8995-1:2013. Studies are carried out in an optimized method by running a genetic algorithm, which has as objective function the minimization of time of financial return on investment of lamps and luminaires,which are necessary for the achievement of illuminance area. For the development of the tool spread sheets were associated with the Python programming language and the PyCharm as the development software. The lumens method was used for lighting sizing, the simple linear regression technique was used to estimate the rate of electrical power for a period of 10 years and NetPresent Value a long side the discounted pay back for analysis of financial return of the solutions generated by the tool. The developed tool was applied in four different scenarios in the Amazon Energy Efficiency Center(CEAMAZON) building. Valid solutions for all scenarios were found, that is, a pay back with in 10 years, taking into consideration the initial investment, annual consumption and maintenance,if any. The best solutions were simulated by the software DIALux as an aid in the projection of the distribution of luminaires in environments. The aspects described in this work show the functionality and applicability of this tool, in order to support the user in the planning of lighting projects, having achieved the established goal, showing functionality and effective ness.
|
