by John D. McDonald, IEEE
As utilities begin to harness big data in earnest, they will begin to realize value in many forms. Greater productivity and efficiencies will be gained in several areas between generation and end use.
On the distribution system in particular, simply reporting, analyzing and presenting the health of major assets in real time and historical trends will help rationalize operations and maintenance work while informing a well-prioritized capital investment plan. We call this condition-based asset management.
Utilities will benefit in myriad ways from having condition-based, factual insights into the health of their sprawling assets. First, this approach increases safety, reliability and affordability–the pillars of regulated utilities’ obligation to the public and factors that increase customer satisfaction and aid economic development.
And as regulators more closely scrutinize grid modernization proposals and associated cost recovery filings, the utility that can demonstrate mastery of operations and maintenance for its asset base and present a fact-based capital expenditure plan will be most likely to succeed.
The alternative is to continue the current–soon to be old–way of doing things.
In this example, a time-based asset health program can provide only guesstimates and apples-to-oranges comparisons for prioritizing maintenance needs and capital investment.
This broader vision of the smart grid is not limited to sensors and controls but includes the hardware and software necessary for assessing asset performance and condition in near real time. Using data in this regard requires analytics and visualization tools, means going from unaware to real-time analysis, from manual to automated, from reactive to proactive, and harvesting value from each fundamental shift.
Big data harnessed this way drives organizational and business process change that can be an arduous but fruitful avenue to de-siloing. Traditional rivals in information technology and operations technology must cooperate, and executives in the utility’s lines of business also get involved in aligning business value with grid improvements.
Theory, in Practice
Sounds good on paper, right? Let’s look at a real-world example. Our colleagues at Commonwealth Edison Co. (ComEd) in Illinois are developing a program coordinated by Rich Gordus, smart grid manager for grid technologies and strategy. It’s in its early stages, but ComEd has derived significant benefit from its efforts. ComEd wisely articulated its philosophy toward grid analytics and new technology upfront by stipulating they must reduce system stress, enhance security, reduce costs and improve reliability. Further, the utility determined that potential operational aspects of grid analytics should address four questions:
- What’s the right operational philosophy for my utility?
- Will a new application scale for future expansion from pilot to service territory?
- Will the business case be positive and show customer value?
- Will analytics improve reliability for customers?
In 2008, ComEd set to create asset management techniques that could move it from the time-based assessments of the past to the condition-based assessments required for a fully rational operations and maintenance approach, as well as a well-prioritized, multiyear capital plan. The old techniques were based on intuition and experience with a bias toward evaluating an entire asset class one at a time. The new techniques sought would provide the same, fact-based analytical framework that could provide apples-to-apples comparisons of assets in any class and assign maintenance or capital priorities to individual assets that need maintenance or are most likely to fail. The results would inform a multiyear capital plan.
ComEd understood that beyond gauging asset health, grid analytics coupled with visualization would provide valuable, near real-time insights to grid operators, system engineers and capacity planners. Moving from a reactive stance to a proactive stance would mean cultural shifts. Information technology and operations would have to work together, and fact-based prioritization of Opex and Capex would have ripple effects across budgeting and regulatory approaches.
Toe in the Water First
The foregoing principles were first applied manually to one asset class to test their value. Once value was established, ComEd applied the principles to all asset classes. Then it created an asset management system with sensors, distribution automation devices, automated data flows, an appropriate data communications network, analytics and visualization tools.
Work was underway in 2009-2010. The operations technology group took the lead because it would deploy sensors and distribution automation devices. Operations had to involve information technology because operations needed software that would help it monitor, assess and visualize grid operations. An integrated team would address the challenge.
The two formerly siloed rivals became partners in technology design, development and implementation, with information technology active in business requirement sessions and asset life cycle cost and benefit analyses.
The information technology-operations team had to create a program that addresses four questions:
- Would data from a substation serve both system operators and engineers?
- How could that data be visualized effectively in a graphic display?
- How could measurements and calculations be integrated and presented for proactive decision-making?
- Would the system the team created scale from a pilot to hundreds of substations?
The team decided to focus on one transmission-fed substation with systemwide characteristics in ComEd’s Innovation Corridor that includes nine towns and part of Chicago. (It’s also the site of a 130,000-interval meter pilot.)
The first step at this brownfield site was to replace all electromechanical relays with microprocessor-enabled relays with supervisory control and data acquisition (SCADA) functionality and breaker-monitoring features. (Data outputs include mechanical and electrical operating times for the main contacts, contact wear and system-monitoring and evaluation tools.) The project also installed monitoring gear on transformers and load tap changer controls. Parallel to the substation conversion, ComEd’s information technology-operations team developed visualization tools in the form of dashboards.
Transformer data outputs, for instance, included percent instantaneous loading, current loading, current and voltage temperature characteristics, oil temperatures, fan operations and tap changer position. Near real-time values would be presented alongside the context of historical trends. Load tap changer data outputs included bus voltage, current, transformer current and oil temperature.
