# NASA Office of Earth Science -- Applications Program

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

*ENERGY MANAGEMENT*

***Program Plan: 2004-2008***

![](media/image1.wmf){width="1.1902777777777778in"
height="0.9840277777777777in"}*Science for Society*

> *Accelerating the realization of economic*
>
> *and societal benefits from Earth science,*
>
> *information, and technology ...*

**ENERGY MANAGEMENT**

*Program Plan: 2004-2008*

**I. Purpose and Scope**

#### ESE & Applications Program

The purpose of NASA's Earth Science Enterprise (ESE) is to increase our
knowledge of the Earth system, including its response to natural and
human-induced changes to enable improved predictions of climate,
weather, and natural hazards. ESE and the Applications Program serve
NASA and Society by expanding and accelerating the realization of
societal and economic benefits from Earth science, information, and
technology research and development.

The overarching goal of the Applications Program is to bridge the gap
between Earth science research results and the adoption of data and
prediction capabilities for reliable and sustained use in decision
support.

The Enterprise works through partnerships with public, academic, and
private organizations to develop innovative approaches for using Earth
science information and technology. The Applications Program enhances
the availability, interoperability, and utility of Enterprise and
private sector data sets, communications, computing, and modeling
capabilities to serve specific national applications.

Overall, the approach is to enable the assimilation of Earth science
data and model outputs to serve as inputs to decision support tools and
assessments. Developments may be specific to a national application or
may be served through a cross-cutting solution. The outcomes and impacts
are manifest in enhanced decision support and the social and economic
benefits gained through improved decision making, public information,
and efficient and effective management.

#### National Applications 

The specific National Applications partner with organizations,
especially Federal and private-sector organizations, with appropriate
information infrastructure to apply NASA data and models. These partners
own and operate Decision Support Systems for their policy, analysis and
management responsibilities.

The Applications Program supports the national applications by providing
the partners with opportunities to enhance their Decision Support
Systems. A challenge is to integrate copious volumes of data with
computationally demanding scientific models in order to produce and
package products that operational users can accommodate in their systems
for analysis and decision making. Decision Support Systems provide
systematic mechanisms to handle the volumes of data, incorporate model
outputs and predictions, and benchmark the value of the products.

The Enterprise Applications Program employs functional steps of
Applications Research, Verification & Validation, and Benchmarking in
its systematic approach to bridge the gaps between the research and
operational domains.

> *Applications Research*: Evaluate the requirements and technical
> feasibility of Earth science data and models, information products,
> and predictions in partners' operational decision support needs.
>
> *Verification & Validation*: Measure the performance characteristics
> of data, information, models, and predictions to meet requirements for
> the applications.
>
> *Benchmark*: Enable the adaptation and adoption of geospatial
> information and methods derived from Earth science results to serve
> decision support

The desired outcome of the national applications is for the partner
organization to use the project results, such as guidelines and
prototypes and procedures, as benchmarks for operational use and enhance
their management and decision-making capabilities with appropriate Earth
science products and tools.

The following Program Plan describes the activities for a systematic
approach to evaluate, verify, benchmark, and extend the use of Earth
Science knowledge, data, and technology to support our partners'
decision support tools and management responsibilities.

#### Energy Management Purpose

To improve the Nation's public and private capability for integrating
environmental data into sound management of energy demand and energy
availability while expanding the economy and raising the standard of
living of all Americans. NASA's science missions in cooperation with
other federal agencies and research organizations have made measurable
contributions to the understanding of climate, weather, land usage in
the context of natural and human influences on the environment. NASA
intends to add value to applications focused on energy demands and
availability with traditional primary renewable and non-renewable
resources. Applications with alternate primary energy sources will also
be evaluated.

NASA recognizes that Federal Departments such as Interior, Agriculture,
Commerce, Transportation, and Energy, and Agencies such as Environmental
Protection, Federal Emergency Management have primary responsibilities
in energy production, consumption and conservation. NASA will work
cooperatively with these entities and the private sector to apply our
unique science results and mission technology to further the National
goals for energy independence.

The Energy Management Applications Program intends to coordinate with
various agencies, industry associations, and companies to convert
appropriate ESE radiation and meteorology science data over the globe
into industry-specific parameters and formats for incorporation into
industry and other-agency government Decision Support Systems (DSS).

#### Background

In the year 2000, energy-sector industries associated with producing,
supplying, and consuming electrical power exceeded \$1.4 trillion.
Recent energy-related shortages have fueled the debate over national
energy policy, bringing to the forefront issues concerning increased
energy-efficient consumption, production of energy from new sources, and
the integration of these new sources of power into existing grids.
Ensuring affordable energy is critically important to the health of the
nation's economy. As energy-related technologies become more
sophisticated, the demand for more detailed weather and solar radiation
information increases. This applications program is dedicated toward
expanding the use of weather and solar energy information in
energy-related industries. To date four of these industries have been
identified and targeted for use of from NASA analysis and modeling data.

1.  **Renewable Energy Production**: One developing energy source,
    renewable energy technologies (RETs), is expected to provide between
    5% and 10% of the world's energy within 25 years, rising to 50% by
    the year 2050. The estimated average growth rate of the solar energy
    (photovoltaic) market is 25% per year through the year 2010
    (Maycock, 2000). Growth in wind turbine sales has averaged 40% per
    year for the past 5 years (Gipe, 2000). Utility-grid-connected solar
    thermal power plants will be cost competitive with fossil fuel
    plants in the near future, and various international organizations
    are currently offering significant economic incentives to deploy
    initial plants (Rannels, 2000). During the last decade, renewable
    energy sources contributed substantially to the growth in U.S.
    energy production, outpacing all fuel sources except for nuclear
    energy (National Energy Policy, 2001). Estimates of the magnitude
    and variability of solar energy and prevailing winds are critical to
    the optimal selection of locations for these technologies.

