A Micro-Grid Distributed Intelligent Control and Management System

Micro-grids require active control to maintain quality of service and to interface with the power grid in a bi-directional manner. Further, micro-grids must be justified by environmental, governmental, and economic viability. We present a programmable architecture for active, optimal distributed control of elements of the grid to achieve desired behavior. A unique aspect of this architecture is to include a distributed inductive engine for learning the local dynamics of generators and loads in the micro-grid. It generates feedback laws that are adapted to the current status of the micro-grid, and responds to anomalous events in a resilient manner. An important novelty is that control laws are extracted online for bidirectional discontinuous nonlinear loads by mean field methods from physics outside the standard design methodologies for piecewise linear quadratic controls.