The best example of combined dynamic rates and smart billing is found in Ontario, Canada. It uses central MDM to produce time-differentiated customer bills.
The buzzword of the day is ‘analytics.’ But what does it mean?
grid strategy and development, Telvent: Data analytics could be defined as managing and presenting all network endpoint data in a way that makes it easier for the network owner to operate, plan, and optimize more efficiently from the utility side. More specifically than that, in our context, the distribution utility; we’re interested in the medium-voltage and low-voltage grid.
Devendra Vishwakarma, T&D principal consultant, smart grid practice, Infosys: Depending on the level at which you’re talking, everyone has a different definition of analytics. Analytics in the generic sense means energy trends, technology services, hardware processes that will enable us to make sense of data and turn it into actionable intelligence to make day-to-day decisions.
Fortnightly: How are analytics capabilities different now from what they were for utilities in the past?
Wambaugh, UISOL: Utilities have been doing analytics since spreadsheets. Load a bunch of data into a spreadsheet, use some of the tools and, boom! You have analytics.
Valocchi, IBM: It’s true that data and analytics aren’t new terms in the industry, especially data. We’ve always had a number of operational types of data: plant statistics, transformer statistics, statistics around assets—like age and condition.
Meyers, Telvent: Traditionally, getting energy usage information into the network-modeling context has been very labor intensive. It’s somebody sitting down and building every one of the rate classes. Then maybe we can get a spreadsheet that has some typical usage patterns for 100 people in each class and somehow force-feed that into the network models, recast that out, and make assumptions about the typical customer.
Bill Devereaux, vice president, industry strategy, Oracle: The utility industry is going through a transformation right now in terms of moving the management of operations—both customer and distribution operations—to a context where more of the decision making and analysis is based on true data coming from the field through sensors and various communications techniques.
Curt Puckett, senior vice president, sustainable use, KEMA: I was hired by Consumers Energy 33 years ago to participate in what were called ‘controlled service experiments.’ We were controlling residential air conditioners and small commercial air conditioners, putting in heat storage in residences, controlling residential water heating, and running time-of-use rate experiments. A lot of the stuff we talk about being new these days is just re-treaded. The marvelous thing, of course, is that technology didn’t stand still.
Fortnightly: What kinds of new data do utilities have to access now?
Bill Lewis, global alliance manager, utilities, Infosys: This explosion in interest in analytics has arisen out of the massive amounts of volume, the ‘big data’ as people are referring to it, coming from the smart metering systems and the sensors in the grid.
Puckett, KEMA: The [quantity of] data that flows now is orders of magnitude larger than the data that flowed before.
Valocchi, IBM: The difference that I see today is the data is more real-time and much more granular than it’s ever been.
Anjul Bhambhri, vice president, big data products, IBM: Utilities are seeing a very large amount of valuable data that allows them to look at