2.  **Building Design**: Architects and engineers are incorporating
    energy-efficient technologies into new building projects. A
    scientist with the U.S. Department of Energy, has noted that
    industry now has the capability to design and construct buildings
    that use 50% less energy at no increase in construction cost if
    accurate environmental data are available (Balcomb and Curtner,
    2000).

3.  **Biomass Fuel Development**: Raising crops as a fuel source is a
    large developing industry. This biomass industry originated using
    corn crops, but new species are under development. Many other
    species are also used for biomass-based manufacturing to reduce
    reliance on petrochemicals in other industries. The energy industry
    requires environmental parameters for planning, monitoring, and
    predicting yield of various fuel crops.

4.  **Energy Utilities**: Utility companies make decisions on the buying
    and selling of power based partly on information about short-term
    weather fluctuations and historic seasonal conditions. With growing
    supply from Renewable Energy sources utilities are developing
    strategies to optimize and integrate the production and use of
    alternative energy sources into traditional systems. Traditional
    weather data for air temperature, precipitation, humidity, and wind
    are no longer sufficient.

To date, the energy sector has relied on historical meteorological and
solar energy information only to provide location-specific climate
context to guide the feasibility and optimization of an energy-producing
technology (i.e., wind and solar energy). The historical context helps
to measure the future performance of the technology at that location.
However, information regarding future weather and climate variability is
necessary for more accurate design and for more efficient operation of
systems. The balance between supply and demand of affordable energy is
vitally important to our economy. The energy industries are continuing
to develop decision-support systems to deal with these complexities. The
Energy Management Program envisions the development of datasets to
support these decision-making systems directly.

**II. Approach**

#### Generalized Approach

The approach of Energy Management Program is to develop information
pathways from NASA satellite analysis and modeling to DSS's supporting
energy demand and availability in industry and government entities.
These entities require historical, near-real time, and forecasted
environmental data. Physical quantities of required data are
specifically selected, derived, and formatted to meet the needs for
current DSS's of partner agencies. The data sets will also provide the
opportunity to improve those DSS's. .

To facilitate this approach the Energy Management Program has adopted a
basic 3 step procedure:

1.  *Research*: Study the overall energy field and identify various
    industry sectors and identify government agencies that contribute to
    these sectors. Assess the field needs and as necessary create and
    validate prototype datasets that address those needs.

2.  *Partner:* Make contact and build partnerships with prospective DSS
    developers and data users in government and industry. Increase
    exposure to industry sector and interact with industry engineers and
    scientists.

3.  *Specialize:* Interact with partners and improve prototype datasets
    to better meet the industry needs. Cultivate new users. Upgrade the
    capabilities and parameters as new analysis and modeling techniques
    are developed and improved.

This strategy was applied to the solar and wind industries in the
development of a highly successful web based data set called the Surface
meteorology and Solar Energy (SSE) data set. Since its inception, the
SSE web site has now received over 1.5 Million hits with over 150,000
data document downloads and nearly 14,000 unique users. To develop this
data set NASA climate research data sets were processed to produce
specific parameters needed by industry engineers. The work was completed
in partnership with the Department of Energy/National Renewable Energy
Laboratory (DOE/NREL), the Canadian Meteorological Service (CANMET)
Energy Diversification Research Laboratory (CEDRL), and several small
solar and wind companies. NASA has developed a direct link between the
SSE web site and CEDRL's renewable energy DSS called RETScreen^TM^.

Due to the success above, the Prediction Of Worldwide Energy Resource
(POWER) project has been initiated to expand upon SSE to add near-real
time and forecasted datasets to the historical datasets already being
provided. The POWER project is the central element of the Energy
Management Program.

#### Partner Interactions 

The approach of the Energy Management Program with individual partners
is illustrated in Figure 1 as proposed in the POWER project. Energy
Management is aimed at providing data from new NASA missions and
research projects directly to DSS's used in the energy sector
industries. POWER accomplishes this purpose by facilitating the
development of parameters from weather and climate forecast models to
such DSS's. Since the types and scopes of DSS's vary, this program will
seek specialized partnerships with each partner. For instance the
RETScreen DSS is a package of macros used for the feasibility study of
renewable energy projects that input Solar energy, wind energy and
geothermal energy systems. By its nature it requires a large number of
parameters. Linking directly the SSE website with this package provides
improves the cost benefit analysis of these projects to international
customers including investment agencies. This increases the
competitiveness of the US businesses in global markets. The Energy
Management Program is developing an agreement with the Canadian
government to continue and expand this collaboration through the POWER
project. The SolarSizer is a design package developed by a U.S. company
made specifically to optimize the design of photovoltaic systems. This
package needs a reduced number of parameters involving solar energy and
clouds. ![](media/image3.wmf){width="6.397222222222222in"
height="3.589583333333333in"}

The Energy Management program will expand the number of DSS's supported
in industry and government through POWER and other projects. To this
end, there is already an agreement in place between NASA and the
National Renewable Energy Laboratory, a national laboratory sponsored by
the Department of Energy. The scope of NREL's role in the development of
energy related DSSs is large. This agreement includes the support of an
improvement in the National Solar Radiation Database, vital for US
exploration of solar renewable energy systems. NREL also is developing
programs for energy efficient buildings and redistribution of energy.
The POWER project is aimed to work closely with NREL to develop this
interaction.

Besides NREL the Energy Management Program is targeting other government
agencies for collaboration and partnerships. Negotiations and
collaborations with the National Oceanic and Atmospheric Association
modeling are underway to forge pathways of predicted parameters for
energy industry use. Partnerships with other agencies such as the
Department of Agriculture are also targeted through an already existing
agreement with the USDA and NASA.

Besides government agencies the Energy Management program has targeted
industry societies and consortiums. Negotiations are ongoing to forge a
partnership between the Electric Power Research Institute (EPRI) and the
NASA to support EPRI load forecasting DSSs. EPRI has a developed
short-term load forecasting DSS for utilities. They are interested in
improving this DSS and in developing longer term forecasting tools.
Other societies such as the American Society of Heating, Refrigeration,
and Air-Conditioning Engineers (ASHRAE) and the American Institute of
Architects (AIA) have also been contacted through POWER.

