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When Is a Meter Not a Meter?
By Mark Knight
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Not too many years ago, metering was mostly about measuring total usage over time. Many utilities self-generated and the need to know actual time of consumption to support transmission contracts, congestion, and high-priced generation was not a significant issue. Then the need to understand line losses, price variations, time-based purchase contracts, spot markets, and reliability led to more detailed metering for commercial and industrial (C&I) customers and the world of metering began its journey to where we find ourselves today.
We live in a world where home automation has been technically available to the mass market for about a decade; where energy shortages have caused blackouts (local and regional) and large price fluctuations; where many utilities are providing services for more than one commodity (electricity, water, gas) due in part to mergers and acquisitions; and where managing data has become as much a part of the business as managing pipes and wires.
The technology has changed, the regulations are changing, the customers are changing, the processes are changing, and expectations have changed. In short, the industry has changed and it will continue to change for the foreseeable future.
Perhaps the reason that the chicken crossed the road was to read the meter on the other side, but today that is no longer necessary. So how has the meter itself changed and when is a meter not a meter? Since the question posed by the title of this article probably attracted your attention, it seems only fair to provide an answer, and one that is as good as any is when it is a disconnect switch, or perhaps when it is an interface unit for a pulse output meter, or perhaps when it is a node in a wireless mesh network. That is to say; the meter is continuing to evolve at a rapid pace.
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The New Functions of a Meter
According to one definition, a meter is “an instrument that records or regulates the amount of something passing through it, like electricity or gas.” However, as all know, modern meters do much more than that. Not only do meters record commodity use, but they can do it in two directions. Meters also can store data, aggregate it for time-of-use rates, collect multiple types of information, monitor themselves and any attempts at tampering, and sound an alarm when certain conditions occur. And, of course, meters also act as network nodes and remote disconnect switches.
Of course, not all meters are made equal and a meter’s level of functionality is dependent on its targeted use. However, without question, today’s meter is a technological marvel. In addition, many meters oftentimes have to perform their functions in sub-freezing temperatures and in the heat of a blazing summer’s day.
In the past, the functionality of commercial meters has exceeded the capabilities of residential meters and this has been due to demand (no pun intended) from large customers and utilities alike, eager to learn more about how they use electricity. Now, with AMI implementations growing at increasing rates, the improvements in the functionality of residential meters is outpacing that of commercial meters.
Commercial meters have always had the capability to collect different channels of data, but the numbers of deployed meters have generally been limited. Today, huge numbers of smart (residential) meters are being deployed that have the capability to capture vast amounts of data at frequent intervals. Large numbers of meters, increasing functionality, and more granular timescales create a perfect data management storm. It is also important to note that it’s not just meters that are changing. The microchip has steadily been becoming ubiquitous in equipment and today’s utility company finds itself in the position of owning tens of thousands or even millions of devices that are capable of providing a wealth of data about the health of equipment as well as what is going on in the pipes and wires.
Of course being in the possession of the devices and being in a position to leverage the data are two different things. This is an important point because the utility of today—and perhaps more importantly the utility of the future—has as much to do with managing data as it does about managing pipes and wires.
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New Demands on Data
So where is all this data coming from and where does it need to go? KEMA has advised utilities on these issues in the past and our firm is seeing more and more interest in providing answers to these and other questions as the move to adopt AMI becomes more widespread. However, it is not just AMI that is driving these questions. Similar questions arise in the areas of substation automation and distribution automation as more and more two-way capable intelligent devices are implemented, often as a straight functional replacement for an older electromechanical device.
In one such project, KEMA interviewed approximately 110 engineers from 25 departments at a utility where people were asked about the data that they used, and where the capabilities of data collection from intelligent devices was explained. One of the findings of the work was an interesting paradox: engineers wanted more data (and more timely data) but they also wanted less IT systems to have to use.
This is typical of the types of challenges that the modern utility faces. KEMA has performed this type of service for other utilities and it is a useful tool in itself for aiding in communicating between different groups within the utility about the types of data that are available, and how it can be used. In this type of project, with regard to socializing information about the types of data that are available, the types of responses received can often be summarized as usually falling into one or more of the following perspectives:
- I need more data
- I need better quality data
- I need the data that Protection, Metering etc. are using
- I know we have the data somewhere, but I don’t have access to it
- I spend too much time collecting data instead of analyzing it
- I need the data in a more timely manner
- I have access to plenty of data but it’s all in different places
- I have access to the devices but the commands to retrieve it are all different
- I know we are installing new devices but I don’t know what data each device has available
- Enough with the data, what I need are better ways to analyze it
- We have that data here?
