The current state of the smart grid is not enough for the needs of utilities and their customers. Today’s ‘smart grid’ is not truly a smart grid, but simply smarter metering. The components that make the grid smarter – networking capabilities, digital controls, distributed intelligence, smarter failure avoidance strategies, etc. – have not yet arrived in their best form. These components derive most of their value because they produce data that utilities have never had access to in the past. But for now the data that is being created is essentially useless. There is currently no way to understand this data, nor are there existing ways to implement it in meaningful ways. And with the current expectation that energy demand is projected to grow by more than a third of its current amount by 2035,1 it’s about time we all start paying attention.
This is not to say that there haven’t been attempts to modernize the grid. It’s just that those that have been introduced have left utilities and customers wanting more. For example, Northeast Utilities (NU), a major utility serving Connecticut, Massachusetts, and New Hampshire consumers, criticized the state of Massachusetts in early 2014 regarding its advanced metering plan, claiming it had ‘no rational basis for the implementation of advanced metering infrastructure (AMI).’ NU felt that Massachusetts’ proposed electrical grid modernization plan, one that would require the utilization of advanced metering or smart meters within the state, would be too costly for the insignificant amount of functionality it would bring to utilities and customers.2
While most utilities would disagree with NU’s position, it is worth considering. If utilities were able to properly leverage the data that these meters collect to actually improve billing, significantly decrease outages, etc., then there would be no question about the value of implementing them. But with the state of the technology available, it is extremely difficult to obtain useful data from the grid today.
Why is data so difficult to obtain from the current smart grid?
Currently, utilities networks are able to access very little of the data that is coursing through their infrastructures. The primary reason it is difficult to obtain useful data is because of the massive amounts of data that come from customer systems, grid operations systems, and enterprise systems. This is very different than the complications that arise from smart metering, which is more on the customer system component side. But there are thousands of other points throughout the smart grid where data collection comes into play. And for the most part, data is simply sitting there in space, not being utilized in a meaningful way.
It’s not only that the data cannot currently be accessed, but that once upgrades are made to utility networks, a resulting side effect is that electricity providers will all-of-a-sudden be expected to process much more information than they’re accustomed to processing.3 And adding more data to analyze can be extremely overwhelming.
There are some sophisticated analytics technologies that are currently being used to collect and process this data. But the information that is collected is isolated into separate pillars that do operate cohesively. This makes it nearly impossible to recognize the more complex relationships between the data within each. So it is challenging to achieve one cohesive picture of an electric utility’s data and how it can be applied to operations.
What are the most common types of outdated technologies that are currently being used by electric utilities?
Though there are probably too many to name, the three that most people in the industry immediately think of are:
- Operating a distribution grid by looking at only the substations. If utilities could add data from endpoints (meters) and intermediate points (reclosers, breakers, transformers, etc.) to this picture, they will significantly modernize their operations.
- Somewhat related to the previous point utilities are still operating distribution systems without the voltage information from the endpoints, which creates a potentially dangerous blind spot.
- Collecting meter readings only as needed to support customer billing. Utilities should be able to collect meter readings at any given time, and leverage that data to make short or long-term decisions about operations.
There are several solutions that can help improve the decades old infrastructure
The most compelling solution is by far the use of the cloud, which provides easily configurable computing power so that data storage can be easily added, to almost any level, to store the data needed for the analytics. With the cloud, there is the promise that software and other digital technologies will be able to provide utilities with solutions that can reduce cost and increase reliability and transparency, and even save more energy for utility companies and users.4
Utilities can also use the free, Java-based programming framework, Hadoop, to support the processing of large data sets in a distributed computing environment. This allows data analysis tasks to be spread over as many separate processors as needed, no matter how large the data sets, or how complex the analysis. The user always sees a responsive tool. Cloud data storage can be scaled to suit the volume of data and the expected lifetime of the data. Cloud systems connectivity can also easily support users operating from desktop computers in the office, from laptops in vehicles, and from tablets or even from smart phones used by field workers.
Data analytics can solve these issues and use cases
Data analytics can help to determine the most efficient operation of distribution equipment, which includes benefits like optimizing voltage settings to maintain specified voltages at customer meters while minimizing delivery system losses and power acquisition costs. Another example would be the ability to correlate blink counts at meters to identify fault locations or analyze outage reports to locate tripped circuits.
It can also be used to monitor electric system operations to alert operators when performance trends indicate failing components or required maintenance, which ultimately reduces system failures and emergency repair costs.
Lastly, data analytics can benefit the customer directly by delivering useful information that helps to reduce their energy consumption and energy costs, particularly when complex TOU or CPP rates are available. These can typically be difficult for the customer to evaluate, but ‘bottom line’ analytics can make the choices clear. In the same vein, analytics can provide guidance to the utility during new rate evaluations, showing the results of alternative rate structures being considered.
Unlock your data for future decision making!
Software solutions offer utilities an opportunity to innovate and update their existing infrastructures in a non-invasive manner. With the ability to access the data flowing through the power grid, some of the benefits utilities would experience include:
- Ability to access and unlock new products
- Widening the types of services a utility is able to provide
- Improved asset deployment and operating efficiency
- Enablement of active customer participation
- Ability to accommodate all generation and storage options
- Ability to fulfill the demand for power that is expected to increase with the changing digital landscape
- Capability to predict and respond to system disturbances
- Ability to anticipate and operate during natural disasters
- Resilience to physical and cyber-attacks
But all of these benefits are powered by correctly harnessing the unstructured data in a utility’s networks. Being able to do so not only creates the opportunity for smarter decisions, but faster ones that are based on accurate and timely analytical analysis. These solutions can enable a flow of information which can transform raw data into useful, comprehensible information, leading to better business decisions for the utilities and a better experience for the customers they serve.
About the Author
Scott Foster is the president and CEO of Delta Energy & Communications, and has over 29 years of experience in the energy sector.
References
1 World Energy Outlook 2013 Factsheet (2013) http://www.iea.org/media/files/WEO2013_factsheets.pdf
2 Investigation by the Department of Public Utilities on its own motion into Modernization of the Electric Grid, D.P.U. (December 23, 2013) http://haltmasmartmeters.org/wp-content/uploads/2014/01/NSTAR_R12-76-Comments-7986-POSTED01172014_HIGHLIGHTED.pdf
3 Gomes, Lee. 9May 25, 2011) The Challenge of Big Data on the Smart Grid. MIT Technology Review. http://www.technologyreview.com/news/424088/the-challenge-of-big-data-on-the-smart-grid
4 Enabling the SmartGrid through Cloud Computing. (April 2012). http://energy.gov/sites/prod/files/Friday_Trinity_Ballroom_3_0855_Primetica_final.pdf
