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In this paper, the application of an Adaptive Network-based Fuzzy Inference System (ANFIS) to control a hybrid solar and wind grid-tie inverter in order to reduce power oscillations and enhance power quality is presented. To extract the maximum power from the PV system, a Perturb and Observe (P&O) algorithm is presented that tracks the Maximum Power Point (MPP). Time-domain simulation results of the studied system are performed in MATLAB/SIMULINK under different operating conditions such as changing irradiation and short-circuit faults in the power grid. From the simulation results, it can be concluded that the designed ANFIS controller and the proposed P&O algorithm perform better than the traditional PI controller and improve transient responses under severe operating conditions.

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For monitoring the energy supply from the hybrid small-scale wind turbine generator (WTG) and rooftop solar Photovoltage (PV) systems, this paper presents the design of a management program of the studied system based on the Internet of Things (IoT) technology. The proposed studied system consists of digital power meters that communicate wirelessly to the Programmable Logic Controller (PLC) through the ZigBee communication standard. By using a free cloud platform will greatly facilitate the Supervisory Control and Data Acquisition (SCADA) interface design work for a Human Machine Interface (HMI) or mobile phone. This system configuration may be easy to be fitted for collecting electrical information such as voltage, current, power, frequency of the system to be monitored. This is one of the cheap solutions deployed in small-scale hybrid power systems (HPS) or factories because wireless communication is very convenient in construction and installation.

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