Bloomberg has released May 2014 PV Spot Prices with current module costs (COGS), margins and sales prices. This data is extended to profile the levelized cost of energy (LCOE) for solar PV technology, and is combined with new solar efficiency data to define the LCOE roadmap for solar energy in Qatar going forward.
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A critical component of the economics of solar PV in Qatar is the ability to translate solar power production into local gas market efficiencies and displacement of natural gas demand. More important: the ability to extend gas displacement into higher LNG exports AND to link the export cash flows to the income statement of the solar power systems. The result can be solar PV projects that are economically feasibility in the absence of government grants, production subsidies or tax incentives. Meanwhile, project cash flows tied to natural gas exports can be 20% to 400% greater than cash flows from power sales, depending on the domestic power tariff in force and the gas marketing strategy used.
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Solar data collection, as defined by ISO and WMO standards, is a relatively new activity in Qatar. This article summarizes initiatives underway. In nearly all cases, public access to the solar radiation data is limited since data collection remains immature and unvalidated, or the data is strongly aligned to private commercial interests. Notwithstanding, data collection efforts are making significant progress and are likely to benefit renewable energy strategy development and policy design at the national level.
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The standard way to read text files into R is to use the read.table() command. However, many users struggle with time delays when loading large data sets. An alternative command that offers significant speed improvements is fread(), or fast read, which can found in the data.table package. The following code loads a tab delimited file with a million elements and reveals that fread() reduces load time by almost 99%, as confirmed by the benchmark performance stats at left. The function is still under development, but it is available for download and doesn’t suffer from stability issues. Instead, expect argument structure and command syntax to change over time.
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An innovative CSP storage demonstration project is being pursued by Sandia National Laboratories and Areva at the U.S. Department of Energy’s (DOE) National Solar Thermal Test Facility in Albuquerque, New Mexico. The CSP storage pilot project, partly funded by the DOE, uses the French industrialist’s Compact Linear Fresnel Reflector (CLFR) technology married to a molten salt test loop to reduce the cost of concentrating solar power projects.
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CSP in Saudi Arabia made progress today with the new commissioning announcement by Solar Systems of Australia, a Silex company. A 1MW demonstration project began production at the Nofa Equestrian Resort, a recreational facility owned by His Highness, Prince Sultan Bin Mohammed Bin Saud Al Kabeer. As shown in the project image, the plant uses Solar System’s “dense array” dish concentrator solar technology. There are 26 dishes in total and project economics were justified by displacing on-site diesel generation for the remote facility.
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With language, we learn to listen and to speak. With literacy, we learn to read and to write. With programming, we learn how to use and to make software programs. Programming is the new literacy of the digital age. Scientific programming is an essential skill. It allows us to respond to new data structures and new technology, to expand Internet interfaces, to challenge common understandings or wisdom, and to access the control panels of machines and civilization.
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Dubai Electricity and Water Authority
This week, PV Insider, CSP Today and MENASOL hosted a seminar on Optimal O&M for PV Plants in MENA. It gave practical insight into some of the soiling and O&M issues that developers, asset managers, and debt providers take into account in O&M planning and budgeting.
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Beamer is a document class that is by far the most practical tool for making presentations involving data science, business analytics, or general research. It is widely used in most conferences and easily lends itself to data intensive reporting and repetitive batch processing.
A custom beamer template is presented that is easy to extend or modify. The benefits of the beamer document are numerous:
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The levelized cost of energy (LCOE) is presented by region and for different power generation technologies. The simple model ignores the impact of subsidies, financing and tax impacts to focus on relative performance by technology.
The LCOE data is compared to annual average power prices. In practice, price levels can vary over wide ranges, especially given winter weather. Several noteworthy conclusions are evident when average prices are used:
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Air Mass Coefficient
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The air mass coefficient defines the path length (or column depth) of sunlight through the atmosphere. The air mass for dry air, wet air and dust are key inputs for estimating solar extinction and the irradiance intensity on the Earth’s surface. The air mass coefficient is a ratio between the path length for a specific zenith angle and the column depth when the zenith angle equals zero.
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The solar constant represents the mean amount of total solar irradiance (TSI) at the top of the Earth’s atmosphere. The following code downloads TSI measurements across a range of experiments and satellite data collection efforts to present a composite time series of TSI spanning the period 1976 to 2013. The objective is to confirm the numeric value of the solar constant and to define the amount of variation in solar irradiance entering the Earth’s atmosphere.
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Additional chapters under R Programming have been completed, delivering new text on R colors and the Grammar of Graphics package ggplot. The R color table can be downloaded here
R Colors By Name (77 downloads)
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Renewable energy in Kuwait is well supported. The Kuwait Petroleum Company and the Ministry of Water and Electricity sponsored a joint study by the Kuwait Institute of Scientific Research to determine the potential for renewable energy given an optimal generation mix. Study details have been presented publicly, revealing the following model inputs: wind and solar resource assessment data, RE technology costs short- and long-term, short-term hourly demand profiles, long-term power demand forecasts, power sector plant performance, and energy price forecasts.
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