The presentation of the SCADA system and its use as a management software of hybrid sources is presented. Here an energy management technique for Hybrid Renewable Energy System (HRES) connected with AC load using Adaptive Neuro Fuzzy Interference System (ANFIS) is proposed. In this work, photovoltaic (PV) system, Wind Generating System (WGS), Fuel Cell (FC), Ultra Capacitor (UC) and the battery are considered as the energy sources. The ANFIS technique is trained with the inputs such as the previous instant energy of the available sources and the required load demand of the current time and the corresponding target reference power of the sources and storage devices. According to the load variation, the proposed method makes the appropriate control signals at the testing time to manage the energy of the HRES. Energy management in Smart Home environment is one of the main topics adopted in Smart Grid research field. In this paper, we present a Multi-Agent System (MAS) for a Smart Home intelligent control. Such a solution was integrated in a smart meter in order to alter the shape of the residential load curve. The MAS is strong appropriate to solve complex distributed problems as home automation system. Our contribution consists in performing an algorithm for scheduling appliances tasks, and designing a model for a direct load control which may accommodate customer preferences. A STATCOM based voltage regulation and harmonic mitigation is introduced. The implementation of the system elements and control method has been done in MATLAB/Simulink and the performance of the proposed method is analysed by using different environmental and load test conditions. The results of the test cases confirms that the proposed control technique is effective in prediction of energy required for the next instant and manages the energy flow among HRES power sources and energy storage devices