The partnerships above represent active and developing partnerships in
energy-related industry sectors. The Energy Management Program will seek
to expand these and development new partnerships through the POWER
project. The datasets resulting from the program will be designed to
meet the needs of the particular DSS partnership.

#### Logistical Approach and Roadmap

The Energy Management Program has determined that a variety of datasets
are needed to meet the needs of government and industry DSS developers.
These datasets include the long-term datasets of historical parameters
(20 years and longer), near-real time data sets (within hours to a week
of the actual event), and forecasted datasets. Forecasted parameters
have been determined to vary from short-term (2days -- 2 weeks),
mid-term (1 month -- 2 years), and long-term (10 years and over).

Figure 2 presents an overview of the data sources and DSS needs that
encompass Energy Management. In this figure, a project like POWER
provides the integration and benchmarking of parameters identified for
transfer to DSS developers and industry needs. NASA satellite analysis
projects like the International Cloud Climatology Project (ISCCP), the
Surface Radiation Budget Project (SRB) and the Clouds and Earth Radiant
Energy Systems project all will provide key inputs to the products
required for energy-related DSS's. Additionally NASA funds the Data
Assimilation Office (DAO) to provide long-term historical meteorological
data. The DAO is also developing predictive capabilities and is
participating in the NSIPP (NASA Seasonal Interannual Prediction
Project). NASA also funds the climate modeling at the Goddard Institute
of Space Studies (GISS). NOAA has a large program of weather and climate
prediction and for this reason collaboration with NOAA is being pursued.
The interaction of the Energy Management Program with scientific
research and modeling is essential to improve DSSs in the energy-related
fields.

The progressive nature of the link between the Energy Management Program
and the increased capabilities of NASA supported satellite systems is
shown in Figure 3. This figure represents a roadmap of the Energy
Management Program as accomplished through the POWER project. As EOS new
missions are flown an improvement of the data sets and eventually
forecasts will be made. Figure 2 depicts the increase in understanding
in time with each new mission relevant to improving the estimation of
surface meteorology and radiation energy fields. The new data sets will
become the baselines for improved forecasts of the relevant industry
parameters.![](media/image4.wmf){width="6.538888888888889in"
height="3.8805555555555555in"}

The roadmap also shows the strategy to phase in the development of
certain datasets with time. Initially, Energy Management will emphasize
historical datasets and the development of new protoptypes to expand
applicability to new users. Near-real time and forecasted datasets are
phased in with time as better validation mechanisms are developed. Also
phased with time are new industry sectors. For instance, datasets for
the biomass industry sectors are delayed until 2006 when better
precipitation datasets are expected from both satellite and modeling
systems. Electric power industry datasets will take the longest to be
effective due to the expected developed of electric power
redistributions systems.

![](media/image5.wmf){width="6.620833333333334in"
height="4.940277777777778in"}

#### Crosscutting Solutions

The Energy Management program will seek to enhance its goals through
cooperation and leveraging of activities in other application theme
programs. Energy Management through POWER has already sought to develop
a relationship with the Air Quality program to share computing
facilities and thus atmospheric information relevant to both Air Quality
and solar radiation forecasts. Other themes such as Aviation Safety and
Agricultural Competitiveness and Urban Development will yield potential
for further cross-cuts where relevant atmospheric and surface
information will be shared to benefit both programs.

#### 

#### Potential Benefits

Table 1 summarizes benefits a benefits analysis through the initial 6
year period (2003 -- 2008) and beyond. A detailed description of this
benefits table from the POWER project is given in the appendix. The
extended period is provides time for continued improvement and time for
market saturation of the data products and algorithms. Although no
realized estimates are expected to the Biomass and Energy sectors by
2007, the fundamental development for these projects will completed and
in place for measurable benefits in each sector beginning in FY08. These
benefits assume the budgets outlined below.

#### Budget Explanation

The expected costs for FY2003 and the next 5 years for the NASA Energy
Management including the Prediction of Worldwide Energy Resources
(POWER) project is given in Table 2. Through FY 2008, the project ramps
up capabilities by providing for research into the identification and
development of industry parameters needed for the utility energy and the
energy efficient building architecture/engineering industry sectors. The
NASA contribution to the funding level at this time is estimated at
\$1.25 million dollars. Although, the funding levels beyond FY 2008 are
still being developed, the NASA contribution for succeeding years is
expected to be level and then be reduced as the transition is made from
development to operational deliverables. In the FY 2006 time period,
work to provide agricultural parameters for biomass energy crops is
planned to begin.

The initial emphasis with the partnership with the Department of Energy
(DOE) National Renewable Energy Laboratory (NREL), industry societies
(like the Electrical Power Research Institute (EPRI)) and private
companies will be to provide and test historical data parameters. These
collaborative partners are expected to pledge their own resources toward
the POWER initiative goals. The collaborative partner line item
represents an estimate of these types of contributions that will depend
upon the early successes of the project. Also, during this time the
Atmospheric Science Data Center (ASDC) will be become a partner for the
processing and internet access of the data sets. Lastly, the POWER
program also envisions soliciting and funding a limited number of
collaborations to increase core capabilities. Contracts will focus on
specific aspects of the parameter development problem in the Energy
industry and in the Energy Efficient Building sector and planned to
require nearly \$300,000.

