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首页> 中文期刊> 《能源与动力工程》 >Artificial Intelligence Integration with Energy Sources (Renewable and Non-renewable)

Artificial Intelligence Integration with Energy Sources (Renewable and Non-renewable)

         
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In the past decade or so,AI(artificial intelligence)technology has been growing with such a mesmerizing speed that today its presence in almost any industry that deals with any huge sheer volume of data is taking advantage of AI by integrating it into their day-to-day operation.Meanwhile,seven billion people worldwide shape the world’s energy system and directly impact the fundamental drivers of energy,both renewable and non-renewable sources,to meet the demand for electricity from them.These energy sources can be reached from nature such as solar,wind,etc.,and human-made such as NPPs(nuclear power plants)in the form of either fission as an old technology since the Manhattan project and in the near future as fusion in the form of magnetic or inertial confinements.Meanwhile,AI controlling nuclear reactors are about to happen.The basic idea is to apply AI with its two subset components as ML(machine learning),and DL(deep learning)techniques to go through the mountains of data that come from a reactor,spot patterns in it,and calling them to the unit’s human attention operators is not invadable either.Designers of such nuclear reactors will combine simulation and real-world data,comparing scenarios from each to develop“confidence[in]what they can predict and what is the range of uncertainty of their prediction”.Adding that,in the end,the operator will make the final decisions in order to keep these power plants safe while they are in operation and how to secure them against cyber-attack natural or human-made disasters.In this short communication article,we would like to see how we can prove some of these concepts;then a NPP manufacturer can pick it up and use it in their designs of a new generation of these reactors.

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