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Efficient Operation of Solar Power Based Power Management for Remote Power Application

T. A. Sivasangari, A. Sudhanandhi, A. P. Sambavi, S. Vivekanandan

Abstract


The growing need of electrical energy can be fulfilled by harnessing energy from Renewable Energy Sources (RES) along with conventional sources of energy. By understanding need of electricity and available energy sources and storage, energy management can be done. The task of Energy Management System (EMS) is to manage the energy between source and load. In recent decades photovoltaic power generation has become very important due to its many benefits such as needs a few maintenance and far many researches are conducted and many papers were published and suggested different methods for extracting maximum power. This paper presents in detail the power management of the extracted power of PV system. The simulation has been accomplished in Proteus software containing photo-voltaic array, controller and energy management block. From the perspective of consumers, we can investigate how to minimize the expected costs with real time electricity pricing, which is the focus of this paper.


Keywords


Pulse Width Modulation, Photo Voltaic, Renewable Energy Sources, Power Management.

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References


Australian PV Institute. Australian PV market since April 2001.[Online]. Available: http://pv-map.apvi.org.au/analyses

M. Bozchalui, S. Hashmi, H. Hassen, C. Canizares, and K. Bhattacharya, “Optimal operation of residential energy hubs in smart grids,” Smart Grid, IEEE Transactions on, vol. 3, no. 4, pp. 1755–1766, 2012

S. Makonin, F. Popowich, L. Bartram and I. V. Bajic, “AMPds: A public dataset for load disaggregation and eco-feedback research,” in Proc. IEEE Electrical Power Energy Conference (EPEC), Halifax, Canada, IEEE Press, 2013, pp. 1-6, doi:10.1109/EPEC.2013.6802949.

A. Tani, M. B. Camara, and B. Dakyo, “Energy management in the decentralized generation systems based on renewable energyultracapacitors and battery to compensate the wind/load power fluctuations,” Industry Applications, IEEETransactionson, vol.51, no.2, pp.1817–1827, 2015

Mohamed S. Taha; Mohamed, “Optimal”,IEEE transaction on,2014.

ChenyiZhou; SongLiu; PengLiu,”Neural Network Pattern Recognition Based Non-intrusive- Load Monitoring for a Residential Energy Management System”, 3rd International Conference on Information Science and Control Engineering, 2016.


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