Smart data, dumb grid?
I think, therefore …..
What is a Smart Grid? Think of Asimov's Bicentennial Man, not human yet sentient nonetheless. When is a robot human? When is a grid smart? Like the Bicentennial Man struggling to develop emotions and become human, the electricity grid is struggling to develop sensory information and become smart - but how well is it doing? What needs to take place to move us from a “dumb” grid that is filled with smart data (data from smart devices) to a Smart Grid? Clearly it is the joint capabilities of being able to identify issues and take steps to address them; but to call today’s grid “dumb” is probably unfair and implies a lack of intelligence and automation which is obviously not the case.
KEMA has worked with many utilities over the years to help develop substation automation (SA), distribution automation (DA), and to develop architectures for sharing data from intelligent electronic devices (IEDs) at the enterprise level. Yet clearly there is a quantum leap that needs to occur to move the grid from where it is today to a truly smart grid, whether at the distribution level or at the transmission level, or both.
There is a lot of data currently available from SCADA systems, reclosers, digital fault recorders (DFRs), smart relays, breaker monitors, capacitor bank controllers etc. So when does Smart Grid get smart? And when does it get the capability to heal itself? After all one of the touted benefits of a smart grid is the ability to utilize information from the types of devices previously mentioned so as to automatically avoid power outages and other problems by detecting (or monitoring and anticipating) problems with the power system.
To use a true but often over-quoted phrase it is all about turning data into information, and information into knowledge. But even that is not enough. For grid applications to be effective we need to turn that knowledge into action.
Action is where the value is
Some actions will be immediate such as self healing (“post fault recovery”), switching operations etc., some will be near time such as dynamic ratings, transformer load management and outage management coordination, and others will use historical information for distribution planning, asset management and other data and information mining activities.
What is smart grid?
The Energy Independence and Security Act of 2007 (EISA) defines smart grid as being characterized by ten items listed in Section 1301 which are:
increased use of digital information and controls technology to improve reliability, security, and efficiency of the electric grid
dynamic optimization of grid operations and resources, with full cyber-security
deployment and integration of distributed resources and generation, including renewable resources
development and incorporation of demand response, demand-side resources, and energy-efficiency resources
deployment of ‘‘smart’’ technologies (real-time, automated, interactive technologies that optimize the physical operation of appliances and consumer devices) for metering, communications concerning grid operations and status, and distribution automation
integration of ‘‘smart’’ appliances and consumer devices
deployment and integration of advanced electricity storage and peak-shaving technologies, including plug-in electric and hybrid electric vehicles, and thermal-storage air conditioning
provision to consumers of timely information and control options
development of standards for communication and interoperability of appliances and equipment connected to the electric grid, including the infrastructure serving the grid
identification and lowering of unreasonable or unnecessary barriers to adoption of smart grid technologies, practices, and services.
It is important to note that these functions do not define what Smart Grid is, just what it should do. Indeed, a good deal of confusion remains within the energy industry regarding what precisely is the Smart Grid but these items generally share a common requirement which is to integrate and share data rapidly. And there is good reason that there is no single and concise definition of what smart grid is, at least from a prescriptive implementation form. It is not a case of “one size fits all” nor should it be.
While utilities are fundamentally similar in many ways the history, goals, drivers, demographics, and regulatory requirements make each utility unique. Indeed, requiring utilities to conform to a single definition of smart grid would impose false targets and imprudent requirements in some cases which is why every utility needs to understand what smart grid means to them and to take the steps to meet those goals.
With many utilities looking to redesign their business models to add capabilities that leverage new technologies and seek to improve performance and reduce risk, it is essential to measure realized value from these technology and process driven changes. This requires linking strategic objectives with shareholder value in a holistic business management system. A transformation program like this represents a significant opportunity to look at how current business processes are performed based upon current limitations of organization, processes and technology and to align new processes with strategic objectives that provide shareholder value, transform the current business processes, and improve the approach to risk management while defining quantifiable metrics that can measure this progress.
While we are on a national path to achieve a “smart” grid, we will be years (decades, perhaps) away from achieving a truly “intelligent” grid. This process is a journey and will take time, characterized by an intelligent grid as reaching a state where the following items occur:
sensors and controls become truly autonomous, driven by self-correcting, intelligent algorithms, operationally embedded
utilities and energy providers are making the investment decision a priority, with intelligent controls a design standard for asset management
new stakeholders and market participants offer a larger array of new products and services
regulators and policy makers enable effective cost recovery schemes, not tied to the current regimes
consumers demand the flexibility and fully engage as active participants
All dressed up but nowhere to go
Being in the possession of smart devices and being in a position to leverage the data are two different things. The utility of the future has as much to do with managing data as it does with managing pipes and wires. Managing data is key, and a critical piece of managing data is getting it to the right systems and people in the right format at the right time.
