Advanced Computational and Modeling Research for the Electric Power System

siberiaskeinData Management

Nov 20, 2013 (3 years and 11 months ago)

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Advanced Computational and Modeling Research for the Electric Power System

Funding Opportunity Number: DE
-
FOA
-
0000729

Topic Areas of Interest


The purpose of this FOA is to apply the advancements in basic research in mathematics and computation,
developed

under programs such as ASCR or internally at universities, national laboratories, and the
private sector, to improve the performance and capability of power system software tools and/or operator
platforms, for the benefit of enhanced system reliability an
d flexibility. The effort will foster the
establishment of an OPEN collaboration of researchers and industry to study cross
-
cutting computational
needs of broad mutual interest to the electric industry; to work collectively (drawing on a variety of
discip
lines and world
-
class expertise) to develop and validate solutions that are relevant and effective at
addressing actual operational and/or planning concerns; and to reach outside the collaboration to engage
and to share this knowledge with other interested

stakeholders.


Applications are sought in two Topic areas of power system research:

A) Data Methodologies; and

B) Dynamic Simulation Tools and Measurement
-
Based Control.


Topic A: Data Methodologies


One of the characteristics of the smart grid is en
hanced system visibility and understanding, achieved
through a wide variety of sensor measurements, i.e. data sources. However, this large volume (and
variety) of data, as well as associated latency, poses its own challenges. Thousands of data points mus
t be
acquired, shared, and processed (often in real
-
time).


Examples of computational research related to data for the power grid include (but

are

not limited to) the
following:



The way data is collected, used, stored, and archived (i.e. data architecture)

to improve
applicability for real
-
time operations and off
-
line planning studies;



The way data is communicated so that the right data is moved to the right application, which
could be spread over many substations and control centers, within the required la
tency;



Application of filtering and other techniques to improve suitability for models and software tools
(including wide area control and protection) by characterizing uncertainty, addressing
inconsistencies in data streams, and dynamically identifying on
ly the data relevant to current
decision needs, thus enhancing the data/application relationship;



Data mining/analysis, visualization, and discovery.


In addition, developing and deploying mechanisms to increase operational flexibility will require sharing

and fusion of data across a variety of models that can capture system dynamics and interdependencies,
typically absent in the isolated, static, steady
-
state approaches prevalent today. Thus, there is a need to
develop methodologies that address data/mode
ling seams that are present within geographic and
jurisdictional

areas; across the electric system (i.e., generation, transmission, and distribution); and
between markets, operations and planning.


Data methodologies must be informed by and validated on ac
tual power system data, e.g. real
-
time data
streams provided by utility partners. Proposed projects must develop and provide (for use by other
researchers) a set of appropriate, “real” data test cases so that researchers outside the project can validate
t
he methodologies. The FOA

is NOT intended to build
-
out electricity infrastructure, such as widespread
placement of PMUs, smart meters, or other sensor technologies.