Management smart building with photovoltaic using (ANN) to increase energy efficiency.

the issue of rising electricity demand in the building sector is one of the major challenges. Therefore, the Building Management System (BMS) inside the building. Since the PV, national grid, and diesel generators supplies building electrical power, so the Energy Management System (EMS) technologies are necessary to study the priority of PV to supply building power to save energy. This paper proposes a Smart Building Management System (SBMS) used with Heating, Ventilation, and Air Conditioning (HVAC) in addition lighting systems. HVAC is controlled with occupancy sensors, temperature control, and load control. Lighting systems are controlled through occupancy sensors and daylight sensors to make them operate to minimize electricity consumption. Using Artificial Neural Network (ANN) control of the EMS in this work, SBMS and EMS are created and simulated using two case studies to supply public buildings. The first situation is SBMS without EMS and the second situation is SBMS with EMS. Finally, the results showed the impact of SBMS on the reduction of energy consumption for HVAC systems and lighting (20% on summer day and 11% on winter day), as the energy consumption was reduced for both HVAC and lighting by about (54% on a summer day and 44% on a winter day) because we added the scenario of case two to the one scenario case in a public building. [ABSTRACT FROM AUTHOR]