Energy management strategy with smart building control system to reduction electrical load using ANN

Buildings have long been large energy consumers, and inadequate control of heating, ventilation, air conditioning kinds variable refrigeration flow (HVAC-VRF) lighting systems. To reduce consumption by using a smart building system (SBCS) in was created occupant control, daylight sensors, weather condition variations, load consumed, changes solar power. The model tested MATLAB/Simulink, it then utilized to investigate the impact an integrated on usage based two scenarios. first scenario simulation behavior, meteorological variables, temperature, control. This resulted savings for HVAC (23% summer days 16% winter days), (22% 15% days). In second scenario, integrate PV power with artificial neural network (ANN) algorithm manage PV, grid, diesel generator. As result, were 56% day 65% combined lights.