IEEE Power & Energy Magazine - January/February 2016 - 50

The common information model-based standards are aimed at improved
model quality, reduced net labor requirements, and a systematization of
data that can support the ever-smarter grid of the future.
The CIM Approach
a power grid is an enormous, complex, interconnected
machine that we all depend on to deliver power reliably; at
the same time, societal values and concerns drive policies
such as deregulation, open markets, energy diversity, carbon reduction, emission control, and the like. implementation of these policies requires sophisticated automation, and
an increasingly critical part of this automation is based on
mathematical modeling of the grid as a whole system. this
holistic analysis is necessary because a power grid is made
up of millions of parts that are bound together in instantaneous interdependence by the physics of electricity, and no
decision can be taken about one part without some impact
on the rest.
the business processes that analyze the grid are complex
because of the need to simulate the physics of electricity on
a very large scale and because ownership of and operating
responsibility for the grid is distributed among many participating grid entities. the eastern interconnection in North
america, for example, stretches from the atlantic coast to
the rocky Mountains and is made up of grid parts owned by
hundreds of different utilities, plus participating generators
and consumers of many types. it is divided into a hierarchical arrangement of planning and operating entities with
a variety of different responsibilities. in carrying out these
responsibilities, each entity must assemble accurate models tailored to a variety of specific purposes. each model
is huge-millions of individual datum must be accurately
assembled in order for each analysis to be accurate. Much of
the analysis is "real-time," meaning that models of present
system operations must be assembled and solved within tight
time limits.
the size of models coupled with changing power grid
conditions would, alone, make maintaining accurate models
a significant challenge. but added to this, the data required
to produce models for any given analysis always come from
multiple organizational sources. behind each analysis, therefore, lies a complex information management process that
involves participation by many entities in order to maintain
the model required for each particular purpose.
because of the number of different departments and
corporate entities involved, standards for exchange of network information are necessary, and developing these standards has been a focus of iec's ciM work for some time.
but interoperability requirements go far beyond the ability to exchange and then process data from many sources.
Most current modeling processes have far too many manual
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steps-too many points of data entry, too many manual
checks, too many partially automated data transformations.
From its inception, a central objective of the iec ciM has
been to reduce the amount of time senior power-system engineers (a scarce commodity!) need to spend doing manual
data management that could be automated.
the key to reducing labor (while simultaneously increasing network model quality) is to assure that the various elements of information coming from multiple different sources
will fit together into a meaningful whole without manual
intervention-and so can be assembled into all the different
kinds of models that are needed. Metaphorically, what practitioners need is a versatile and reliable building block data
architecture, and this is what the iec ciM has developed,
in addition to a format for exchanging the building blocks.
the ciM approach to network models is to design modular data such that each logical part of the overall data can
be supplied from its natural source and reliably plugged
together with parts from other sources to make all of the different kinds of analytical models required in today's grid. in
the rest of this article, we outline the architecture behind the
ciM network building blocks and report on the current state
of its development and deployment.

Problem Description
broadly speaking, the ciM goal for network modeling is to
define network analysis data in terms of building blocks-
let's call them "model parts"-that satisfy the following two
requirements:
1) each model part is designed to fit into a 'model framework' that allows model parts to be 'composed' to
form the required input data for all of the kinds of
network analysis that are required.
2) each model part has one natural source that could be
assigned responsibility for the quality and availability
of the model part. call this party the "model authority."
the first requirement expresses the basic goal: all types of
cases can be constructed straightforwardly by putting together
the right selection of building blocks. the second requirement
is basic information-management wisdom. it is always desirable to have a single well-known original source for each
datum. this reduces the chance of conflicting data and provides natural points of quality control. (Note that this does
not mean that all data come from one source; it only means
that each datum has a single source.)
any given network component will be represented in
many thousands of analytical cases. the ciM started with a
january/february 2016

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - January/February 2016