Distributed Real-Time OPF and State Estimation Architecture for Active Distribution Networks

This work proposes an online distributed control architecture that utilizes dynamic optimal power flow (DOPF) and time of use energy prices alongside state estimation and linearized AC-power flow to ensure optimal and safe operation of active distribution networks, where distributed energy resources (DERs) are embedded. The DOPF problem is formulated as Mixed-Integer Non-linear Programming (MINLP) to maximize the net profit of an active distribution network assuming different buying and selling time of use energy prices. After that the DOPF formulation is relaxed to a non-linear programming problem to be solved with off-the-shelf solvers like IPOPT. The proposed framework is introduced showing how the algorithms are distributed between the cloud and edge devices to allow online control of distribution networks. Finally, the proposed control architecture is validated using real data from a distribution grid located in Spain.