Olaoluwapo Ajala with adviser A. Domínguez-García
During the last decade, we have developed numerous control algorithms for distribution network applications that rely on a distributed decision-making approach wherein control decisions pertaining to individual assets in the microgrid are based on information acquired locally and other information obtained by exchanges with other nearby assets. Through these efforts, we have shown that the distributed decision-making approach has the potential for realizing, in a scalable fashion, all the control functions that are necessary for stable, reliable, and resilient microgrid operation. The objectives of this next phase of research are then:
1. To develop detailed models of power system distribution networks, with their associated lower level controls, and implement these models on a real-time simulation platform.
2. Develop reduced-order counterparts for these distribution network using singular perturbation techniques and determine the root mean square error of the model’s response.
3. Synthesize the distributed control algorithms for which we have established solid theoretical foundations into a microcontroller hardware platform.
4. Utilize our real-time simulation platform and the microcontroller hardware platform to develop a controller hardware in the loop (C-HIL) laboratory for testing and validation of distributed control architectures.
The ﬁnal research deliverable is an industrial-grade control node prototype that integrates numerous distributed control algorithms. By using our C-HIL laboratory (see Figure 21), we will demonstrate that using a collection of such devices to control the assets of a microgrid provides a plug-and-play control platform that is robust and resilient. In the process, we will also demonstrate that such a control platform provides a cost-effective solution for promoting a seamless interconnection and interoperability of multiple power system assets, as well as enabling a plug-and-play expansion of an existing distribution network. This research is funded by the Department of Defense, Environmental Security Technology Certification Program.