For a long time, the utilities industry was not significant in terms of attracting new customers. Merger and globalization have changed that, as the industry transforms into a more dynamic market-driven environment with fewer but larger companies.
The energy and utility industries are undergoing a large-scale transformation through data science technologies such as predictive analysis. Power grids are improving intelligence every day with the induction of data science. Electric power sources are starting to become more prominentand there is a spike in the amount of choices customers have. One of the technological drivers that has impacted this is the emergence of big data and analytics which play a pivotal role in the industry.
Privatization and deregulation have resulted in enormous changes in the utilities sector. The descent of nationalized providers has opened a highly competitive utilities marketplace. Because of this many utilities, companies are working towards improving their performance metrics to trump their competitors. They need to juggle all of this while staying compliant!
Key Advantages of Data Management and Data Analytics in the Power and Utility Industries
Efficient and Accurate Forecasting
Data analytics is used to accurately predict the energy consumption which will influence dynamic pricing. It plays an important role in forecasting power generation, especially for renewable energy sources such as solar and wind power, which are both impacted by variable weather conditions.
Data can be analyzed and used to help design electrical devices that reduce power requirements. Energy efficiency plays a vital role in improving operational areas and addressing equipment efficiency and insulation problems, all while reducing carbon emissions. As a result, companies are able to project their energy consumption and capitalize on potential energy saving opportunities.
Integration of all kinds of data, from energy consumption to weather data, enables companies to identify where renewable power generation devices should be installed, improving energy efficiency and power output. By including geographical information data from satellites or LiDAR (light detection and ranging), three-dimensional, spatial planning is possible.
Power Generation Planning
Leveraging the power of analytics, utility companies have the ability to improve their power planning. Identifying the two key decision-making processes in power generation,power planning and dispatching of the economic load, can be helpful. Energy demand decision-making gets easier as the amount of data increases. Once data is gathered from multiple sources, several models run on top of that data to arrive at power planning. When we say ‘economic load dispatch’, we are referring to matching energy demand with the optimal power supply from the grid over a specific time frame
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