研究目的
Investigating the effect of different meteorological input data on the sizing of stand-alone photovoltaic systems for energy autonomy in remote areas.
研究成果
The use of TMY time series presented higher reliability in sizing stand-alone PV-ES system than using annual time series of historical years or the Mean Year. The PV-ES size was highly affected by the month of January which is the month with the lower solar radiation values and the higher energy demand. The results of the study showed that TMY as input data can provide increased reliability compared with installations resulted from the historical years, and can be used to determine a PV-ES system size able to fully cover the electrical requirements of the domestic consumer.
研究不足
The study is limited to the use of specific meteorological data series and a specific geographical location (Rhodes). The results may vary with different data sets or locations.
1:Experimental Design and Method Selection:
The study uses the computational algorithm Energy System Analysis (ESA) developed by the Soft Energy Applications Laboratory of University of West Attica to simulate the PV-ES system with an hourly time step for each different data series.
2:Sample Selection and Data Sources:
14 different time series of solar radiation with the corresponding air-temperature were used, including annual hourly measurements of 12 years from the period 1985-1999, a Mean Year (MY), and a Typical Meteorological Year (TMY).
3:List of Experimental Equipment and Materials:
The PV area is comprised of one or more photovoltaic modules with nominal power of 320 Wp and maximum efficiency of 16.5%. For the ES system, the lead acid batteries technology was chosen.
4:5%. For the ES system, the lead acid batteries technology was chosen.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The ESA simulates the system with an hourly time step for each different data series and provides the different combinations of PV-ES which assure energy autonomy.
5:Data Analysis Methods:
The results are analysed and the optimum solution based on certain criteria is chosen for the energy autonomy of a specific consumer profile in the area of Rhodes.
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