Question

How does an electrical distribution company utilize data analytics?

Answer 1

Many electric utilities have extended the installation of supervisory control and data acquisition system (SCADA) to the distribution feeder level. These advanced sensor systems have finally made an array of big data analytics applications feasible in the electric power distribution network. These big data/predictive analytics applications include spatiotemporal load modeling/forecasting, energy theft detection, distribution system state estimation, demand response management/forecasting, and distribution system topology identification. All the feeder loads are preprocessed with seasonal differencing and Z-score scaling. The Spatio-temporal correlation matrix of the feeders' load is obtained.

In power grid, the traditional fossil fuels are facing the problem of depletion and the de-carbonization demands the power system to reduce the carbon emission. Smart grid and super grid are effective solutions to accelerate the pace for electrification of human society with high penetration of renewable energy sources. Although the rising awareness of sustainable development have become the impetus to the utilization of renewable energy sources, the intermittent characteristics of wind and photovoltaic energies bring huge challenges to the safe and stable operation in a low inertia power system. The data analytics based renewable energy forecasting methods are a hot research topic for a better regulation and dispatch planning in such cases. Traditional electricity meters in distribution systems only produce a small amount of data which can be manually collected and analyzed for billing purpose. While the huge volume of data collected from two-way communication smart grids at different time resolutions in nowadays need advanced data analytics to extract valuable information not only for billing information but also the status of the electricity network. For example, the high-resolution user consumption data can also be used for customer behavior analysis, demand forecasting and energy generation optimization. Predictive maintenance and fault detection based on the data analytics with advanced metering infrastructure are more crucial to the security of power system.

Thus, the great progress of information and communication technology (ICT) provides a new vision for engineers to perceive and control the traditional electrical system and makes it smart. An embedded information layer into the energy network produces huge volume of data, including measurements and control instructions in the grid for collection, transmission, storage and analysis in a fast and comprehensive way. It also brings a lot of opportunities and challenges to the data analysis platform.