Production of clean, green solar PV (SPV) power in developing countries now becomes a trend because of their economic and technical benefits. Therefore, generating maximum power out of the SPV is a key searchable area. The SPV must produce power at its terminal at their maximum possible power. To reach to the maximum possible power, maximum power point tracker(MPPT) is used in conjunction with SPV. Extracting maximum power from SPV under varying partial shading condition is one of the important factor in performance improvement of SPV. The characteristics of classical MPPT controller is not acceptable under variable shading condition. A clear distinction between global maxima power point from global minima using MPPT technique must be needed for extracting maximum power. This paper proposes a P&O MPPT based particle swarm optimization with improved search space, optimised through Fuzzy Fokker Planck solution. The pre-defined search space has been introduced to provide fine tune to membership function used in Fuzzy logic controller. The partial shading performance has been examined under four different condition such as active partial shading, colour spectrum, dust level and green house gas (GHG) concentration. Both hardware and simulation studies has been carried out for the proposed techniques. The MATLAB simulation result and that of proposed MPPT, offer more and better performance in terms of algorithm convergence by enhancing the efficiency of system under varying shading condition.

Analysing the Output Power of a Solar Photo-voltaic System at the design stage and at the same time predicting the performance of solar PV System under different weather condition is a primary work i.e. to be carried out before any installation. Due to large penetration of solar Photovoltaic system into the traditional grid and increase in the construction of smart grid, now it is required to inject a very clean and economic power into the grid so that grid disturbance can be avoided. The level of solar Power that can be generated by a solar photovoltaic system depends upon the environment in which it is operated and two other important factor like the amount of solar insolation and temperature. As these two factors are intermittent in nature hence forecasting the output of solar photovoltaic system is the most difficult work. In this paper a comparative analysis of different solar photovoltaic forecasting method were presented. A MATLAB Simulink model based on Real time data which were collected from Odisha (20.9517^∘N, 85.0985^∘E), India. were used in the model for forecasting performance of solar photovoltaic system.

Of the 1.24 billion people in the country, more than 450 million people do not have access to electricity as well as over 95,000 villages still remain dark after sunset. Even the electrified villages suffer power cuts of 15 hours or more on a daily basis. These problems compel us to resort to other energy sources that are inexhaustible. The paper proposes analysis and comparative study of Hybrid Renewable Electric System, especially Photovoltaic-Fuel cell hybrid system, Wind-Fuel cell hybrid system and Photovoltaic-Wind-Fuel Cell hybrid system with Hybrid Optimization Model for Electric Renewable (HOMER) software for distributed generation system. The model simulates all the above small power technologies in hybrid configurations to identify the optimum hybrid system with minimal cost for remote residential loads in the Sunderbans, India.

The objective of this research was to study the effect of different environmental factors on performance of solar photovoltaic panel. The photovoltaic solar power represents one of the most promising energy in the world. It is also the cleanest form of energy. But the implementation of a PV system has shown that their reliability and efficiency depend upon many factors. The output of solar PV system is mainly affected by different environmental factors like dust, color, irradiance, shading, etc. Because in all the cases, the output power and efficiency are more rather than affected condition. Here the number of experiment has been conducted to verify the change in i-v and p-v characteristics of the system. The experimental data were used to calculate the efficiency and power output of the system. The result shows that the output power and efficiency are affected by environmental factors.