In time, a growing emphasis will be placed upon aspects of the
predictive problems and the partnerships will expand their emphasis into
the incorporation of predictive parameters into their development tools.
To facilitate the predictive parameters the collaboration with NOAA and
other operational modelers becomes active to begin deriving and
verifying parameters predicted from model forecasts and assimilations.
This will begin in FY 2004 as data is supplied by NOAA, but the NOAA
contribution is expected to increase in labor and expenses. By FY 2008,
the NOAA collaboration should entail the labor of at least one full
person plus computing expenses. By this time, the NASA sponsored effort
will be used in the production of a series of forecasted prototype data
sets at a variety of forecasting periods. The prototype data sets for
the longest forecast periods (multi-year) are expected to be latest in
development as scientific and information technology advancements are
made.

##### Planned Milestones

The following general milestones are expected in the next 5 years:

1.  Energy Management Partnerships: The Energy Management Program
    through the POWER project expects to complete agreements with the
    Canadian government and NOAA. The program will begin working with an
    existing agreement with the USDA. The initial relationship with NREL
    will be expanded to include DOE. Opportunities to partner with DOD
    will also be pursued. An agreement with EPRI will be finalized.
    Other industry society partnerships will be pursued such as ASHRAE
    and AIA.

2.  Facilitate the collaboration and crosscuts within the NASA Earth
    Science and Applications divisions to enhance data source options.

3.  POWER SSE Releases 4-6: These enhanced versions of the web site will
    provide many more important solar and wind parameters and statistics
    not normally available to industry engineers at finer resolution and
    higher quality. Additionally, future releases will expand upon the
    direct linkage to other decision making tools in the renewable
    energy industry as demonstrated in Release 4.

4.  POWER Energy Efficient Buildings Data Set: This data set will be
    specifically designed for building engineers and architects who wish
    to use recent past and future weather conditions to reduce electric
    power costs and emissions. Solar energy parameters are included
    needed to compute the ambient light resources of the buildings
    areas. Wind, temperature and humidity information are now use to
    optimize the orientation of the building and its heating,
    air-conditioning, ventilation systems. The data set will be made
    compatible with existing industry design packages.

5.  POWER historic prototype data sets for Agriculture/Electric Power
    Load: In addition to the energy-efficient buildings data sets,
    prototype data sets will be developed with various partners to
    address needs in both the agriculture and in forecasting electric
    power load and supply. Electric Power load is forecasted through an
    existing tool that requires regional climate data as one of its
    inputs. A data set will be prepared to be ingested by this tool.

6.  POWER Short-term and mid-term forecasted prototype data sets:
    Knowledge of methods for deriving energy industry parameters from
    scientific data sets will be applied toward weather and climate
    forecasted fields. Prototype data sets from forecasted fields will
    be developed for both the renewable energy industry and
    energy-efficient building industry.

**References:**

Balcomb, J. D., and A. Curtner, 2000. "Designing Sustainable Buildings:
MCDM-23, A Tool for Making the Right Decisions." *Proceedings of Solar
2000, Solar Powers Life, Share the Energy*, June 16-21, Madison, WI,
American Solar Energy Society.

Gipe, Paul, 2000. "Wind Booms Worldwide: Latest BTM Report Paints a
Promising Picture." *Renewable Energy World*, 3(4):132-149.

Maycock, Paul, 2000. "The World PV Market 2000: Shifting from Subsidy to
'Fully Economic'?" *Renewable Energy World*, 3(4):58-75.

Rannels, James, 2000. "The DOE Office of Solar Energy Technologies
Vision for Advancing Solar Technologies in the New Millennium."
*Proceedings of Solar 2000, Solar Powers Life, Share the Energy*, June
16-21, Madison, WI, American Solar Energy Society.

**APPENDIX**

POWERBebefits809 8/09/02

**NASA/ESE/POWER PROJECT POTENTIAL BENEFITS AND UNCERTAINTIES**

**FROM 2002 THROUGH 2017**

Charles H. Whitlock and Paul W. Stackhouse, Jr.

c.h.whitlock@larc.nasa.gov and p.w.stackhouse@larc.nasa.gov

**EXECUTIVE SUMMARY**

This document provides the second analysis of benefits to the United
States energy industry if the proposed NASA Earth Science Enterprise
(ESE) Prediction Of World Energy Resources (POWER) project is activated.
The POWER project proposes to coordinate with various agencies, industry
associations, and companies to convert appropriate ESE radiation and
meteorology science data over the globe into industry-specific
parameters and formats for incorporation into industry and government
Decision Support Systems (DSS). **The ratio of** **energy-industry**
**benefits to** **anticipated NASA POWER** **costs** **is**
**approximately** **12,400:1** **for 2002 through 2017**. **Benefits**
**are** **approximately** **\$153 billion** in present-value Y2K dollars
for that period. **That value could be 50% too high** because some data
are either uncertain or unavailable. **The estimate also could be
hundreds of percent too low** because benefits to other industries and
the U.S. government (including the Department of Defense) are not yet
estimated.

**The POWER project follows a building-block strategy to maximize NASA
socioeconomic benefits to the energy industry.** Each phase is dependent
on some parameters from earlier phases as well as newer ESE science
results. Individual phases are directed at a particular segment of the
energy industry selected to maximize benefits based on ESE science data
availability during a particular time. Delaying a phase will eliminate
billions in benefits to the U.S. economy during the early 21st century.

**HISTORY**

Article 203 of the 1958 Space Act, as amended, requires NASA to enable
the fullest commercial use of space-derived technologies and science as
well as support Sections 5, 6, and 9 of the Solar Heating and Cooling
Demonstration Act of 1974. Many current technologies in the energy
industry are upgrades to historical research from NASA. Early NASA solar
panel and propeller research is the basis for todays more-efficient,
reliable, and cost-effective equipment in the renewable energy industry.
Advanced meteorology is now needed to enable reliable design of solar,
wind and other power-producing systems over the globe.

