Project Description

Distributed energy resources (DERs) in the power grid refer to rooftop photovoltaic (PV), stationary or mobile battery energy storage (e.g. Tesla power wall batteries and electrical vehicles), as well as smart loads (e.g. controllable heaters and air conditioners) at the customer sites. As the adoption of DERs continues to increase, an electric system with high penetration of DERs can offer tremendous advantage over the traditional power system, with higher efficiency, less power conversion stages, smaller footprint, and higher reliability and resiliency. However, the existing grid is not designed to accommodate the large penetration of DERs. This is because as energy prosumers, DERs require both control and information technology (CIT) and bidirectional energy infrastructures to enable them to consume and produce energy safely and reliably. The inherent intermittent characteristics of DERs and the need to optimize for economic incentives further complicate the operation and control of the traditional power grid. Control algorithms in the forms of centralized, decentralized, hierarchical, and full-distributed fashions have been proposed to integrate DERs into the power grid, but challenges of growing complexity, scalability and reliability remain. In particular, an outstanding problem is that there is a limited understanding of how practical communication and computational performance affects the real-time resiliency and scalability of the proposed DER control algorithms. To this end, the proposed project will conduct a comprehensive and systematic grid-edge control and characterization study, with the following tasks:

  • Task1: Identify and integrate an existing OpenDSS and NS3 models of an IEEE distribution test feeder with high penetration of DERs;

  • Task2: Implement existing decentralized, hierarchical or full-distributed control algorithms in the HPC and HELICS co-simulation platform;

  • Task3: Case study on reliability and scalability evaluation.

Selected students are expected to have a mixed background, or at least a strong interest in developing their skills, in power systems, computer networks, and HPC coding. Selected students are expected to be fast hands-on as well as collaborative learners.