Although the term “utility of the future” is used generically above to refer to the impacts that technology and data are having on utilities, it is also the title of a book by KEMA that is an outgrowth of strategy work performed by KEMA for major utilities and other key energy industry suppliers and which reflects the ideas and conclusions drawn in countless hours of discussion with the leadership of these companies as their existing operating and business models are forced to meet increasingly complex challenges.
This need for rapid integration and supporting communications must start with good interface definitions. Now that Advanced Metering Infrastructure (AMI) and Smart Grid (whatever that really means) have so much attention in the industry the need for people to start adopting and deploying standards is absolutely essential. In fact it is probably far more important than actually trying to define what Smart Grid really is.
There has been a lot of focus on communications standards, data standards, and cyber security standards with the latter generating a lot of recent headlines. But cyber security goes beyond the protection layer (technical devices or services) as it must also be integrated into the processes and business plans to be most effective. Security in the processes often take the form of key controls that supplement the protection layer.
If we cannot integrate these disparate data streams and make effective use of them, we will just have stovepipes of data from smart devices that can only be used for standalone applications.
The future is smart grid. The future is wow
There's no doubt about it, the era of Smart Grid is upon us. Everywhere you turn there are AMI projects and intelligent electronic devices being implemented; augmenting the already plentiful data being provided by the current generation of SCADA systems. The integration of these data we know will yield many benefits in the creation of new information that can be used to improve reliability in many ways. Some of this will ultimately be accomplished automatically such as for self healing networks but what of the interim? Even the self healing actions will likely take different forms that are differentiated by how long it takes to implement the action identified by the grid. Self healing on bulk transmission may require sub-second switching in conjunction with configurable relay settings but self healing on a rural distribution feeder may be instantiated by the creation of a work order for a mobile workforce system.
If you can’t integrate data, you can’t leverage it
So where is all this data coming from and where does it need to go? And how does it get there? And in what format? Should all this data be subjected to the same level of security? KEMA has advised utilities on these issues in the past and is seeing more and more interest in providing answers to these and other questions as the move to adopt AMI becomes more widespread. Consumers Energy is one utility leading an effort to examine the CIM[a] and MultiSpeak[b] standards, determine gaps, and make recommendations back to both MultiSpeak and the IEC[c][1].
The Advanced Metering Infrastructure (AMI) market is relatively immature and technologies are changing rapidly – and will likely continue to change at an accelerating rate. As a means to mitigate technical risks and lower life-cycle costs, Consumers Energy is actively involved and making significant contributions to industry standardization efforts impacting their AMI program [1].
Standards are the future, the future is now and as standards (e.g., ANSI C12, IEC 61968, etc.) become more mature and are adopted by manufacturers and utilities, it will become a more manageable challenge to implement and integrate smart devices. Do you recall the familiar adage: “work smarter, not harder”? This applies to AMI and Smart Grid just as well as it applies to anything else. We as an industry need to be smart about how we design and implement these advanced systems, and this means investing time in and committing to standards.
But, it is not just AMI that is driving these requirements. 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.
Chicken or the egg?
We have focused on interfaces and data transfers up to this point. Interfaces are critical but we also need to be able to store and rapidly retrieve these data. Meter data management systems (MDMS) are now defined as systems that link a utility’s meter data to its back-end enterprise systems [Chartwell]. That link is crucial and several utilities including Consumers Energy have incorporated MDMS into their AMI implementation strategies. Some utilities implement AMI and then MDM. Others implement MDM and then AMI. Twenty-two percent of utilities that Chartwell interviewed in its 2007 metering survey state they are currently using a standalone MDMS to process and store their incoming meter data. This can be utilized for Grid Applications when integrated with several key distribution systems but how can you leverage that for Smart Grid?
Earlier we used the term “Grid Applications”. What’s the difference between Smart Grid and Grid Applications? In the AMI Pilot at Consumers Energy we have been using the term Grid Applications to refer to applications that leverage the data from smart meters, but not from other sources that are normally considered as Smart Grid. We reserve the term Smart Grid for applications that leverage data from all smart devices and perhaps even broader sources of data.
