Calculating lifetime solar energy cost with new, balanced approach

February 8, 2011 By Angela Hardin
Argonne chemist Seth Darling measures the performance of a nanostructured organic photovoltaic cell. Credit: Argonne National Laboratory

Researchers at the U.S. Department of Energy's Argonne National Laboratory in partnership with an analyst at Gartner, Inc. have developed a new and more instructive approach to calculate the lifetime cost for a solar-generated energy system for comparison to other energy systems.

Usually when people consider the cost of , they use the dollars per Watt metric, which is only a measure of the initial capital cost and the solar panel vendor's performance specification. This doesn't take into account the actual you will get from the system or other cost factors such as maintenance. A far more informative metric is the levelized cost of energy (LCOE).

"In typical LCOE projections for solar energy, many assumptions are swept under the rug, and we wanted to make a small step toward lifting up that rug and showing how you can truly get a handle on those assumptions to develop a more accurate picture of the potential costs," said Argonne solar researcher Seth Darling, who leads the development of the new approach. LCOE is the cost of an over its lifetime per energy unit produced.

"Specifically, the Argonne approach uses a that statistically selects from probability distributions to account for the uncertainly associated with various cost and production parameters," Darling said. A Monte Carlo simulation can produce millions of possible performance outcomes that might occur in the future, weighted to reflect their likelihood.

A variety of stakeholders, including investors and , are tracking the generational development and commercialization of solar technologies and require greater insight into the projected costs of a solar energy project to aid in decision making.

"Investors need to know their expected return on investment, regulators and policy makers help define the economies of energy productions and require reliable information, funding agencies need a means to analyze proposed technology development, and technology developers want to understand how they will compete relative to other technologies," according to a new paper published by the researchers.

Argonne's optimized approach to calculating the LCOE for photovoltaics will provide each group with better guidance. However, implementing this approach will require development of more rigorous data sets of location-specific solar panel performance and other parameters. Fair comparison to traditional energy sources, such as coal or natural gas, will require a re-examination of the hidden costs associated with those technologies.

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More information: The new methodology is presented in the paper "Assumptions and the levelized cost of energy for photovoltaics" in Energy & Environmental Science.

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5 / 5 (1) Feb 08, 2011
Like many things, going bigger is more efficient.

Yesterday, while search youtube for solar related advancements, I found videos of a 40MW parabolic trough power plant using pipes in vacuum tube. Well, 40mw is what the plant is really rated, but I calculated it probably produces closer to 58MW during the day, though some of this is used in pumping water, and some is stored as steam for night time use, so 40mw is probably an "average".

Going with larger mirrors means you can have larger pipes which hold more water, but have lower surface area, which in turn means even better performance because of less heat loss. with the vacuum tubes they have almost no heat loss, except at contact points, which is unavoidable.

You can still make back yard solar power for water heating and home heating, and these are still cheaper and more cost effective than photovoltaics. I've seen SMALL homemade solar units which cut winter water heating bill in half and removed summer bill completely.
4.7 / 5 (3) Feb 08, 2011
I'll use this new metric as soon as we

- add the environmental cost to fossil fuels
- add the cost of tens of thousands of years of storage for radioactive waste to nuclear power

THEN it will be a fair comparison.

(As an aside: Monte Carlo methods only give good resukts if you paramtrize them correctly. I somehow doubt that they have good parameters for all possible deployment scenarios (and if they did then a Monte Carlo smimulation would not be necessary because a simple expected value would enough)

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