CQUniversity Australia - MD Rahat Hossain

STUDY
ENGAGE
ABOUT US
RESEARCH
ACADEMIC

Research Details

Thesis Name: A Novel Hybrid Method for Solar Power Prediction

Thesis Abstract:

. Solar energy is judged as potential power producing resource because of its accessibility and geographical benefits in local power productions. Still a negative aspect, to solar choice, is its intermittent nature and dependence on climate variation. Solar energy resource, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident solar radiation which does not always radiate when electricity is needed. This results in the variability, unpredictability, and uncertainty of solar energy supply. Consequently, the accurate or precise prediction of solar power presents a major challenge to distribution and transmission grid operators because knowing how much electricity installations will produce over the next certain specific period of time is the only way to optimally integrate large scale solar electricity into power grid operations. The involvement of renewable sources with storages make it mandatory to precisely predict the gains and the loads because based on that precise prediction control decision is made. Nonetheless, such hybrid forecasting has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. However, with the increased complexity in contrast to single power prediction systems, most hybrid prediction system, particularly heterogeneous regression algorithms or machine learning techniques based hybrid.....

Why my research is important/Impacts:

Power generated from renewable sources (i.e. solar, wind) cannot be managed like conventional power sources: their power production is not imposed by human intervention but by meteorological conditions. Power generation has several different formats, but almost all energy forms originated from the sun. Solar energy systems utilize the sun’s radiation system directly by means of photovoltaic energy. Uncertainty naturally influences solar power because the production of electrical energy from solar resources relies on the quantity of radiance in a particular site. Efficiency of solar power forecasting systems depends on the obtainable solar radiation, temperature and wind speed at the system location. Previous few years, significant attempt were functional towards the research of various issues linked to the forecasting accuracy of solar photovoltaic schemes. The problem is very tedious and complex, not only because of the various uncertainties at each stage, starting from the meteorological and load data to the economic analysis, but also because of the nature of the photovoltaic systems, unlike the widely used conventional, and fuel-driven systems. An accurate simulation of the performance of any solar energy forecasting system will require historical meteorological data that are representative of the conditions occurring at the location of interest. However, the length of historical records is generally too short in most of the cases to permit reliable energy forecasting to be forecasted. Unreliable generation sources like solar can have a detrimental effect on grid stability as their power output levels fluctuate with meteorological conditions......

Funding/Scholarship: Postgraduate Research International Scholarships (PRIS); Co-Funded Industry Scholarship (CIS) by Australian Power Institute (API)