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Year by year control of normal and emergency conditions of up-to-date powersystems becomes an increasingly complicated problem. With the increasingcomplexity the existing control system of power system conditions whichincludes operative actions of the dispatcher and work of special automaticdevices proves to be insufficiently effective more and more frequently, whichraises risks of dangerous and emergency conditions in power systems. The paperis aimed at compensating for the shortcomings of man (a cognitive barrier,exposure to stresses and so on) and automatic devices by combining their strongpoints, i.e. the dispatcher's intelligence and the speed of automatic devicesby virtue of development of the intelligent system "Artificial dispatcher" onthe basis of deep machine learning technology. For realization of the system"Artificial dispatcher" in addition to deep learning it is planned to attractthe game theory approaches to formalize work of the up-to-date power system asa game problem. The "gain" for "Artificial dispatcher" will consist in bringingin a power system in the normal steady-state or post-emergency conditions bymeans of the required control actions.

The Concept of the Deep Learning-Based System "Artificial Dispatcher" to Power System Control and Dispatch