In 1995, the DOE National Renewable Energy Laboratory (NREL) contacted
the NASA Langley Research Center with a need for surface solar
radiation, cloud, and temperature information over the globe. Early ESE
Surface Radiation Budget (SRB) science data were furnished to NREL after
re-formatting the science data to NREL-defined parameters and format.
Potential industry users were directed by NREL to contact the NASA
Langley Research Center. Industry users noted that neither agency\'s
content nor format met every-day business needs. A number of new
industry parameters had to be created using unpublished ESE methods and
intermediate data not in public archives as a result of federal budget
limitations. In addition, NASA results needed to be tested relative to
standard industry procedures and data. Validation against more-recent
NASA ground site information was also very desirable.

In 1998, the NASA ESE program began sponsoring a 4-year activity to
develop a user-friendly, high-speed- delivery web site to provide
Surface Solar Energy (SSE) design parameters to both the energy industry
and the public. Small business and international energy industry
advisors provided advice on desired design parameters and definition of
a user-friendly format (see Partners list at \<
http://eosweb.larc.nasa.gov/sse\>). Data were made available to the
public as releases 2 then 3 at that web site. **In spite of the fact
that all design-parameter needs are not being met, the site has
experienced greater than 1 million hits, and 165,000 data documents have
been downloaded over 39 months of public availability.**

**RESULTS**

The following table presents results in terms of the particular
energy-industry segment targeted for that phase. **Phase 1** targets the
final portion of the solar and wind segment of the renewable energy
industry. **Details and assumptions are given in Appendix A**. **Phase
2** targets the buildings and architecture segment of the energy
industry. That segment is receiving a lot of attention because buildings
consume 65% of U.S. electricity and now are being constructed or
renovated at a rapid rate. **Appendix B provides details**. **Phase 3**
targets the biomass segment of the energy industry. This fuel is the
only method known that may displace as much as 1/3 of petroleum usage
during the 1st half of the 21st century (**Appendix C**). **Phase 4**
deals with the prediction of solar, wind, and biomass resources to
manage energy production and estimate consumption over future periods
from a few days to years-ahead (**Appendix D**). **Appendix E**
summarizes benefits for all phases.

**Table. Summary of POWER Program Benefits**

+--------+---------------+-----------------+-----+--------+----------+
| **[Ph  | **[Problem]{  | **[Solution     | **  |        | **[De    |
| ase]{. | .underline}** | ]{.underline}** | [Be |        | velopmen |
| underl |               |                 | nef |        | t]{.unde |
| ine}** |               |                 | its |        | rline}** |
|        |               |                 | ]{. |        |          |
|        |               |                 | und |        | **[Time  |
|        |               |                 | erl |        | Fram     |
|        |               |                 | ine |        | e]{.unde |
|        |               |                 | }** |        | rline}** |
+--------+---------------+-----------------+-----+--------+----------+
|        |               |                 | **  | *      |          |
|        |               |                 | 200 | *2002- |          |
|        |               |                 | 2** | 2017** |          |
+--------+---------------+-----------------+-----+--------+----------+
| 1\.    | Several solar | Provide new     | \$  | \$34.6 | F        |
| Rem    | & wind        | global values   | 250 | B      | Y02-FY03 |
| aining | parameters    | for diffuse,    | M   |        |          |
|        | are not yet   | direct beam,    |     |        |          |
| solar  | available for | and             |     |        |          |
| and    | the design of | tilted-surface  |     |        |          |
|        | more          | radiation       |     |        |          |
| wind   | efficient     | industry        |     |        |          |
| in     | renewable     | parameters.     |     |        |          |
| dustry | energy power  |                 |     |        |          |
|        | systems.      | Provide new     |     |        |          |
| needs  |               | diurnal wind    |     |        |          |
|        |               | speed and       |     |        |          |
|        |               | direction       |     |        |          |
|        |               | parameters for  |     |        |          |
|        |               | various types   |     |        |          |
|        |               | of vegetation.  |     |        |          |
+--------+---------------+-----------------+-----+--------+----------+
| 2\.    | Buildings use | Provide new     | \$0 | \$27.8 | F        |
| Bu     | 65% of        | illumination    |     | B      | Y03-FY07 |
| ilding | electricity   | and ASHRAE (1)  |     |        |          |
| and    | in the U.S.   | industry        |     |        |          |
| archit | Savings of    | parameters in   |     |        |          |
| ecture | 50% are now   | combination     |     |        |          |
| in     | possible at   | with selected   |     |        |          |
| dustry | no increase   | radiation,      |     |        |          |
|        | in            | wind, and       |     |        |          |
|        | construction  | meteorology     |     |        |          |
|        | costs if      | from Phase 1.   |     |        |          |
|        | certain       | Provide several |     |        |          |
|        | environmental | high-speed data |     |        |          |
|        | and           | delivery        |     |        |          |
|        | m             | methods for a   |     |        |          |
|        | eteorological | very wide range |     |        |          |
|        | parameters    | of users.       |     |        |          |
|        | are available |                 |     |        |          |
|        | during the    |                 |     |        |          |
|        | design phase. |                 |     |        |          |
+--------+---------------+-----------------+-----+--------+----------+
| 3\.    | Energy        | Provide new     | \$0 | \$70.6 | F        |
| B      | production    | rainfall and    |     | B      | Y05-FY10 |
| iomass | from selected | PAR (2)         |     |        |          |
| energy | biomass crops | parameters in   |     |        |          |
| fuel   | has the       | combination     |     |        |          |
|        | potential to  | with selected   |     |        |          |
|        | replace 37%   | radiation,      |     |        |          |
|        | of the        | wind, and       |     |        |          |
|        | world\'s 1998 | meteorology     |     |        |          |
|        | petroleum     | from Phases 1   |     |        |          |
|        | consumption.  | and 2. Develop  |     |        |          |
|        | New           | new weekly      |     |        |          |
|        | techniques of | high-speed data |     |        |          |
|        | monitoring    | delivery        |     |        |          |
|        | crops and     | methods for     |     |        |          |
|        | potential     | both the energy |     |        |          |
|        | supply need   | and agriculture |     |        |          |
|        | to be         | industries.     |     |        |          |
|        | developed.    |                 |     |        |          |
+--------+---------------+-----------------+-----+--------+----------+
| 4\.    | Predictions   | Integrate ESE   | \$0 | \$19.6 | F        |
| Energy | of            | POWER-developed |     | B      | Y08-FY13 |
| Re     | alternative   | methods for     |     |        |          |
| source | fuel          | energy-industry |     |        |          |
| Pred   | availability  | parameters from |     |        |          |
| iction | for the       | Phases 1, 2,    |     |        |          |
|        | production of | and 3 into      |     |        |          |
|        | energy and    | various         |     |        |          |
|        | probable      | government and  |     |        |          |
|        | consumption   | industry        |     |        |          |
|        | are becoming  | weather and     |     |        |          |
|        | more          | climate         |     |        |          |
|        | important as  | prediction      |     |        |          |
|        | fossil types  | programs.       |     |        |          |
|        | become less   |                 |     |        |          |
|        | available.    |                 |     |        |          |
+--------+---------------+-----------------+-----+--------+----------+

