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7 projects looking to use big data to cut the cost of solar power

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The Department of Energy is putting a collective $9 million into 7 projects being developed at universities and government labs that will us big data to lower the cost of solar in various ways. The projects, at places like Yale, and the National Renewable Energy Laboratory, will be focused on using analytics to lower the cost of solar installations and making solar cells more efficient.

Apple's massive solar farm in North Carolina, photo by WCNC-TV
Apple’s massive solar farm in North Carolina, photo by WCNC-TV

Here’s the 7 projects:

  • A solar financing model: NREL and solar financing startup Clean Power Finance will use $2.26 million to analyze data from 1,300 solar installation companies to try to create new types of community and regional financing methods.
  • A publication and patent reader: SRI International, the University of Toledo and GE (s GE) will use $600K to create software that can read and analyze science publications and patents to unearth innovations that can lower the cost of solar.
  • Articulate a solar theory: Gordan Moore had his own law for chips, and some in the solar sector talk about a Swanson’s Law for the dropping cost of solar, but folks at MIT will use close to $500K to study the tech evolution process of solar and to create an overarching theory.
  • Better forecasting of production costs: Researchers at the University of North Carolina at Charlotte, Arizona State University and the University of Oxford will use almost $950K to analyze data about patents, prices and production to create better forecasts of solar cell, wafer and panel prices.
  • A model for solar markets: Sandia National Labs, the University of Pennsylvania and the California Center for Sustainable Energy will use $2.3 million to process data about solar markets and to create a model looking at how economic and social issues impact solar installations.
  • Better strategies for community-led solar purchasing: Yale and SmartPower’s New England Solar Challenge will use $1.9 million to develop new strategies to that can make community solar buying programs work better.
  • More effective solar installation in Texas: The University of Austin will use close to $500K to collaborate with six Texas utilities to create more strategic ways to install and interconnect solar in the state.

3 Responses to “7 projects looking to use big data to cut the cost of solar power”

  1. And here I figured they were going to figure out a way around paying people with solar panels “net metering” rates.

    In case you don’t know, in most states power companies are required to buy excess solar power from consumer (roof top) systems at retail rates. While this is great for solar producers, it’s terrible for the power company because they lose any margin they would have made on the difference between wholesale and retail prices.

    Now before you cry crocodile tears for the power companies, remember they basically have a fixed rate, set by the states’ PUC, except in areas that have “competition.” Those rates are based on operating cost + rate of return. When you are forced to buy power from a solar panel at retail rates, they basically are working for nothing and losing money. Eventually if enough people have solar installations the power company will need to raise rates on everyone (which will hurt non-solar homes, most of whom aren’t going to be able to invest the capital to put up a solar system, or happen to live on lots that aren’t solar-friendly, etc).

    • Pawel Szczesny

      You are forgetting the other side of the coin:
      1. Solar PV produces energy during the day during most of the peak hours. While most customers pay a standard flat rate, the true cost of energy based on the time of use is 4:1.
      2. Distributed production. Because most systems are distributed throughout the region and they product energy during peak hours, they tend to have a stabilizing affect on the grid. Granted solar PV has to have a penetration of less then 25% on most grid’s before it has an adverse affect, due to shading.
      3. Because of point number 2, there is less money wasted by the utility that accounts for transmission losses. There is also LESS! wear and tear on the distribution system. I know the utilities are making it seem like it’s the other way around, but those small and medium sized systems (1-300kW) don’t produce enough for there to be any actual reverse flow of energy. That energy simply gets gobbled up by the local users, thus creating lesser strain on the distribution system.

      I’m not saying that your point isn’t valid. It’s just that it’s not one sided. There has finally been conducted a investigative paper by NREL, about the effects of PV generation on the grid. In 70% cases, they had a net-positive affect on the grid. Some of the oldest grids that have mostly coal generators, don’t fare so well with renewables.

  2. Luella Daube

    If you think Willie`s story is something,, 4 weaks-ago my brother’s best friend basically got paid $7358 grafting a fourteen hour week at home and the’re neighbor’s mother-in-law`s neighbour was doing this for 4 months and got over $7358 parttime at there labtop. the tips on this site………..