Big Data and Utility Energy Management
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- Sep 22, 2020 4:06 pm GMTSep 22, 2020 3:15 pm GMT
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The way forward to greater efficiency
Big data analytics has the power to improve a number of areas in the power sector – including operations, decarbonization and energy efficiency as well as providing financial benefits.
Machine learning, A.I., Internet of Things (IoT), cloud computing, VR, robotics, distributed ledgers (i.e. blockchain applications) and cybersecurity are being investigated by utilities as potential game-changers. These will require substantial investments. The other thing they have in common is that they generate huge amounts of data. With more smart devices around, the data ocean is getting bigger and bigger.
Much of the utilities' infrastructure is becoming smart - meaning that it has built-in processing, connectivity, and sensor capabilities. Electric vehicles (EVs), smart home systems, grid management systems, and many more subsystems are likely to interface with utilities and provide them with large amounts of data, which is potentially valuable. But you can only do this is you have sufficient computing power and IT capabilities to use the information acquired effectively.
Failure Probability Modeling
Failure probability modeling is being used by a number of companies. By using machine learning algorithms for failure prediction, O & M costs can be reduced. Unexpected failures can have large cost implications, especially if they produce cascading effects throughout the grid.
Smart and Dynamic Energy Management
By using smart and dynamic systems, managing the load can be optimized. This covers all the conventional energy management principles concerning demand, distributed energy sources, and demand-side control, together with energy challenges like energy saving, demand reduction and temporary load. This of course requires advanced system operations.
Demand Response Management
Renewable energy sources have made this a tricky area for utilities – the key to competent energy management means balancing demand and supply. Both high and low demand rates generate plenty of problems and costs for both energy providers and consumers.
Specific real-time management applications and solutions using big data enable monitoring metrics of real-time energy use, and adjust the energy flow to the current demand rate. With smart consumer devices, management programs can encourage better energy use for the consumer, cutting peak demand while also saving money for the householder or business client.
Overall, utilities will need to move forward with the most promising types of advanced computing to ensure that they comply with government decarbonization initiatives, while also encouraging more efficient energy use by the consumer.