MS student Samuel Utomi with advisor A. Domínguez-García
There has been a proliferation of distributed energy resources (DERs) due to their reduced cost and the desire to increase grid infrastructure reliability and stability. This has led to the viable integration of decentralized generation and the need to find innovative control strategies to obtain optimal performance. While in large power systems generation control functions are centralized, integrating decentralized generation requires distributed control strategies, i.e., the generator makes control decisions using local information.
Our research focuses on development and implementation of this distributed control architecture in order to provide frequency regulation services to the bulk grid, while ensuring optimal dispatch of these DERs. With a group of DERs, collectively known as a microgrid, the goal is to use distributed control strategies to gain a system objective while keeping generator set points within limits. This is achieved by employing iterative algorithms that combine local measurements and certain information from neighboring generating units with local, low-complexity computations.
Figure 28 shows our testbed setup. Arduino Mega microprocessor controllers communicate wirelessly by using an XBee shield attached to each one. The lead controller receives a frequency regulation signal from the computer which it then distributes to the other controllers using the aforementioned algorithms. Once the algorithm is complete, controllers send the resulting reference signal tothe hardware-inthe-loop simulator. It contains a model of our microgrid that provides a set amount of power to the bulk grid, based on the regulation signal. This research is supported by Advanced Research Projects Agency-Energy (ARPA-E).