Using a distrubution management system to improve asset management

Using a distrubution management system to improve asset management

Hahn Tram
SchlumbergerSema 6399 South Fiddler’s Green Circle,
Suite 600 Greenwood Village, CO 80111

Abstract
Most utilities implement a Distribution Management System (DMS) to increase service reliability, improve customer responses, reduce operational costs (mostly labor), and meet regulatory requirements. This paper focuses on increasing the utilization and return on investments of DMS by extending its applications to reduce the lifecycle costs of distribution network assets. DMS technologies, consisting of Distribution Supervisory Control And Data Acquisition (SCADA), applications for control room and dispatch operations, outage management, etc., are commonly available today. This paper does not propose any enhancements to these existing products. Rather, it presents a business process model to extend the benefits of existing DMS applications to collect business metrics for Enterprise Asset Management, reduce inspection and maintenance costs, and enable value-based system planning and engineering to minimize capital project requirements.

The expanding DMS business objectives The drivers and business case for a DMS have shifted and expanded over the years since DMSs or Outage Management Systems (OMSs) became commercially available around 1990:

Early to Mid 1990s – DMS was designed and implemented to meet regulatory requirements, improve service reliability, and increase operational efficiency. The focus was particularly on meeting regulatory requirements and improved outage durations.
Late 1990s – Adding to the earlier objectives, DMS was intended to increase operational efficiency, improve communications both internally within the utility and externally with customers and the public, and enable value-added services, such as customer callback and performance-based rates. The focus was increasingly on operating efficiency and communication improvements [Tram and Engelken, 2000].
Today's Focus –Utilities are beginning to extend the business value of DMS investments to support Enterprise Asset Management (EAM) for increased asset utilizations and financial return on assets. They also aim to increase the effectiveness of DMS in daily operations by leveraging the asset registries in EAM to further increase the aforementioned DMS business benefits. Such focus is the subject of this paper.

Enterprise asset management
The EAM discipline is aimed at increasing the return on asset investments by reducing the total costs of asset ownership and by increasing asset utilizations. Before exploring how DMS can benefit EAM and vice versa, this section provides a quick overview of EAM—its business model, drivers, and core processes—to ensure that the two systems and process models are aligned.

The EAM Business Model
The EAM business model has three main entities (by functions if not by organization units):

Asset Owner – The asset owner sets investment levels, determines the desired internal rate of return, defines the acceptable risk profiles, and manages the regulatory relations.
Asset Manager – The asset manager is responsible for the effectiveness of the asset investments, deciding what work to perform on the assets and where and when.
Service Provider – The service provider is responsible for timely and efficient work execution and for resourcing and scheduling the jobs within the budget and time allotted.

EAM is about improving the effectiveness of the asset manager. Note that the service provider functions may be outsourced to another company in some utilities. Likewise, some utilities may act as the asset manager for energy delivery assets that other companies own. This point is important in designing EAM integration architecture.

The Asset Management Paradigm
Now that the race to e-everything and diversify has slowed, many utilities’ focus and information technology strategies are returning to the utility core business—running the energy delivery system. As they have prepared for deregulation and competition over the last decade, utilities have emphasized and generally achieved good gains in labor efficiency and customer services. The next plateau in business performance is managing the energy delivery assets more effectively, not just more efficiently [Tram, 2002].

Observations such as the following have indeed directed many utility executives to take a fresh look at the way their assets are used and managed:

At the end of 2000, the top 100 electric utilities in North America had T&D assets valued at $285 billion [source EEI].
From 1991 to 2000, these utilities invested an average of $6.1 billion per year in new assets [source PowerDat].
These investments earned less than half of what the Standard and Poors (S&P) 500 companies earned [source TK Consulting].

Also fueling the utility interests in EAM today and in the foreseeable future are the following factors: more limited capital due to lower market caps, an aging workforce, aging assets, tighter capacity constraints, and a more constrained regulatory environment (e.g., frozen rates).

Core EAM Processes
EAM lowers the overall cost of services while maintaining service quality by effectively planning and managing the assets through their lifecycles (see Figure 1):

Improve asset performance and increased work effectiveness through the assets’ lifecycles, from investment and project planning, engineering and design, construction, and Operations and Maintenance (O&M), to repair and replacement.
Increase asset utilization by prioritizing and planning capital projects, including quantified risks in service reliability and quality.

