Solving real world problems with modern technology is a cornerstone for us. In close collaboration with partners in the energy sector, we created a concept that presents a solution to one of the big challenges in the energy sector today: Knowing when to sell and buy energy.
The energy sector is highly competitive as tight revenue opportunities dominate the market. Finding new business models and services is a must in order to stay ahead and keep customers from parting ways and moving to the competitors. We invented a concept to meet that need.
Forecasting Power Consumption
The concept is a smart grid that lets energy providers forecast the consumption of all households on their grid. By collecting data and controlling specific appliances in households, energy providers are able to trade and utilize power more sustainably.
Using predictive analytics on data from the grid combined with relevant external data, weather e.g., makes it possible to prescribe the right action at the right time automatically.
and Consumers through Smart Appliances
With this smart grid, households choose one of three consumption level packages to follow; Economy, Normal, or Luxury, and give the energy provider access to smart appliances accordingly. This allows the energy provider to regulate the households’ compliant smart appliances.
The households save money and help the energy provider save on the environmental cost. The power provider can tune the amount of power provided according to the households’ current energy need and optimized power trading.
The Techy Side of Things
A setup like this involves multiple technologies and devices. Here is an overview:
Household control panel:
• Each household gets an energy efficient control panel that lets the consumers manage and review all their smart appliances. This is achieved on low-cost hardware using TouchGFX.
• The control panel is connected through a lightweight protocol, MQTT, which allows us to connect with IBM’s Bluemix.
In the cloud:
• IBM’s cloud solution, Bluemix, provides access to a wide variety of modules such as several types of databases, applications, analytics, and access to IBM Watson services etc.
• In this set-up, we use Bluemix to collect, handle, and respond on information passed back and forth between the households and the energy supplier.
Automatic and intelligent decisions making:
• To make intelligent decisions on when to buy and sell energy, and when to regulate consumer devices, we use IBM’s SPSS Modeler. This enables us to make predictive analysis on the information streaming through the predictive model, giving us the insight to control or automate the system intelligently.
The energy provider:
• On the other side of the fence is the energy provider and the service organization. They communicate with the system through Web API’s like REST, getting information such as current status, usage forecasts etc. This empowers decision makers to buy and sell energy at the best time possible, and how to detect anomalies in the system in order to set a service technician in motion.
- TagsCloud & Mobility, Internet of Things, Technology & Platforms