AI is booming, with machines that can recognise patterns or rules and provide an automated response becoming increasingly popular across a range of industries, from retail to financial services.
For years, software company NeuCo have been developing optimisation technologies – a form of artificial intelligence (AI) – that can make power plants more efficient. This will enable computers to monitor the hundreds of fine-grained controls that may be altered in, for example, a coal-fired power plant, and learn how to adjust them in a more effective way.
Human operators in such facilities are tasked with overseeing all kinds of minutiae, such as the level of oxygen in the furnace, the frequency of the soot blowers that keep tubes in the system clean, or the build-up of slag that, if left unchecked, can grow into huge boulders ready to break off and wreck the equipment.
Peter Kirk, former chief executive of NeuCo states “There’s too much data and it overwhelms the human ability to respond; instead, a computer can take over. Machine learning allows software to identify small changes that improve the efficiency and stability of the coal-firing system. The result” Mr Kirk says, “is sometimes an efficiency improvement of about 1%. That might not sound like much, but coal power plants are massive carbon emitters. I mean, that’s 1,000 cars coming off the road”.
GE Power plans to develop this technology, which has already been used in many plants around the world. They also plan to use similar technology with wind turbines. The idea is to better predict the likely output from turbines, based on weather patterns, so that maintenance days can be more accurately scheduled for times when they are less likely to be operational.
Computer Science and Engineering students should further explore how AI is being used in a range of industries and the challenges involved in programming. PPE students should consider the philosophical and economic debates around the use and impact of artificial intelligence. Psychology students should explore whether we can ever fully replicate the human brain and the ethical issues linked to this.
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