On one hand, utilities are implementing more and more data warehouses and business intelligence systems that allow them to utilize data that has been integrated through the use of Enterprise Application Integration (EAI), Service Oriented Architectures (SOA) and other techniques. However, as more information is made available and as even more data are becoming available from intelligent substation devices and smart meters, the industry as a whole faces the challenge of having to integrate new stovepipes of data that seemingly appear almost as rapidly as we remove the old ones.
Perhaps this should not come as a surprise. As new technology opens up access to new treasure troves of data, new applications appear that can use these data and provide value in niche areas. What this means for utilities that are in the planning stages of AMI projects is that the management of the data has to be carefully thought out in advance with respect to key issues such as data consumers and integration requirements. Now that more detailed and more frequent data are available, utilities are learning that the new technology holds the promise of being able to help in many new areas of utility operations, which in itself represents a challenging new paradigm.
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New Challenges for Utilities
Many utilities are presently asking themselves how much data they really need and when do they need it. Put another way, should a utility collect as much data as the technology allows, or should it begin with minimal data collection to support existing business processes only and increase only as requirements dictate? Or should the utility pursue a hybrid approach between these two options?
There are many factors to consider when making these decisions, but many of these are obvious and it is simply a case of looking at how the variations in each factor affect the utility’s costs and technology choices, and how they support business requirements and expected benefits. The important thing here is that a utility needs to understand what data could be collected and how it could help its business. This involves socializing the data that could be collected and then standardizing the data that should be collected. Another way to look at it is that a utility needs to share information about the data before it shares the data itself. So, for instance, some of these factors include:
- Meter capabilities —The amount of memory on the meter needs to be considered and the data that the meter is capable of recording needs to be socialized in order to meet both near term and future requirements.
- Current data use / Process evaluation —Manual processes should be automated to deal with increased data volumes, and current processes need to be examined with respect to any benefits from incorporating additional data granularity. Process diagrams need to be updated to reflect data from new metering components.
- Interval size —Smaller intervals mean more data. More data requires more memory and more storage but provides a more detailed picture of usage and operating conditions. More data also requires more bandwidth for transmission.
- Collection frequency —More frequent collection means better ability to respond to conditions in a timely manner and reduces “burst rate” peak data transmission rates for data transmissions by providing the capability for spreading the load (if bandwidth is an issue).
- Duration of storage —The longer data is kept online, the more storage is required. Older data may be aggregated to reduce online storage requirements.
- Temporal availability —When considering how frequently to collect data, there are three broad temporal classifications for when field data can add value. Near-time allows for notification of events and abnormal conditions. Minutes to hours after an event allows for updates on system status and feedback for engineers and customers. Days to months after the event allows for detailed data mining and analysis looking for trends, etc.
As AMI technology and MDM systems become more and more mature and as standards continue to develop, the process of choosing meters and AMI technology should become more of a plug-and-play process. As standards (e.g., ANSI C12, IEC 61968, California Meter Exchange Protocol, etc.) become more mature and are adopted by manufacturers, it will become a more manageable challenge to implement AMI, at least from an integration perspective, as it becomes more of a commodity market with common functionality and support for standards. There will always be factors to differentiate vendors as technology and innovation drive the industry forward. Some factors such as cost, choice of communications media, and vendor preference will remain even as new AMI technologies and new vendors appear, but the choice of an MDM (as an enterprise system) has many complexities to consider.
As data and information are shared more and more within the enterprise, it is important to know exactly what data are being used. Likewise, any changes that are made to the data need to be well documented since that may impact subsequent users of that data. In summary, each utility should be asking itself this question when it next accesses data from either its meter data management system or other enterprise system: Do we know where our data has been, and do we know where it is going next?
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Download the March 2008 Issue
Use the link below to download the PDF of the full issue of the March 2008 Automation Insight for the complete print versions of the articles.
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[download] Automation Insight March 2008 (.pdf 236 kb)
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