\(1\) American Society of Heating, Refrigerating, and Air-Conditioning
Engineers, Inc.

\(2\) Photosynthetically Available Radiation

**APPENDIX A-1**

**PHASE 1 - SOLAR AND WIND PORTIONS OF THE RENEWABLE ENERGY INDUSTRY**

(Includes Photovoltaic, Solar Thermal, and Wind Systems)

The wind-energy industry needs advanced and specialized wind data to be
derived from the Goddard Earth Observing System (GEOS) reanalysis data
to account for vegetation and minimize propeller-wake shadowing on wind
farms. New diffuse and direct-beam solar radiations are also planned
along with total solar radiation on tilted solar panels and
solar-concentrator 2-axis tracking systems. None of this new data will
be publicly available from any other organization in the foreseeable
future. Certain U.S. government agencies also have an interest in the
data for all locations of the globe. A Release 4 SSE web site is the
planned data delivery method. It is assumed that full funding for
development of this phase is available during FY03.

The cost of 10^6^ BTU of typical mixed energy types is \~\$13.50 in Y2K
nominal, non-inflation adjusted dollars (DOE Annual Energy Review 2000,
http://www.eia.doe.gov/emeu/aer/aerpdf.html), hereafter referred to as
DOE Y2K Annual Review. The basic unit of energy is 10^15^ BTU = 1 quad.
Therefore, 1 quad of energy cost \~\$13.50 x 10^9^. The DOE Y2K Annual
Review suggests that Y2K solar/wind portion of the renewable industry
size = 0.12 quad BTU = \$1.62 x 10^9^ for all types of U.S. consumption.

Natural Resources Canada (NRCan) has unofficially suggested that
POWER/SSE data benefits industry expansion and the resulting
displacement of petroleum-based energy. NASA data allows system design
in regions where environmental information is incomplete or does not
exist. Benefits are probably between 10% and 20% of renewable energy
values. We assume that SSE Release 3 benefits 10% of this U.S. industry
(\$.16 x 10^9^ in Y2K dollars). It is reasonable to assume that Release
4 with winds, direct normal radiation, and tilt-surface information in
combination with future ESE science updates will help maintain a benefit
of 10% of industry value well beyond 2003.

Various sectors of the renewable energy industry are expected to grow at
different rates ranging from 2.4% (solar thermal) to 3.7% (wind) to 19%
(photovoltaics) per year according to DOE\'s National Energy Modeling
System (NEMS) (from Macauley et al. Resources for the Future Discussion
Paper 02-05, February 2002, http://www.rff.org). If the above growth
rates are weighted in accordance with their respective production
magnitudes, an average growth rate of 4% is obtained for the combined
three systems over the period 2001 through 2020 because wind is the
largest producer of energy.

Macauley et al. note that NEMS has been criticized for its assumptions
concerning market penetration and other characteristics of its modeling
and forecasting approach. In particular, another DOE study (Osborn et
al., http://enduse.lbl.gov/Projects/NEMSwind.html) indicates that NEMS
wind industry growth may be as much as 53%/yr instead of 3.7%. NEMS is
clearly different than recent wind energy growth rates (\~40%/yr). If
wind were to grow at a 40% rate instead of 3.7%, the weighted-average
yearly growth rate for the combined solar thermal, photovoltaic, and
wind sectors would be slightly less than 40%.

Picking a middle range, growth of the combined solar and wind U.S.
renewable energy industry is assumed to be 25% in this analysis.
POWER/SSE benefits in constant Y2K dollars are estimated to be:

YEARLY BENEFITS FOR SOLAR AND WIND PART OF THE RENEWABLE ENERGY INDUSTRY

(10^9^ Y2K\$)

  ---- ---- --- --- ---- --- --- ---- ----- ---- ---- ---- ---- --- --- ----
                                                                        

                                                                        
  ---- ---- --- --- ---- --- --- ---- ----- ---- ---- ---- ---- --- --- ----

The values essentially amount to industry expansion resulting in savings
of petroleum-based energy costs.

**APPENDIX A-2**

**PHASE 2 - BUILDING/ ARCHITECTURE INDUSTRY**

Phase 2 requires new illumination parameters that enable improved
interior daylighting design. Also needed are certain new meteorological
parameters currently recommended by the American Society of Heating,
Refrigerating, and Air-Conditioning Engineers, Inc. (ASHRAE) for
construction and renovation of buildings. Wind as well as total,
diffuse, direct beam, and tilted-surface radiation will be taken from
the SOL/WIND phase 1 activity for nighttime ventilation cycle and
thermal design inputs. Data delivery may be more complex than a single
web site technique. There are reported to be over 100 different computer
programs for designing buildings. Some use monthly statistics, and
others use time-simulation procedures. Multiple distribution media may
be required. ASHRAE has 50,000 members and has expressed an interest in
distributing a portion of the data to its members. It is assumed that
full funding will be available for this phase from FY03 through FY07.

