The growth in sustainable generation technology such as fuel cell, wind energy conversion system, photovoltaic system, increase in fuel cost, energy necessity and the reduction in the fossil fuel reserve, for better power quality and reliability, is obliging the power sector to use the renewable based energy sources. In India, wind energy is gradually becoming an important and significant energy resource. Keeping in opinion the aforementioned wind energy prediction is becoming an essential study for harnessing the wind energy prospective. This paper proposes an effective technique based on intelligent approach for predicting wind power in different areas. This technique is based on using an intelligent model concerning the predicted gap to its similar one and two year old data. There are many intelligent and conventional models existed in literature for the wind power prediction like support vector machines (SVM), back propagation (BP) prediction etc. In this paper an effective fuzzy logic and model predictive control based models have been developed and offered for the wind power prediction for microgrid application by using air density and wind speed as the input parameters for fuzzy system. The outcomes are compared with the computed data and existing models and it can be observed that the different errors are found within the permissible limits. The outcomes obtained from fuzzy based technique are very close to calculated values if compared with model predictive based technique. Hence, the proposed models can be employed for the prediction of wind speed and wind power generation in the selected stations. The existing models results are compared with Kolkata city outcomes. The Error RMSE with Support vector machine, Back propagation, Model of forecast error correction +SVM and Model of forecast errors correction +BP, Neural Network method, model predictive based system, and proposed fuzzy logic based system are 30.48%, 32.83%, 26.81%, 28.58%, 1.1431%, 1.38% and 1.12% respectively. Therefore, the proposed techniques provide the best results and even these are observed within the suitable limits. Additionally, the achieved outcomes can be used for Microgrid/SmartGrid applications.

The partial shading (PS) is a phenomenon that affects PV panels frequently. Many Photo Voltaic (PV) array reconfiguration techniques have advanced recently, making significant progress in providing solutions to partial shading. But the majority of the currently used techniques still fall short of achieving efficient shade dispersion and power enhancement. This paper presents the study of Improved Sudoku technique and also provides a comparative analysis with other techniques. This Improved Sudoku Technique is a puzzle-based technique where the sum of numbers in each row and column is constant, and each row and column contains numbers from 1 to 9. The main objective of this paper is to improve the power and dispersion of the standard two shade patterns. Additionally, a comparison with other renowned techniques like Honey-comb (HC) and Total Cross Tied (TCT) is conducted to demonstrate its outstanding performance. In terms of power enhancement and fill factor (FF), the developed method offers extremely satisfactory performance in every area. To further demonstrate the adaptability of the suggested methodology, a more thorough analysis based on additional performance metrics such as maximum power GMPP(Pmax), fill factor (FF) along with mismatch losses (ML) and execution ratio (ER) is carried out.