The Convergence of Data and Automation in Utilities
Watch above as Casey Werth from IBM shares his thoughts on the intersection between Data, Security and Automation in the utilities world.
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In the utility industry, the intersection of automation, predictive analytics, data, and security has the potential to revolutionize the way utilities operate. Here are some key points to consider:
Automation of Usage and Load Shifting:
- Load shifting is the practice of adjusting the demand for electricity to match the available supply.
- Automation technologies, such as smart meters and sensors, are increasingly being used to automate load shifting, enabling utilities to manage peak demand more effectively and reduce energy costs.
- These technologies can also improve reliability and reduce the risk of blackouts by balancing the load across the grid.
Predictive Analytics:
- Predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.
- In the utility industry, predictive analytics can be used to forecast demand and optimize energy supply, enabling utilities to make more informed decisions about load shifting and energy management.
- This can lead to more efficient and reliable energy delivery, reduced energy costs, and improved customer satisfaction.
Data and Security:
- The automation and predictive analytics technologies used by utilities rely heavily on data, making data security a critical concern for utilities.
- Utilities must ensure that customer data is protected, and that their systems are secure against cyber threats.
- This requires robust security measures, such as data encryption, firewalls, and regular security audits, especially as decentralized grid technologies become more popular.
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