Research Progress: PV Solar

Intiation of a Database
In order to provide an easily-accesible, comprehensive solution for solar power availability data we decided to work on developing a database. Power availability is determined by the capacity factor or the amount of actual energy produced over the available rated energy of a PV system. In order to calculate capacity factors for a site, AC output had to be generated from either the PVWatts or SAM software available through NREL. We used PVWatts Version 1 because the data is calculated from actual NSRDB locations and thus provided a limited, accurate source for gathering data in a time-consuming manner. By clicking through the GUI format, we obtained site location, radiation, AC output, and cost/energy value for the Southeastern United States. This region was chosen because it is generally given less attention than the rest of the southern states for solar power and was observed to have relatively low wind potential. Each state’s data was compiled into a separate excel file where calculations were made and then the result summarized into one database.
 
The capacity factor (CF) was calculated using two different equations based on the difference in potential and actual rated capacity of PV systems.  While scientific analysis provides reason to consider a derated capacity factor so as to determine the ratio between actual AC output and actual AC capacity, industry standards have promoted using the nameplate DC capacity instead. NREL scientist confirmed that the AC-to-AC CF makes more sense but NREL had to change their calculations in 2005. Thus solar capacity factors are quite low.
 
                   
 
where Ptotal out is the value generated from the model for a typical year in kWh and the DC rated capacity is 4.0 kW. To convert output from kWh to kW, the denomenator is mutiplied by 8760, the total hours in the year. In the AC-to-AC capacity factor, the Derate Factor is the estimated losses in conversion and transmission of DC power to AC useable electricity. We assumed the NREL default Derate Factor of 0.77 for our calculations to be consistent in creating a universal database. Because the data is taken for the full 60 minutes of each hour no additional conversion is needed for capacity factor.
 
Monthly capacity factor was also calculated using a similar formula for each month. Monthly capacity can be useful in analysis of feasibility for PV application during only a specific time of the year such as the summer time (when electricity cooling costs are higher). Peak and Off-peak capacities have not yet been included due to a lack of accessible hourly data.
 
 
Zoning by Capacity Factor 

While we realized the data was limited in quantity for zoning by capacity at the state level, we decided to zone the Southeastern United States together to provide greater accuracy. The rest of the U.S. can be zoned in this manner if further analysis is performed on the data available from the 239 NSRDB sites. The range of solar capacity values for large areas of the U.S. is similar so it might make more sense to have inter-state zones instead of intra-state zones.  

 

We considered 3 factors in determining zone lines for solar energy: capacity factor, latitude/longitude coordinates, and geographical features.

·         Capacity Factor: all sites should have a similar capacity factor for all three types of arrays. We assigned industry standard capacity factors to zones.

·         Lattitude: The N-S coordinates of a site determines the incidence angle for solar radiation. Thus, we tried to make zone lines primarily in the East-West direction.

·         Geographical Features: We zoned specific areas in accordance to the terrain as this will help determine the feasibility of development in specific zones

 

The resulting figure shows 6 different zones.

 

 

Using criteria of capacity factor, latitude, and geographical features of the lang, the following patterns were found:

·         Zone 1 had the highest capacity factors followed by 2, and 3

·         Zones 5 and 6 had the lowest capacity factors

·         Zone 4 was based on a lower CF and Appalachian Mt terrain

 Each zone's capacity factor was averaged and analyzed to develop a 95% confidence interval for each zone. More sites will be necessary to develop more accurate zones in the future. The equations used to calculate the average capacity factor and standard deviation is included below. 

 

                                             

 where N is the set of all sites within the specific zone, n is the number of sites in that zone and CFi is the Industry Standard CF. For the standard deviation calculation, Xi is the annual average CF at site i, and  is the average of the annual average CFs of every site within the zone.