The DOE March 2001 Monthly Energy Review gives Y2K primary energy
consumption as 98.8 quads, an all time record. Residential and
commercial building energy consumption is 36.4% of primary consumption
or \$486 x 10^9^ in constant Y2K dollars. Commercial buildings are 45%
(\$219 x 10^9^) of that total (Environmental Building News, May 2001,
from 1995 Commercial Buildings Energy Consumption Survey, DOE).
Accounting for the number of buildings, average energy expenditures per
building were:

4.6 x 10^6^ commercial buildings average = \$48,000/yr

101.5 x 10^6^ residential buildings average = \$2,600/yr

(We ignore the residential segment of the building industry for the
remainder of this analysis because both industry and customers have
mixed small-scale time/cost/reliability incentives at this point in
time.)

New commercial buildings (170,000/yr) can have 50% reduced energy
requirements at no increase in construction costs (various DOE reports
and Environmental Building News, May 2001, from A Characterization of
Building-Related Construction and Demolition Debris in the United
States, EPA, 1998). Atmospheric data MUST be available for design of
daylighting, auxiliary renewable energy power on roofs, accounting for
winds, solar geometry, etc. Over 200 building-design software programs
are now available from various sources. Unfortunately, these design
programs often are not used to maximum advantage because neither the
building nor the architectural industries can easily obtain the
atmospheric data except at 239 major cities of the U.S. It is a major
problem when companies wish to bid on construction projects in foreign
countries, a significant segment of both the civilian and
government/military segments the industry.

It is reasonable to expect that a web-based buildings/architectural data
source would experience the same type of success as the renewable energy
NASA/ESE/SSE web site enjoyed. There are 10 to 20 times more potential
users for buildings/architectural data than there are renewable energy
industry users. For many users and potential construction sites, this
would be the only near-complete data available. A 20% impact on the new
construction industry may be reasonable.

It is expected that a prototype NASA/ESE/POWER buildings/architectural
web site would be available for industry testing by mid-FY 2004 with a
final version in mid-FY 2006. By that time, industry usage should be
such that benefits should be around 10% of new commercial building
construction.

New commercial construction is (170,000/4,600,000) = \~3.7%/yr of the
existing number of commercial buildings. Using conventional technology,
energy consumption would increase by \$8.1 x 10^9^ per year from new
building construction. We assume no expansion in the new buildings
industry within the U.S. relative to constant Y2K dollars. (That is not
the situation over the globe where U.S. companies are participating.)
Assuming a 20% impact on U.S. new building construction energy growth,
benefits are as follows:

YEARLY BENEFITS TO THE NEW-CONSTRUCTION ARCHITECTURE/BUILDING INDUSTRY

(10^9^ Y2K\$)

  ---- --- ---- --- ----- ---- ---- ----- ---- ---- --- ---- --- --- --- ----
                                                                         

                                                                         
  ---- --- ---- --- ----- ---- ---- ----- ---- ---- --- ---- --- --- --- ----

The above benefits do not include benefits to be obtained from
renovated-building construction. Assuming major renovation every 25
years, the average number of renovation buildings per year is
(4,600,000/25) = 184,000. The amount of energy used in these renovated
buildings is (184,000/4,600,000) x (\$219 x 10^9^) = \$8.76 x 10^9^.
Existing construction will severely restrict the application of new
technologies in many cases. We assume 5% impact on renovation
construction energy growth in the commercial buildings/architectural
industry.

YEARLY BENEFITS TO THE RENOVATION-CONSTRUCTION ARCHITECTURE/BUILDING
INDUSTRY

(10^9^ Y2K\$)

  ---- --- ---- --- ----- ---- ---- ----- ---- ---- --- ---- --- --- --- ----
                                                                         

                                                                         
  ---- --- ---- --- ----- ---- ---- ----- ---- ---- --- ---- --- --- --- ----

These values also essentially amount to savings in petroleum-based
energy costs. Combined new- and

renovation-construction benefit estimates are as follows:

COMBINED BENEFITS FOR BOTH NEW AND RENOVATION CONSTRUCTION

(10^9^ Y2K\$)

  ---- --- ---- --- ----- ---- ---- ----- ---- ---- --- ---- --- --- --- ----
                                                                         

                                                                         
  ---- --- ---- --- ----- ---- ---- ----- ---- ---- --- ---- --- --- --- ----

**APPENDIX A-3**

**PHASE 3 - BIOMASS ENERGY**

Phase 3 focuses on agricultural parameters needed to predict the
availability of biomass crops that are needed for producing energy from
biomass power plants. Key new parameters are rainfall actually hitting
the ground, Photosynthetically Available Radiation (PAR), and various
parameters needed to predict crop disease and pest onset conditions
around the world. Total, diffuse, and beam radiation; wind; and
temperature/humidity data will be taken from Phases 1 and 2 for
calculation of evapotranspiration parameters. Data delivery techniques
have not yet been decided, however, limited discussions with a few
precision agriculture farmers indicate that weekly historical data is
probably desirable. It is assumed that full funding will be available
beginning FY05 through FY10 for development of this phase.

The DOE Y2K Annual Review indicates that the U.S. biomass energy
industry in Y2K was about 3.3 quad or \$44.6 x 10^9^ in size. DOE
projections published in SOLAR TODAY (June/July, 1997) indicate that the
industry growth rate is expected to average about 50%/yr through 2020.
New crop species and processing technologies are expected lower the
price of ethanol to 30% of present values, greatly increasing market
penetration (Renewable ENERGY World, May-June, 2000). In the very long
term, global bioethanol energy is expected to equal 37% of the world\'s
1998 petroleum consumption. It should be noted that the Resources for
the Future Discussion Paper 02-05 (Macauley et al.) indicates that the
DOE NEMS model shows only 2.9%/yr market growth for electrical energy
generation. Major biomass energy consumption includes several
industries, (transportation, chemical manufacturing, electrical energy
and heating), however. It should be noted that DOE has recently created
a new center for biomass energy research.

