The Use of Constraint Programming for the Autonomous Management of Power Flows

摘要

This paper describes a novel network agnostic approach to the real-time management of power flows within MV distribution networks with a number of embedded generators. The approach in question uses the artificial intelligence technique of constraint programming to autonomously make decisions about how to manage a number of generators as part of a larger autonomous regional active network management system called AuRA-NMS. The results of testing using commercially available IEC 61850 compliant substation computing hardware, connected to a real-time simulator, are presented for two different case study networks: an interconnected 33kV network and an 11kV radial network. These results demonstrate the feasibility of the approach both in terms of its applicability to different network topologies and its real-time performance. The paper concludes by discussing the methodology for future testing which aims to assess the robustness of the approach against a number of other proposed approaches and the plans for field trials of the current prototype.