One of the most obvious trends from the big smart grid conference DistribuTECH last week was how much analytics and big data tools will be used to try to remake energy in 2012, from curbing energy consumption, to reducing energy loss, to adding in more clean power to the grid. Here’s 10 ways that analytics and big data will start to shape the production and consumption of energy in the world:
1). Weather data: Having a finger on the pulse of constantly changing weather data on a micro and macro level can help utilities, building owners and consumers optimize their energy consumption habits and promote energy efficiency. Startup EnergyHub recently partnered with sensor network player Earth Networks to use weather data to make a more efficient form of demand response (utilities controlling power consumption). Other startups like EcoFactor, Opower and Tendril also use weather data as part of their energy behavioral analytics.
IBM has long sold a weather prediction service called Deep Thunder to municipalities, organizations and utilities, which use it to do things like tailor their services, change routes, or generate more or less power. I think weather data could some day provide a platform for some very important next generation services and applications for energy efficiency, much in the way that location data is used as a platform for a variety of services.
2). Cell phone data: Cell phones in our pockets are essentially palm-sized sensors and computers sending a constant stream of information to the cloud where companies could one day use that data to create energy efficiency and better energy products. And yes, a lot of that data is private information, but after that data is anonymized it can be used for the greater good of the community — particularly via the billions of cell phones in developing countries. A startup called Jana does research projects around cell phone data in developing countries, and looks to work with NGOs on programs to create better infrastructure, energy infrastructure and resources.
3). Connected thermostat data: One of the biggest trends from DistribuTECH this year was the overwhelming amount of smart thermostats that are now being sold and marketed. Companies can incorporate that thermostat data into data bases that can be used to promote energy efficiency. EcoFactor’s service remembers every time a home owner overrides the automated smart thermostat system and changes the personalized service to accommodate that manual override. Using 100,000 connected thermostats (which produce 5 billion data points each month) EnergyHub found some interesting statistics like folks in cold climates have a lower average heating temperature set point than households in warmer states.
4). Hadoop & energy databases: The open source data base tool Hadoop is well known — and oft used — in the computing worlds. But in the energy and utility worlds it’s quite rare. However, as the amount of energy data has started to rapidly grow from the smart grid, some companies are embracing Hadoop as a key way to manage energy info. Opower tells me it’s using Hadoop (and the company commercializing Hadoop, Cloudera) as an important way to manage its massive energy data streams. Likewise PJM has turned to Hadoop as a way to organize the energy data coming off of a synchophaser sensor project.
5). Clean power data: One of the main goals for the smart grid is to enable the addition of more variable clean power, which is far more unreliable than fossil fuels (the sun doesn’t shine and the wind doesn’t blow 24/7). Analytics crunching the data from a utilities’ energy supply and demand can help make clean power a little less variable, by being able to more accurately predict the environmental conditions, as well as more accurately assess demand from energy users.
6). Electric car data: Electric cars will by their nature be connected cars, using information technology to manage the vehicle charge and location. Utilities will be closely tracking the charging habits of electric car owners in order to make sure that the grid isn’t overloaded in some early adopter neighborhoods.
7). Power line sensors: One of the areas of low hanging fruit for the power grid is the simple task of helping utilities find blackouts more easily and be able to monitor and manage grid outages. That’s partly where sensor systems called synchophasers come in, which can in real time monitor the health of power lines, collecting multiple data streams per second. Expect all major networks to have synchophaser systems installed over the coming years.
8). Real estate data: Startups like First Fuel Software can use big data to make super accurate assessments about buildings and ways to reduce the energy consumption of buildings — without any extra hardware or monitoring software being installed at the building. Things like weather around the building, demographics of the people in the building, and the building’s historical energy consumption can be used to create an accurate projection. The best way to make a building more energy efficient is by getting as much data about the building;s energy use as possible.
9). Variable pricing: Some day when electricity is sold throughout the world at different prices dependent on supply and demand, massive data bases will be needed. This type of variable pricing is offered in some places in the world, but if it ever becomes ubiquitous it will help curb consumption, by offering high prices when energy is being over used.
10). Using behavioral analytics to curb energy consumption: Getting into the brains of energy users is the job of startups like Opower and Tendril (after it acquired Gr0unded Power.) Essentially these companies have collected data on consumers and demographics and they are using it to try to guess the best way to influence the consumer to do things like upgrade their home appliances and lights to more efficient ones.
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