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The recent exits of Google’s PowerMeter and Microsoft’s Hohm products targeted at consumers have some industry watchers asking if residential consumers really care about home energy consumption data.  Where we once had a monthly bill that simply indicated the previous month’s kilowatthours of electricity use, smart meters can provide data as often as needed (although 15 minute intervals are a de facto “standard” assumption at this time.)  Who would be interested in this data?  Certain consumer profiles like greens, frugals, and tech gadget aficionados have demonstrated that they appreciate detailed information about energy use, but a larger part of the consumer population hasn’t found a compelling value in this data. 

But there is value in the new amounts of heretofore non-existent data from the grid edge that will be available as more Smart Grid technologies rollout into consumer residences and businesses.  There are killer apps in the analysis of energy use data, and data analytics solution providers with experience in business sectors like wireless and consumer retail have interesting ideas about the real values of consumption data.  The ideas documented here are based on conversations with Bob Becklund of PreClarity, co-founder of a data analytics solution firm working in these areas.  Keep in mind that there are still unsettled areas about energy consumption data and privacy, and it will take time to sort out consumer options to permit use of data by utilities or other entities.   But consumers, utilities, and service providers will find significant value in consumption data – particularly as it relates to behavior and lifestyle.

Utilities get smarter about consumers

Utilities could sift through consumer energy use data and perform correlations with demographic data such as zip code, housing and income data to develop profiles of highest value targets for demand response or energy efficiency programs.  Demand response (DR) programs reduce peak demand (electricity used when it is most expensive).   Analysis and simulations of DR program designs and consumer responses can help utilities save money in avoided costs of additional expensive generation, and participating consumers happily save money in programs that fit their lifestyles. 

Utilities could also take energy use data from residential consumers and correlate it with use of social media and preferred consumer interaction channels, and create new education outreach and marketing campaigns aimed at different populations.   One meter may reflect multiple consumers in a household, and each will have preferences for communication channels.  New campaigns could be launched via Facebook or Google + that are targeted to specific demographics for significantly less cost and time than the “one message fits all” practices found in billing inserts. 

Utilities are gradually moving to new pricing plans based on time of use (TOU) or sources of power (clean versus dirty). This is similar to the evolution of pricing within other markets such as the wireless and airline industries.  As pricing has grown more complex, these industries have demonstrated needs for information, insight, and visibility to “what-if” scenarios to support  business decisions, ensure regulatory compliance, and enhance consumer relationships.   Utilities will have similar needs for tools to help them manage a variety of pricing plans and programs and assist consumers in selecting the plans that make the most sense for them.  

Drivers get smarter about EV roaming

EVs have some strong similarities to mobile phones – consumers tend to take them everywhere.  In the early days of mobile phones, it did not take much distance to move from your zone and incur expensive roaming charges.  Could the same history repeat itself with EV charging plans?   Perhaps not, but roaming and charging at pay stations could create billing complexities for consumers, energy service providers, and utilities.  Data analytics expertise can assist in bringing transparency to all the charging data and the business rules behind roaming EV billing, as well as assist in trip planning or identifying the best charging locations.

Consumers get smarter about energy consumption data

Energy consumption data is all about behavior, and therefore needs privacy protections.  However, that being said, there are situations where consumers may find value in giving permission to utilities, energy service providers, or other third parties to access and analyze their energy consumption data.  For instance, appliance warranties in the future may look very different.   Instead of phoning up a repair shop once the refrigerator has died, a consumer may choose a warranty option that allows the manufacturer to monitor the refrigerator’s use of electricity, and analyze that data to predict and schedule maintenance calls that become proactive rather than reactive. 

Consumers may appreciate services that analyze energy use and break it down by appliance or device – similar to how credit card companies report spending patterns into dining, air travel, and other categories.  Seeing categories helps consumers plan budgets, and similar reports of appliance consumption could help accelerate retirement of inefficient, older appliances for more energy-efficient ones.   

We’re just at the beginning of a brave new world of energy consumption data and no, it’s not overkill.  Data analytics can turn this data into usable information.   Leveraging expertise and experiences of solution providers from related business sectors will expedite the discovery and deployment of these new killer apps for the Smart Grid.

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