BOULDER — Applying its atmospheric expertise to solar energy, the National
Center for Atmospheric Research (NCAR) is spearheading a three-year, nationwide
project to create unprecedented, 36-hour forecasts of incoming energy from the
Sun for solar energy power plants.
The research team is designing a
prototype system to forecast sunlight and resulting power every 15 minutes over
specific solar facilities, thereby enabling utilities to continuously anticipate
the amount of available solar energy. The work, funded primarily with a $4.1
million U.S. Department of Energy grant, will draw on cutting-edge research
techniques at leading government labs and universities across the country, in
partnership with utilities, other energy companies, and commercial forecast
providers.
Much of the focus will be on generating detailed predictions
of clouds and atmospheric particles that can reduce incoming energy from the
Sun.
“It’s critical for utility managers to know how much sunlight will
be reaching solar energy plants in order to have confidence that they can supply
sufficient power when their customers need it,” says Sue Ellen Haupt, director
of NCAR’s Weather Systems and Assessment Program and the lead researcher on the
solar energy project. “These detailed cloud and irradiance forecasts are a vital
step in using more energy from the Sun.”
The project takes aim at one of
the greatest challenges in meteorology: accurately predicting cloud cover over
specific areas. In addition to helping utilities tap solar energy more
effectively, detailed cloud predictions can also improve the accuracy of
shorter-term weather forecasts.
The project expands NCAR’s focus on
renewable energy. NCAR designed a highly detailed wind energy forecasting system
with Xcel Energy that saved Xcel ratepayers an estimated $6 million in a single
year. The center is also creating advanced prediction capabilities to enable
wind farm developers to anticipate wind energy potential anywhere in the
world.
“Improving forecasts for renewable energy from the Sun produces a
major return on investment for society,” says Thomas Bogdan, president of the
University Corporation for Atmospheric Research, which manages NCAR on behalf of
the National Science Foundation. “By helping utilities produce energy more
efficiently from the Sun, we can make this market more cost
competitive.”
-----Clouded forecasts-----More than half of all
states in the U.S. have mandated that utilities increase their use of renewable
energy as a way to reduce dependence on fossil fuels such as coal, oil, and
natural gas, which affect air quality and release greenhouse gases associated
with climate change. But the shift to energy sources such as solar or wind means
relying on resources that are difficult to predict.
Because large amounts
of electricity cannot be stored in a cost-effective manner, power generated by a
solar panel or any other source must be promptly consumed. If an electric
utility powers down a coal- or natural gas-fired facility in anticipation of
solar energy, those plants may not be able to power up fast enough if clouds
roll in. The only option in such a scenario is to buy energy on the spot market,
which can be very costly.
Conversely, if more sunshine reaches a solar
farm than expected, the extra energy can go to waste.
But predicting
clouds, which form out of microscopic droplets of water or ice, is also
notoriously difficult. Clouds are affected by a myriad of factors, including
winds, humidity, sunlight, surface heat, and tiny airborne particles, as well as
chemicals and gases in the atmosphere.
Solar energy output is affected
not just by when and where clouds form, but also by the types of clouds present.
The thickness and elevation of clouds have greatly differing effects on the
amount of sunlight reaching the ground. Wispy cirrus clouds several miles above
the surface, for example, block far less sunlight than thick, low-lying stratus
clouds.
To design a system that can generate such detailed forecasts,
NCAR and its partners will marshal an array of observing instruments, including
lidars (which use laser-based technology to take measurements in the
atmosphere); specialized computer models; and mathematical and artificial
intelligence techniques. Central to the effort will be three total sky imagers
in each of several locations, which will observe the entire sky, triangulate the
height and depth of clouds, and trace their paths across the sky.
The
team will test these advanced capabilities during different seasons in several
geographically diverse U.S. locations: the Northeast, Florida, Colorado/New
Mexico, and California. The goal is to ensure that the system works year round
in different types of weather patterns.
-----Not just for solar
energy-----Once the system is tested, the techniques will be widely
disseminated for use by the energy industry and meteorologists.
“This
will raise the bar for providing timely forecasts for solar power, ” Haupt says.
“It also represents a great opportunity for providing far more detail about
clouds in the everyday weather forecasts that we all rely on.”
One
application for such detailed forecasts could be short-term predictions of
pavement temperatures. Such information would be useful to airport managers,
road crews, and professional race car drivers.
“Pavement temperatures
make quite a bit of difference in how tires grip the surface,” says Sheldon
Drobot, deputy director of NCAR’s Weather Systems and Assessment Program. “This
has substantial safety implications.”
NCAR is launching the solar project
with numerous partners in the public and private sectors. These include:
Government labs: National Renewable Energy Laboratory, Brookhaven
National Laboratory, the National Oceanic and Atmospheric Administration’s Earth
System Research Laboratory and other NOAA facilities;
Universities: The
Pennsylvania State University, Colorado State University, University of Hawaii,
and University of Washington;
Utilities: Long Island Power and Light, New
York Power Authority, Public Service Company of Colorado, Sacramento Municipal
Utility District (SMUD), Southern California Edison, and the Hawaiian Electric
Company;
Independent system operators: New York ISO, Xcel Energy, SMUD,
California ISO, and Hawaiian Electric; and
Commercial forecast
providers: Schneider Electric, Atmospheric and Environmental Research, Global
Weather Corporation, and MDA Information Systems.
Computing time will be
provided by the New York State Department of Economic Development's Division of
Science, Technology and Innovation on an IBM Bluegene computer at Brookhaven
National Laboratory.
The University Corporation for Atmospheric Research
manages the National Center for Atmospheric Research under sponsorship by the
National Science Foundation. Any opinions, findings and conclusions, or
recommendations expressed in this publication are those of the author(s) and do
not necessarily reflect the views of the National Science Foundation.