Much of the U.S. biomass industry is regional to reduce transportation
costs of the fuel from the farm to the processing plant. In the future,
fuel supply will probably be international in nature because of growing
season limitations in most regions. The U.S. will probably be a major
supplier to some other regions of the globe.

Near-real-time hindcasts and forecasts on a weekly basis would give
individual growers information on crop progress and alert to the
possibility of pest/disease outbreak. Most important, it would allow
estimates of the time of harvest or be one DECISION TOOL for abandoning
the crop to make the land available for other alternatives. Such
capabilities would allow energy producers and trading markets
information for assessment of fuel supply from another global region
during the non-growth season at a particular processing plant. These
same capabilities would aid the U.S. food industry.

The agricultural community has many predictive services available to it
now. Our information is that none of the present services are as easy to
obtain or of the same type (global multi-parameter) as proposed by the
POWER project. In the long term, the NASA site would be turned over to
NOAA, USDA, DOE, or an industry association or company for operation.

We are not able to estimate market penetration at the present time. For
purposes of this preliminary analysis, we make a baseline assumption
that energy resource planning activities will have 1% impact on the
biomass market under usual operating conditions. Benefits of energy
prediction will not begin until 2008. We assume that biomass energy
consumption will expand at a 25%/yr rate, between the two DOE estimates.
Benefits under these assumptions are:

YEARLY BENEFITS TO BIOMASS ENERGY INDUSTRY

(10^9^ Y2K\$)

  --- --- ---- --- ---- ---- ----- ----- ---- --- ---- --- --- ---- ---- ----
                                                                         

                                                                         
  --- --- ---- --- ---- ---- ----- ----- ---- --- ---- --- --- ---- ---- ----

**APPENDIX A-4**

**PHASE 4 - ENERGY RESOURCE PREDICTION**

Phase 4 deals with the prediction of various radiations, illumination,
near-surface wind, rainfall, and ASHRAE parameters such that various
industry and government decision support centers can predict energy
production and consumption over future periods from a few days to years
ahead. Radiation, rain, and wind influence biomass growth and the
ultimate prediction of how much power may be available for the next day,
week, or month from that source. Detailed near-surface wind information
is needed for the prediction of intermittent wind energy to be available
from large wind farms as well as for the ventilation and cooling of
buildings. ASHRAE-type environmental parameters and illumination are
required to assess future heating, cooling, and electricity requirements
in buildings. NASA-developed techniques for these parameters in phases
1, 2, and 3 will need to be integrated with various government and
industry weather and climate prediction software programs. Joint
validation of the new results will be required. It is assumed that full
funding for this phase will be available for beginning FY08 through
FY10.

In Y2K, the total U.S. energy supply was 102.6 quads worth \~\$1385 x
10^9^. The breakdown was:

Crude Oil 36.0%

Natural Gas 27.2%

Coal 22.4%

Nuclear 7.8%

Renewables 6.6% includes:

> biomass 3.3%
>
> hydro 2.84%
>
> geothermal 0.34%
>
> solar thermal 0.066%
>
> wind 0.050%
>
> solar PV 0.004%

Energy planning using weather and climate data influences selected
segments of both the supply and consumption sides of the industry. On
the supply side, only renewable sources (6.82 quad) are influenced.
Weather and climate influences use of fossil fuels, nuclear electric
power, and renewable energy (98.7 quad total) on the consumption side.
POWER weather and climate will influence 105.52 quads of energy flow
that amounts to about \$1424.5 x 10^9^ in constant Y2K currency.

Benefits of predictive information will differ in each of the energy
sectors. Impacts will probably be as high as 20% in some renewables, but
be very low in some consumption areas such as manufacturing. Penetration
will be strongly dependent on the reliability and accuracy of the
predictive methods. Benefits will magnify significantly if unexpected
crisis situations develop.

We make the conservative assumption that energy resource planning
activities will have 1% impact on the combined energy market under usual
operating conditions. Benefits of energy prediction will not begin until
2008. We assume that energy consumption will continue to expand at a
5%/yr rate similar to the 1990 to 2000 period. Benefits under these
assumptions are:

YEARLY BENEFITS OF NASA/POWER ENERGY RESOURCE PLANNING

(10^9^ Y2K\$)

  ---- --- ---- --- --- --- ---- ---- ---- --- ---- ---- ---- ---- ---- ----
                                                                        

                                                                        
  ---- --- ---- --- --- --- ---- ---- ---- --- ---- ---- ---- ---- ---- ----

The above values are very preliminary and should be updated when more
complete information can be obtained.

**APPENDIX A-5**

**SUMMARY OF BENEFITS**

YEARLY SUMMARY OF BENEFITS FOR ALL PHASES OF THE POWER PROJECT

(10^9^Y2K\$)

  ---- --- ---- --- --- --- --- ---- ---- ---- ---- ---- ---- ---- ---- ----
                                                                        

                                                                        
  ---- --- ---- --- --- --- --- ---- ---- ---- ---- ---- ---- ---- ---- ----

YEARLY RATIO OF BENEFITS TO NASA COST

(10^3^)

  ---- --- ---- --- --- --- --- ---- ---- ---- ---- ---- ---- ---- ---- ----
                                                                        

                                                                        
  ---- --- ---- --- --- --- --- ---- ---- ---- ---- ---- ---- ---- ---- ----

NOTE: Years 2014, 2015, 2016, and 2017 assume only \$100K of NASA cost
to maintain communications with organizations using the POWER data in
their decision tools. Benefit to cost ratios are very high for those
years.

16-YEAR SUMMARY OF BENEFITS AND COSTS

\* Benefits for the period = \~\$153 Billion.

\* NASA POWER project costs are assumed to be \~\$12 Million for the
period.

\* Total benefits/NASA cost ratio for the POWER project = \~12,400:1