Model-based Integration of Constrained Search Spaces into Distributed Planning of Active Power Provision

Jorg Bremer, Michael Sonnenschein

The current upheaval in the electricity sector demands distributed generation schemes that take into account individually configured energy units and new grid structures. At the same time, this change is heading for a paradigm shift in controlling these energy resources within the grid. Pro-active scheduling of active power within a (from a controlling perspective) loosely coupled group of distributed energy resources demands for distributed planning and optimization methods that take into account the individual feasible region in local search spaces modeled by surrogate models. We propose a method that uses support vector based black-box models for re-constructing feasible regions for automated, local solution repair during scheduling and combine it with a distributed greedy approach for finding an appropriate partition of a desired target schedule into operable schedules for each participating energy unit.