摘要：In modern power systems, a variety of both objects and the tools of control is expected to be much larger than before. As a result, the dynamic properties of these systems are complicated, and the issues of maintaining stability come to the fore. The paper provides a brief overview of the types of stability, including those that, until recently, were considered local in the electric power systems of Russia. It is shown that in today’s conditions the violation of these types of stability affects the operation of the electric power system as a whole. Therefore, the coordination of control of both normal and emergency modes of the systems takes on a special role and should become more intelligent. In this regard, a brief overview of machine learning developments of control agents at different levels of the control hierarchy is presented.
其他摘要：In modern power systems, a variety of both objects and the tools of control is expected to be much larger than before. As a result, the dynamic properties of these systems are complicated, and the issues of maintaining stability come to the fore. The paper provides a brief overview of the types of stability, including those that, until recently, were considered local in the electric power systems of Russia. It is shown that in today’s conditions the violation of these types of stability affects the operation of the electric power system as a whole. Therefore, the coordination of control of both normal and emergency modes of the systems takes on a special role and should become more intelligent. In this regard, a brief overview of machine learning developments of control agents at different levels of the control hierarchy is presented.
