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dc.contributor.authorBatool, M.
dc.contributor.authorIslam, Syed
dc.contributor.authorShahnia, Farhad
dc.date.accessioned2017-03-15T22:27:40Z
dc.date.available2017-03-15T22:27:40Z
dc.date.created2017-03-14T06:55:52Z
dc.date.issued2016
dc.identifier.citationBatool, M. and Islam, S. and Shahnia, F. 2016. Stochastic modeling of the output power of photovoltaic generators in various weather conditions, in Proceedings of the Australasian Universities Power Engineering Conference (AUPEC), Aug 25-28 2016. Brisbane, QLD, Australia: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/50734
dc.identifier.doi10.1109/AUPEC.2016.7749382
dc.description.abstract

The intermittency of solar-powered energy sources prompt the uncertainty of load management. The influence of shading (whatever the reason may be) directly diminishes the feasible output power of the photovoltaic (PV) generators. The major causes of shading are the weather condition changes like the clouds, storms, and rains. Thereby, the dispatchable power for a distinct weather condition at an explicit time frame needs to be quantified. The stochastic modeling of a practical PV system has been performed in this paper. A step-by-step MATLAB-based algorithm is developed for tracking of dispatchable power limit using the Monte Carlo Principle. The proposed algorithm describes the weather condition as a function of cloud presence. The prescribed characteristics consist of the solar irradiance and the ambient temperature. The impact of weather changes on the output power of a PV system is evaluated by this algorithm. The results of this research are concluded by realistic data analysis taken from the Australian bureau of meteorology.

dc.titleStochastic modeling of the output power of photovoltaic generators in various weather conditions
dc.typeConference Paper
dcterms.source.titleProceedings of the 2016 Australasian Universities Power Engineering Conference, AUPEC 2016
dcterms.source.seriesProceedings of the 2016 Australasian Universities Power Engineering Conference, AUPEC 2016
dcterms.source.isbn9781509014057
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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