Development of transformer load management at the Modesto irrigation district
Benefits of Transformer Load Management
Typical MID Load Patterns
The industrial customers differ from those found in many utilities in that they are nontypically
seasonal in their loading; most of these customers are agricultural-industrial in nature,
including processing, canning, bottling facilities and the like. TLM analysis in the district takes this
into account with modification factors specific to these customers.
Normal climactic seasonal variation occurs as one would expect. Peak loading occurs late
summer with high residential air conditioning use.
One requirement for the development of an effective GIS based transformer load
management application was the determination of typical load profiles and factors for typical
customer sets within the irrigation district. Load research was undertaken to provide diurnal
(hourly) load shape information. This load research effort performed extensive sampling of the four
classes of customer represented within the district, including residential, small commercial, large
commercial, industrial and irrigation. Statistical sampling was necessary because it was cost
prohibitive to do an actual load analysis of all customers in the district. The sampling of these
customer sets was performed using statistically valid stratified subsets across the district. Data
types collected by the study varied by customer type. The energy consumption for residential and
small commercial customers was sampled at 15-minute intervals over 31day intervals. Irrigation
customers were sampled for kWh and rated horsepower of water pumps. Large commercial
customers were sampled for kW. The final load factors determined thus take into account these
typical, seasonal load shapes.
Why Transformer Load Management
By developing the transformer load management application, the irrigation district seeks to
use their GIS for realizing direct equipment, labor and materials efficiency. The cost of electric
transformers can be viewed as a function of load capacity over time, and the resulting effect on
equipment life span. An under loaded transformer is a capital loss; the same transformer could be
used to serve higher customer concentrations and therefore make for better utilization of that
particular piece of equipment. Alternatively, an overloaded transformer would be expected to have
a shorter usable equipment life. By providing transformer load management within the context of
the GIS an operator will be able to make more intelligent decisions regarding the continuing use of
certain transformers in certain situations. Decisions might then be made to switch out a particular
transformer for a higher or lower load capacity unit.
The transformer load management system also has the ability to allow a designer or
operator to test hypothetical load situations. For example, customer load expansion might be
planned for an existing transformer location. A designer, using the transformer load management
application could begin by examining the current and historical loads occurring on a transformer.
Then, the operator may add any number of "new" customers onto the transformer, basing the
hypothetical kWh consumption on that typically seen within the neighborhood, on any other
amount determined suitable for the analysis. This additional hypothetical customer loading is added
to the transformer load management analysis at run-time in an interactive process using GUIs built
specifically for this task. No artificial data is added permanently to the GIS or Oracle customer
information system database. The resulting load analysis would allow the designer/operator to
make a more informed decision concerning where new load can be reasonably added, and when
new transformer capacity must be included in the design.
Conversely, customers may be removed from a transformer for the purpose of analyzing
how that change would effect the monthly loading. Again, this change would be achieved at runtime
through an interactive design process. No actual changes to either the GIS or customer
information system data would be realized.
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