App Deconfliction: Orchestrating Distributed, Multi-Agent, Multi-Objective Operations for Power Systems

• Published in: IEEE access Vol. 11; pp. 40314 - 40327
• Main Authors: Reiman, Andrew P., Poudel, Shiva, Mukherjee, Monish, Anderson, Alexander A., Vasios, Orestis, Slay, Tylor E., Black, Gary D., Dubey, Anamika, Ogle, James P.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Advanced distribution operations; Algorithms; Behavioral sciences; Internet of Things; Low-carbon economy; Multiagent systems; Optimization; Pipelines; Power distribution; Power system management; Profitability; Resilience; solution design; Subsystems; system architecture
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3269422

Advanced distribution systems need to integrate and orchestrate intelligent subsystems and grid-edge devices that are increasing both in number and sophistication while also serving multiple system-level objectives such as resilience, decarbonization, equity, and profitability. A modular platform-based approach to distribution system operations technology enables operators to deploy a tailored set of best-of-breed algorithms and applications. Combined with the parallel deployment and control of intelligent grid-edge and internet of things devices, this creates a complex distributed-control environment with applications that span ownership boundaries. Conflicts can emerge between applications that want to control overlapping sets of device setpoints. We propose a formalized approach to resolving these conflicts that can be applied when integrating new algorithms or developing customized solutions. A Deconfliction Pipeline is inserted between the device-controlling applications and the device protocol converter, which transmits control setpoints from the operations platform to the devices. The Deconfliction Pipeline executes a process that sets up, solves, and acts on a formally defined deconfliction problem. The deconfliction problem can be solved using a combination of rules and heuristics, application engagement, and optimization. We demonstrate how a few of the most basic solution strategies can be used to orchestrate harmonious behavior between a pair of simple applications with conflicting greedy optimization objectives.