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| Case Study |
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Load Research solution helps large utility company improve
energy conservation and management |
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Patni leveraged its expertise in the domain of Energy & Utilities to redesign Load Survey System (LSS) -
a mainframe computer application for a large utility company in California.
The Client
The client is one of the largest
electric utilities in the U.S.
serving more than 4 million
business and homes, spread over
a 50,000 square mile service
area across coastal, central, and
Southern California. The utility's
system consists of more than
10,000 circuit miles of
transmission lines and about
100,000 circuit miles of
distribution lines.
The Challenge
Dedicated to the cause of customer leadership, the client has always been on
the forefront of providing quality services across all customer segments. Load
research formed the foundation of its customer services. For the last 20 years,
the company had been using Load survey system (LSS) - an IBM mainframe
based legacy application to handle the load research in its traditional form.
Over the years as the organization grew, it witnessed an increase in the
number of user groups. The pattern of usage changed and rate structures
became complex. The conventional role and function of load research was
expanding to serve multiple user groups with complex rate designs. Hence,
deeper and more accurate ways of analyses were required.
The competition and market forces demanded higher levels of services. As the
company endeavored to enhance its operations, the limitations of the legacy
system posed challenges. Some of the major challenges facing the company
were:
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Alignment of LSS with the changing business requirements |
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Inadequate front-end usability of Legacy LSS |
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Absence of processing of historical data |
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Increased cost of application maintenance |
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Limited capabilities of technology and architecture |
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Absence of interoperability with other systems. |
Integration of LSS systems with other systems such as customer data
acquisition system (CDAS), customer service system (CSS), real-time energy
metering system (RTEM), and billing system was necessary to analyze load
data, for load forecasting, demand side management, cost-of-service studies,
and system planning. The data inconsistency across systems posed a problem
for a seamless integration. Keeping the databases in sync was a manual effort,
and subject to human error. Moreover, the LSS was not fully compatible with
new-generation meters. The client therefore, wanted to replace this system
with an application that would be more contemporary in catering to the
requirements.
The Solution
Patni carried out an assessment of the existing LSS system and the
subsystems involved. It advised the migration of the CICS/COBOL-based
LSS to the .NET environment in order to overcome all technology and
architecture related limitations. Thus, a new Load Research System (LRS)
with modern GUI and Web interface was developed. It offered the agility
to incorporate the changing business requirements. LRS was integrated
with the existing CDAS and CSS system using a middleware. The online
system provided the facility to add new accounts or modify existing
accounts for load research. LRS also placed no limitations on number of
channels, meters, or interval data.
The new system had the capability to manage historical load research
data that enabled information extraction to aid forecasting, planning
monitoring and trend analysis in the short term as well as policymaking
and tariff determination in the long term to gain a competitive edge.
The Technology
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Platform: IBM Mainframe,
UNIX (Shell scripts) |
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Operating System: MVS,
AIX, Windows |
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Language: Cobol, CICS,
JCL, C |
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Database: Db2, VSAM |
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Web: ASP.NET |
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Middleware: IBM MQ
Series |
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Client Server: SQL Server |
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The Benefits
The LRS solution brought in significant improvement in the
client's system planning activities, cost of service studies and in
determining the effectiveness of various conservation and
management programs. It also showed a marked reduction in
processing costs and time.
The new system helped in reducing the post-implementation
bottlenecks and time to go-live. Benefits to the client included:
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Real-time Interval data for Dynamic Load Profiling |
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Increased accuracy in estimating demand due to analysis of
data spread across a larger interval of time |
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Ability to serve multiple user groups with complex rate
designs |
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Storage of Interval data in Engineering Units for ISO
Reporting & analysis. |
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