machine-learning

Clustering Data-driven Local Control Schemes in Active Distribution Grids

Controllable Distributed Energy Resources (DERs) in Active Distribution Grids (ADGs) provide operational flexibility to system operators thereby offering the means to address various challenges. Existing local controllers for these resources are …

Data-driven Power System Methods

Research in the area of machine learning for power system applications

Data-Driven Local Control Design for Active Distribution Grids Using Off-Line Optimal Power Flow and Machine Learning Techniques

The optimal control of distribution networks often requires monitoring and communication infrastructure, either centralized or distributed. However, most of the current distribution systems lack this kind of infrastructure and rely on sub-optimal, …

Data-driven Control Design Schemes in Active Distribution Grids: Capabilities and Challenges

Today, system operators rely on local control of distributed energy resources (DERs), such as photovoltaic units, wind turbines and batteries, to increase operational flexibility. These schemes offer a communication-free, robust, cheap, but rather …