The Analytics Piece
The data outputs on asset condition created an asset health score from zero to 100, a value translated into one of five categories of health: very good, good, fair, poor and very poor. This score is plotted with a risk score that reflects the asset’s criticality and consequence costs of underperformance or probability of failure. The results inform ComEd’s Material Condition Improvement Plan (MCIP), which when rationalized with other factors contributes to operations and maintenance planning, the annual budget and a multiyear capital plan.
Meanwhile, the information technology-operations team created a central dashboard for the upgraded substation with all available metrics on one screen. In 2009-2010, there wasn’t much available on the market. With OSIsoft’s PI Historian database and Ivara software in hand, the team created dashboards that answered their initial mission’s questions on serving system operators and engineers with a graphic display that could assist proactive decision-making and scale to hundreds of similar substations.
Dubbed the One-line Station Overview, the main dashboard includes color-coded icons that indicate asset health: Green is normal; yellow is abnormal; and red is alert. This dashboard provides asset performance and engineering metrics for the high-side bus, transformers and feeders. When preset thresholds are reached for assets that warrant closer inspection, alerts are sent via text, page and email to designated personnel for investigation.
The main dashboard contains button-like icons for drilling down into performance metrics for individual components such as the transformer or the load tap changer, each of which has its own dashboard, as well.
If transformers appear to be an issue, operators can click on that icon to get the transformer dashboard that provides load tap changer position, bus voltage, oil temperature, transformer current and other data. A breaker dashboard provides metrics on trip targets, relay alarms, the breaker’s operational readiness and more.
ComEd plans to integrate an automated work order system that can deploy a field crew without an operator’s pushing a button.
Results so Far
In 2011, one transformer dashboard alerted operators and engineers to five fan issues. A field inspector briefly looked at the asset and disputed anything was wrong, but a second trip and a prolonged visual inspection revealed a fan was intermittently slowing down. If that malfunction hadn’t been caught, the utility would have had to re-rate the transformer for a lower load.
Transformer paralleling situations were detected where the transformers were not regulating appropriately, which could have led to a transformer failure, but allowed proactive emergency repairs rather than mere reaction to a failure event.
In a third instance, a coupling capacitor voltage transformer (CCVT) depressed voltage indicated a failing VT unit, which allowed a planned replacement rather than a post-failure reactive replacement.
The detection of these anomalies through monitoring, visualization and alarming systems validated the monitoring model. As the sampling time interval increases and the substation equipment undergoes normal wear and tear, ComEd will see increased benefits that can be quantified in dollar terms.
Real-time monitoring has raised efficiency levels. Dissolved gas analysis (DGA) presented on the dashboard, for instance, provides asset health data that formerly took as much as two weeks to obtain through sampling and lab analysis.
In 2012, the Illinois legislature passed the Energy Infrastructure Modernization Act (EIMA), which provided a formula rate for certainty around $2.6 billion in cost recovery over a decade, applied to a to-do list for grid upgrades including the installation of thousands of distribution automation devices, deployment of 4 million smart meters and a cybersecure communications system, among many other items, some devoted to grid hardening.
EIMA also contained performance-based metrics for ComEd to meet and report on annually, including improvements in reliability indices such as the System Average Interruption Frequency Index (SAIFI) at 20 percent and the Customer Average Interruption Duration Index (CAIDI) at 50 percent.
ComEd’s work on asset health, risk factors and substation automation for asset management that feeds budgeting, Opex and Capex positioned the utility to gain the support of legislators for a decade of grid modernization. And EIMA is serving as a catalyst for continued development on the work mentioned in this article.
The thousands of distribution automation devices scheduled for installation in the next five years under EIMA financing include mid-circuit reclosers and automatic line re-sectionalizing switches, devices that can perform automatic load flow reconfiguration.
Dashboards: Just the Beginning
Once ComEd installs its smart meters, scheduled for 2015-2021, and when that data is combined with operational data, the system should provide insights into such things as advanced temperature monitoring, customer to transformer validation, feeder voltage limits, feeder overloading, transformer overloading or both.
The goal for ComEd is to use electricity more efficiently, improve system reliability, strengthen system infrastructure and drive regional economic development.
Next Steps: What’s Missing?
ComEd’s Gordus said the ability to combine grid operations data with customer operations data (e.g., from advanced metering infrastructure/MDMS) would provide further insights. Already ComEd’s work in asset management has put it into the vanguard of such efforts nationwide.
John D. McDonald is director of technical strategy and policy development at GE Digital Energy. He earned bachelor’s and master’s degrees in electrical engineering specializing in power engineering at Purdue University and an MBA in finance at the University of California, Berkeley. He is past president of the IEEE Power & Energy Society (PES), an IEEE PES distinguished lecturer, board chair of the Smart Grid Consumer Collaborative and board chair in the National Institute of Science and Technology’s Smart Grid Interoperability Panel. He is based in Atlanta.