Figure 1 – Major EAM Processes. Integrating with DMS involves leveraging the asset repository to improve network operations and work effectiveness and collecting valuable EAM data in distribution operations.

Plan Asset Investments – The key is to take a system approach to prioritize capital projects, optimizing asset utilization and values systemwide rather than project by project. The utility should also attempt to quantify the risk of proceeding with a project.

Plan and Manage Work – The question to address is whether certain work must be performed based on its potential benefits or risks, not just how it can be completed efficiently. An example of this process is Reliability Centered Maintenance (RCM), which develops maintenance programs based on its reliability impact versus cost, rather than based on fixed schedules “by the book.”
Manage Asset and Work Standards – The utility should review its engineering standards, many of which have not been updated for years, for alignment with the EAM strategy, establishing standards and processes that are business valuebased in addition to engineering criteria-based.
Operate Assets and Perform Work – These core processes execute the plan and design developed in the above core processes. Just as importantly, the execution processes should support the asset, work, and standards registries (or data warehouse), which provide critical information for the planning and design processes. The following sections focus on using DMS in this context.

DMS - EAM Process Integration
Figure 2 shows an established DMS integrated process model, where using DMS spans multiple functional organizations of the utility [Tram, 1999].

Figure 2 – DMS Integrated Process Model. Processes that can leverage the EAM data repositories or can support the EAM registries are highlighted.
Table 1 describes the DMS processes that are needed to support EAM or that can leverage EAM information to improve their effectiveness. Table 1 – DMS Processes. DMS processes are particularly relevant to EAM’s success.

Figure 3 illustrates an example of how combining data from DMS on reliability performance and data from marketing on customer expectations may be used to influence O&M planning strategies. Similarly, the incremental cost of improving the energy delivery network form distrubution management and planning systems may be combined with distribution load forecasts to drive asset investment strategis.

Figure 3 – Valued-Based Asset Planning. The two simple examples illustrate how the EAM and DMS/OMS information can be useful to EAM decisionmaking.

DMS In The Overall EAM Strategy

EAM requires more functionality than conventional construction work management, I&M, and Mobile Workforce Management (MWM) applications. It is also more than just RCM. The core of the architecture is a data warehouse that contains operational and performance data repositories for asset, work, and standards. The data warehouse provides analytical applications with business intelligence (e.g., energy and resource demand forecasting), reports, dashboards, automated notifications, etc., for supporting asset management decisionmaking.

All the factors mentioned in the examples illustrated in Figure 3—customer expectations of service reliability, reliability performance, load growth, and incremental costs of upgrading the energy delivery network—vary from one geographic location to another. Hence, the geospatial reference of the DMS and EAM data registries is essential. This point is important as the utility designs its EAM strategy and the DMS integration with that strategy.

Enterprise integration of information systems and technology must align with the utility’s business objectives so that all expected or “designed” business benefits can be realized.

Table 2 looks at the systems with which DMS can potentially interface and the expected benefits of designing each interface in the DMS integration plan. Because the basic system interfaces for network model and customer information [Hatfield and Tram, 2000] are assumed to be available, the table does not include them.

Table 2 – DMS System Integration Plan. The integration architecture must align with the utility's business drivers to capture maximum benefits from the DMS investments. Integrating with EAM should be part of this alignment.

The most important interfaces that will benefit the EAM strategy are a geospatially referenced asset registry and the distribution planning application. In addition, interfaces between DMS and real-time data systems such as SCADA and MWM facilitate collecting asset operation and performance data for the asset registry without overbearing the operation center and field personnel.

References
Hatfield, M. and Tram, H., 2000, “Data for DMS/OMS – How Much Is Enough and Where to Get It,” Utility Automation, September 2000.

Tram, H., 1999, “The Smart Way to Deliver Energy,” Utilities IT, July/August 1999.

Tram, H. and Engelken, L., 2000, “Improving Service Reliability in the Deregulated Environment,” GITA Conference, March 2000.

Tram, H, 2002, “Enterprise Integration for Increasing Returns on Assets,” EUCI Conference on Breakthrough Asset Management for the Restructured Power Industry, October 2002.