iosr-JEEE   Volume-15 ~ Issue-3 ~ may – June 2020

Abstract: The electrical power generation based on the sun's rays through a series of solar cells linked together is considered as clean energy that reduces gas emissions are harmful compared to those produced by fossil fuels. Thus, lead to decrease the effects on the components of the environment. Also, the unknown impacts on the system behaviorwill inevitably affect the final response of the system, so it requires a more robust and effective control methodology. This paper presents the current control based the model predictive control (MPC) to generate optimal pulse of converter gates to handle the photovoltaic system (PV) unit based on maximum power point tracking....

Key Word: Model predictive control; Fuzzy logic control; Photovoltaic integration system; PI controller

[1]. Tuller, Harry L. "Solar to fuels conversion technologies: a perspective." Materials for renewable and sustainable energy6, no. 1 (2017): 3. J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68-73.
[2]. L. Chen, A. Amirahmadi, Q. Zhang, N. Kutkut, and I. Batarseh, "Design and implementation of three-phase two-stage grid-connected module integrated converter," Power Electronics, IEEE Transactions on, vol. 29, no. 8, pp. 3881-3892, Aug 2014..
[3]. Khan, O., and W. Xiao. "Review and qualitative analysis of submodule-level distributed power electronic solutions in PV power systems." Renewable and Sustainable Energy Reviews76 (2017): 516-528.
[4]. Y. Zhou, L. Liu, and H. Li, "A high-performance photovoltaic moduleintegrated converter (mic) based on cascaded quasi-z-source inverters (qzsi) using eganfets," Power Electronics, IEEE Transactions on, vol. 28, no. 6, pp. 2727-2738, June 2013.
[5]. Palma, L. "Push-pull based single stage PV microinverter for grid-tied modules." In 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), pp. 884-888. IEEE, 2016..

Abstract: Increase in use of energy, increase of load on utility grid, rise in crude oil rates, warming of globe and improvement in Renewable Energy technology with drop in prices inspire government for the deployment of productive, low cost use of energy sources for the Microgrid based Renewable Energy System. Load-shedding nowadays is one of the biggest concerns, especially in rural areas as rural areas are more prominent to load-shedding. This research paper mainly focuses the application of Microgrid based Renewable Energy System and its feasibility for a small village of Pakistan. The complete Microgrid based Renewable Energy System has been designed and analyzed using PV*Sol software tool. Simulation result indicates that the total cost of Microgrid System installed has been recovered as well as even generated revenue by selling surplus power to third party consumers.

Keywords: Solar Photovoltaic, Energy Consumption, Microgrid System Designing, Grid Connected, PV*SOL Premium 2019.

[1]. L. C. de Lima, L. de Araújo Ferreira, and F. H. B. de Lima Morais, "Performance analysis of a grid connected photovoltaic system in northeastern Brazil," Energy Sustain. Dev., vol. 37, pp. 79–85,2017.
[2]. M. Usman, M. T. Khan, A. S. Rana, and S. Ali, "Techno-economic analysis of hybrid solar- diesel-grid connected power generation system," J. Electr. Syst. Inf. Technol.,2017.
[3]. R. Bakhshi and J. Sadeh, "Economic evaluation of grid--connected photovoltaic systems viability under a new dynamic feed--in tariff scheme: A case study in Iran," Renew. Energy, vol. 119, pp. 354–364,2018.
[4]. E. Tarigan, F. D. Kartikasari, et.al., "Techno-economic simulation of a grid-connected PV system design as specifically applied to residential in Surabaya, Indonesia," Energy Procedia, vol. 65, pp. 90–99,2015.
[5]. A. A. Moghaddam, T. Dragicevic, Juan C. Vasquez and J. M. Guerrero "Optimal Utilization of Microgrids Supplemented with Battery Energy Storage Systems in Grid Support Applications" in Proc. IEEE IDCM, 2015..

Abstract: Face recognition has recently received significant attention especially during the past few years at one of the most successful applications of image analysis and understanding. Facial recognition technology (FRT) has emerged as an attractive solution to address many contemporary needs for identity and verification of identity claims. The identification of humans by the unique characteristics of their faces is called face recognition. FRT technology is the least intrusive and fastest biometric technology. With the advancement in technology extracting information and within creasing security needs has become much simpler. The system proposed in this paper uses the power of the Convolutional Neural Network (CNN) to encode the face and produce a vector matrix. Then we use tripled loss function to calculate the distance between input and trained image to predict the face.

Keywords: Tensorflow, Face recognition, Keras, ImageNet, Convolutional Neural Network (CNN.)

[1]. Sun, Yi, Xiaogang Wang, and Xiaoou Tang. "Hybrid Deep Learning for Face Verification." IEEE Transactions on Pattern Analysis and Machine Intelligence 38.10 (2016): 1997-2009
[2]. Hu, Guosheng, et al."When face recognition meets with deep learning: an evaluation of convolutional neural networks for face recognition." Proceedings of the IEEE International Conference on Computer Vision Workshops. 2015.
[3]. Zhang, Tong, et al. "A deep neural network driven feature learning method for multi view facial expression recognition." IEEE Trans.Multimed99(2016): 1
[4]. Florian Schroff, Dmitry Kalenichenko, James Philbin (2015). "FaceNet: A Unified Embedding for Face Recognition and Clustering"
[5]. Yaniv Taigman, Ming Yang, Marc'AurelioRanzato, Lior Wolf (2014). "DeepFace: Closing the gap to human-level performance in face verification"