Reducing energy consumption, finding new sources of renewable energy, and increasing energy efficiency are all important big data goals for protecting the environment and sustaining economic growth. Large volumes of data in motion are increasingly being monitored and analyzed in real time to help achieve these goals.
Many large organizations are using a variety of measures to ensure that they have the energy resources they need now and in the future. Nontraditional sources of energy, such as wind turbines, solar farms, and wave energy, are becoming more realistic options as the price and scarcity of fossil fuels continue to be of concern.
These organizations are generating and storing their own energy and need good real-time information to match the supply to demand. They use streaming data to measure and monitor energy demand and supply to improve their understanding of their energy requirements and to make real-time decisions about energy consumption.
Use big data to increase energy efficiency
Organizations are beginning to use streaming data to increase energy efficiency, as highlighted by the following two examples:
A large university monitors streaming data on its energy consumption and integrates it with weather data to make real-time adjustments in energy use and production.
Members of a business community collectively share and analyze streaming energy use data. This enables the companies in this community to consume energy more efficiently and reduce energy costs. Streaming data enables them to monitor supply and demand and ensure that changes in demand are anticipated and kept in balance with supply.
Use big data to advance the production of alternative sources of energy
Organizations are also beginning to use streaming data to help advance research and efficient production of alternative energy sources, as demonstrated by the following two examples:
A research institution is using streaming data to understand the viability of using wave energy as a source of renewable energy. Many different parameters, such as temperature, geospatial data, and moon and tide data, need to be collected. The organization uses monitoring devices, communications technology, cloud computing, and stream analytics to monitor and analyze the noise and impact on marine life made by wave energy technology.
A wind-farm company uses streaming data to create predictions about energy production. The company collects turbine data, temperature, barometric pressure, humidity, precipitation, wind direction, and velocity from ground level to 300 feet. The data comes from meteorological stations around the world. It creates a model of wind flow to improve understanding of wind patterns and turbulence. The analytics are used to select locations for wind turbines and reduce cost.