Development of transformer load management at the Modesto irrigation district

The Modesto Irrigation District believes the economic paybacks in advanced informational technology are of critical importance, especially towards making operational assessments and decisions within the electric utility industry. This paper and the corresponding presentation will emphasis the application of electrical engineering principles and custom GIS (geographic information systems) development required for development of a practicable transformer load management application.

Modesto Irrigation District Background
The irrigation district lies in California’s Central Valley, south of Sacramento and east of San Francisco. The district is a public utility providing electric and irrigation service to the city of Modesto and surrounding communities. The bulk of the district’s 90,000 electric power customer accounts are residential, followed by light commercial, irrigation, and large commercial power consumers. Population of these customer sets is similar in some ways to other electric utilities of similar size, but in other ways differs significantly. Agricultural pumping for irrigation customers reflects a broad range of electric demand requirements, while large commercial operations process agricultural products on a sharply defined seasonal basis. These commercial operations include caning operations for vegetable and fruit products, as well as large wine bottling facilities.

Project Background
The Modesto Irrigation District’s current GIS project is an implementation of Smallworld GIS utilizing a custom electric and irrigation data model, along with a broad range of applications serving those sectors. The system is currently operational in a production environment, though new data modeling and application development continues through the present. One of the new applications in development is the transformer load management system.

Electric transformers in the district are modeled as both underground and overhead equipment arrays. Data fields on the transformer objects in the system capture a wide range of information, including:

Phase configuration,
Kva load rating
Location and equipment identifier numbers,
Part numbers,
Ownership
Map-grid-sequence number identifiers.

Transformer load management concerns itself with assessing, based on the customer types, typical load profiles for customer sets, number of customers and electric power demand history, the relative load demands placed on current and possible transformers in the system. An intelligent transformer load management application needs to accomplish three central goals.

First it allow for field validation of the transformer to customer link.
Secondly it must provide loading analysis that takes into account environmental and equipment factors, as well as statistically determined load profiles.
Finally, it must allow for an efficient yet complete reporting of the resulting load analysis.

The Modesto Irrigation District (MID) chose to pursue completion of these goals by developing the necessary data model and code within their electric GIS. Additionally, because the required customer and meter read data reside in a separate Oracle database at MID, the application had to be built with the ability to capture and process customer data stored externally from the GIS. The relationship between customer (and therefore load) data and the transformer object data stored in the Modesto GIS is implied rather than explicit; no data join relationships exists between transformers and customer objects within the data model. Retrieval of the correct customer load read records from the Oracle database is achieved by referencing map-grid transformer identification numbers, a unique point of commonality that exists in both the GIS and customer information system data stores.

Once retrieved the customer information system data is pre-processed and stored in the GIS database. This duplication of data may seem inefficient on first examination. However, there are a number of good reasons for the approach. On a pragmatic level, by replicating data into the GIS, the transformer load management application can now be downloaded to a laptop computer and be used in the field to verify customer-transformer ties and also by a trouble-shooter when investigating power quality issues and transformer failures. Additionally, it was our experience that performance of the transformer load management analysis was significantly enhanced by translating the data and storing it internally on the GIS. Finally, given the large amount of processing required to use the customer information system data for meaningful analysis, it made sense to store the results of that analysis, thus speeding repeated transformer load management on already processed transformers.