Value: going beyond the obvious
Do we need to differentiate between Grid Applications and Smart Grid? Perhaps not but it helps with the process of building the business case and roadmap for a Smart Grid Program and planning how to realize the benefits that these technologies present. When should we decide to implement these applications and what is the cost of not deploying them?
Grid Applications can be implemented as AMI rolls out through mass deployment but Smart Grid may require significant additional investment to retrofit substations with IEDs, depending on the level of smart devices already deployed and the amount of automation already implemented.
Is there a cost to not investing in Smart Grid? Many people think that there will be significant benefits from Smart Grid with our industry facing increasing congestion, more distributed generation and an increasing focus on renewables? If there is a cost to not investing in smart grid, then waiting to make a decision to deploy Smart Grid is essentially a decision to avoid benefits. It is a decision that may cost jobs, may hit reliability and may hit the bottom line.
In addition to the deployment of Smart Grid, once a Smart Grid system is deployed, there will be several thousand utility jobs needed nationally to maintain the Smart Gird. KEMA estimated this number as just under 5,800 new positions [4].
Some typical benefits of Smart Grid which would not be fulfilled without AMI, intelligent electronic devices, and integration systems include:
increased use of digital information and controls technology to improve reliability, security, and efficiency of the electric grid
deployment and integration of distributed resources and generation, including renewable resources
deployment and integration of advanced electricity storage and peak-shaving technologies, including plug-in electric and hybrid electric vehicles, and thermal-storage air conditioning.
These benefits could be considered as lost opportunities without Smart Grid.
Roadmap to the future
To realize these benefits it really means that not only do you need to have a vision but also a phased roadmap with a detailed business case. It also means that you need to establish reference metrics to track the performance and benefits of these new systems, as shown in the value realization model. This shows that it is first important to identify the benefits to the utility shareholders before creating the processes and operational levers to enable these benefits. These should be implemented under the umbrella of an overall change initiative that includes the specification and tracking of metrics to measure the degree of success that is attained.
The validity of the applications has to be demonstrated not only in terms of functional benefits but in improvements to operating and capital budgets, reliability and other areas. Technical and Management training programs exist in most companies. Despite the fact that everyone says they are necessary, there is a lack of supporting data to show that management training is actually effective. Management trainees are often promoted to higher levels of responsibility and this is often quoted as validation for the programs but the participants in these programs are normally the most promising employees so this is not a valid measure of training success. We cannot afford to let Grid Applications and Smart Grid fall into a category of systems that we feel are necessary and valuable but for which we cannot adequately and quantitatively demonstrate the benefits of these systems and the validity of the programs to implement them. We must create metrics to measure the degree of success that is attained.
Summary
The issues discussed here are also reflected in the results of the Breakout Session Discussions at the Smart Grid Implementation Workshop at the Office of Electricity Delivery and Energy Reliability, June 19-20, 2008 where the fact that Smart Grid is not a case of one-size-fits-all is also stated:
“Measuring progress toward implementation of smart grid involves identifying metrics, establishing baselines, and collecting data to track developments. In doing this there is need to account for the level of development and deployment that has already occurred and to recognize that the topology of each utility’s transmission and distribution system may require its own baselines, targets, and measurement approaches. As a result, it is probably not appropriate to track smart grid implementation in the same way for every entity who adopts smart grid technologies, practices, and services.”
So when does Smart Grid get smart? It is all about turning data into information, and information into knowledge but remember that for grid applications to be effective we need to turn that knowledge into action. Action is where the value is. Now is the time to act.
References
Grid-Interop Forum 2008 MultiSpeak® and IEC 61968 CIM: Moving Towards Interoperability - McNaughton, Robinson, and Gray
IEEE Standard 1366-1998
Power Distribution Planning Reference Book, (Chapter 4 Power System Reliability), Second Edition, CRC Press, 2004 – H. Lee Willis
The U.S. Smart Grid Revolution - KEMA’s Perspectives for Job Creation, Prepared for the GridWise Alliance, January 13, 2009.
Energy Independence and Security Act 2007.
Metrics for Measuring Progress Toward Implementation of the Smart Grid - Results Of The Breakout Session Discussions at the Smart Grid Implementation Workshop, Office of Electricity Delivery and Energy Reliability, June 19-20, 2008
a. Common Information Model. An international standard developed under the auspices of the IEC.
b. The MultiSpeak specification is an industry-wide software standard that facilitates interoperability of diverse business and automation applications used in electric utilities.
c. The International Electrotechnical Commission is the international standards and conformity assessment body for all fields of electrotechnology.
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