PROJECT TITLE :

Data-driven Coordination of Distributed Energy Resources for Active Power Provision

ABSTRACT:

Distributed energy resources (DERs) that are connected to a power distribution system whose model is not completely known can be coordinated to provide a specified amount of active power to the bulk power system while respecting distribution line capacity limits, according to a framework in this paper. Modeling the relationship between DER active power injections and total active power exchanged between the distribution and bulk power systems, an estimator that aims to estimate the IO model parameters, and a controller that determines optimal DER power injections so that the power exchanged between both systems equals the specified amount are the components of the proposed framework. The projected gradient descent approach is used to solve the quadratic programming problem we've formulated. During the estimate phase, we incorporate random perturbations in the active power injections of the DER to resolve the issue of collinearity. Convex optimization can be used to solve the problem of optimal DER coordination by the controller, which can be simply expressed using the approximated IO model. Using the IEEE 123-bus distribution test feeder, the framework's effectiveness is tested numerically.