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Lack of resources established in the present world is initiating everyone towards energy efficient technologies. Among all these resources, power is one which needs to be monitored and controlled as per the need since electricity consumption is increasing day-by day. In this project, we have described an effective implementation of an intelligent remote monitoring system for solar Photovoltaic (PV), Wind Energy Conversion System (WECS) and battery which are used in a greenhouse environment. The proposed system design can be installed in solar PV, WECS and battery in order to solve management problems, maintenance and shortens the mean time to repair. We have designed a smart remote monitoring system based on internet of thing for monitoring Solar PV, WECS and Battery. This system had incorporated remote monitoring for solar PV, WECS and battery through internet using host, network GPRS (Global Positioning Radio Service), embedded system gateway and Arduino. The result of our demonstration shows that the system can monitor store and manipulate data from solar PV, WECS and battery. Thus, the remote monitoring functions are realized in real-time. [ABSTRACT FROM AUTHOR]

The power control of small-scale wind energy conversion system is usually limited by the sluggish mechanical dynamic. Aiming at highlighting this phenomenon, this article introduces a small-scale wind energy conversion system using the permanent magnet synchronous machine as generator to validate different combinations of control strategy resulting from four different maximum power point tracking (MPPT) methods with hysteresis control: one indirect MPPT method based on a look-up table and three direct methods based on perturb and observe relationship. Following two ideal wind speed profiles, a real rapid wind speed profile and using a test bench emulating a small-scale wind turbine, the MPPT methods are compared and analysed based on experimental results. The indirect method operates with the best MPPT performances for all three wind speed profiles while requiring accurate knowledge of the controlled system. The direct methods operate with low MPPT performance under rapid variation of wind speed and the superiority of variable step size is not significant since the dynamic process of the perturbation strongly weakens the effect of MPPT algorithm. In proposed system Adaptive Network-based Fuzzy Interference System is used to control the MPPT. [ABSTRACT FROM AUTHOR]