IEEE Power & Energy Magazine - November/December 2017 - 26

Spatial variability of solar and wind resources differs
by region and can impact the geographic distribution
required to achieve geographic diversity within a system.
by comparing the spatial variability of direct normal irradiance (DNI) for two regions in India. In both circled images,
the center-point daytime hourly DNI was correlated to each
neighboring pixel's daytime hourly DNI out to 200 km (over
many years). The top left of the figure shows Jaisalmer, a city
in the arid desert region of Rajasthan, India. At the bottom
right is Chennai, a city off the coast of the Bay of Bengal in
Tamil Nadu, India. As the illustration shows, the DNI in Jaisalmer is highly correlated and homogeneous out to 200 km;
in Chennai, on the other hand, the correlation coefficient
drops rapidly when moving inland, away from the bay-and
it declines more slowly when moving north and south along
the coastlines.
Geographic diversity in variable renewables decreases
this risk. Spreading resources among large regions mitigates
the impact of weather events. For wind and solar resources,
spreading the capacity among multiple areas decreases the
impact of any one meteorological event, such as a weather
front or a cloud. For wind, the benefits of transmission are
large; for solar, temporal diversity can be increased by spreading resources among lines of longitude. As the Earth rotates,
the irradiance for a given location changes-for example,
solar noon in New York City happens before it occurs in Buffalo, New York. If solar resources are spread among time
zones, the peak in solar generation broadens, reducing the
impacts of sunrise and sunset in addition to those caused by
weather events.
Experience with wind and solar confirms these theoretical conclusions. In the United States, most regional independent system operators (ISOs) are experiencing rapidly
increasing wind and solar penetration. Each has a unique
geography and resource mix. The Midcontinent System
Operator (MISO) manages one of the world's largest
energy and operating reserves markets. It ensures reliable
delivery of electricity at the lowest cost across high-voltage power lines in the midcontinental region of the United
States and Canada.
In 2016, MISO's annual wind energy penetration level
was 8%, and it experienced a record instantaneous penetration level of more than 22% of load served (12.5 GW) on
13 November 2016 at 4 a.m. MISO's wind peak output was
13.6 GW, which occurred on 7 December 2016 at 11 p.m.
MISO's large geographic scope enables it to balance large
amounts of wind generation with a diverse resource portfolio, even though most of the wind is located in MISO's
northern region. This region includes most of the load for
Minnesota, Iowa, North Dakota, South Dakota, Wisconsin,
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ieee power & energy magazine

Michigan, and Manitoba. The MISO north region experienced an annual wind energy penetration level of 26.8% in
2016 with a maximum penetration of 80% of load served. As
wind penetration increases, MISO has also been pioneering
more sophisticated methods of counting wind's contribution
to resource adequacy. These simulations include a lookahead to higher penetrations over time.

Fact Three: Wind and Solar Forecasting
Provide Significant Value
Wind and solar generation can be predicted with some accuracy. Diurnal patterns such as sunrise and sunset can be calculated precisely at every point on the globe, and large-scale
weather systems can be monitored as they cross oceans
and continents. These observable facts enable meteorologists to work with power system planners and operators to
anticipate, prepare for, and mitigate a variety of weatherdriven events that impact the generation of wind and solar
power plants.
Weather forecasting is not new. The predecessor to the U.S.
National Oceanic and Atmospheric Administration, the U.S.
Weather Bureau, was created in 1870 by President Ulysses S.
Grant to assist the military in anticipating storms that could
impact military activities and commercial operations on the
nation's waterways. The benefits of weather forecasting were
later realized by broader economic needs for agriculture and
transportation. No farmer ignores the weekly weather forecast, and many people look at the radar when their flight is
delayed. In the electricity industry as in the agriculture and
airline industries, weather forecasts-specifically, composite
wind, solar, and load forecasts-are critical to minimize risk
and maximize efficiency.
In modern power systems, weather forecasts become
increasingly important. Grid operators have been using
weather forecasts to anticipate challenging load conditions
for decades. Early research in power systems operations with
wind energy showed that power forecasts can provide significant value in their simplest form. For example, if high winds
are anticipated for a period of time, thermal generation can
reduce output, thereby reducing fuel costs to the system. More
sophisticated forecasts that leverage machine learning are
becoming increasingly popular as one method to reduce
system costs.
The unit commitment decision that power system planners
face is complex. Failure to commit sufficient resources to
meet expected conditions can result in operator actions that
may be expensive-e.g., starting a combustion turbine in real
november/december 2017

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - November/December 2017