Stability Quantification for Consensus-Based Power Flow Control between Transmission and Distribution Power Systems

Journal Article · 14 December 2021 · Proceedings of the IEEE Conference on Decision & Control (Online)

DOI: https://doi.org/10.1109/cdc45484.2021.9683682 · OSTI ID:2324948

Xue, Nan ^[1]; Muenz, Ulrich ^[2]; Qu, Zhihua ^[3]; Sun, Wei ^[3]

---

1. Siemens Technology, Princeton, NJ (United States); University of Central Florida
2. Siemens Technology, Princeton, NJ (United States)
3. Univ. of Central Florida, Orlando, FL (United States)

With increasing integration of distributed energy resources (DERs), distribution systems (DS) with DERs are expected to provide proactive grid services. The result is that power references, or known as dispatch signals, required for DS can become faster changing than in legacy power system. Consensus-based integral controls have been proposed for the purpose of coordinating power generations of DERs in DS to match the power references. These existing controls assume the integral control signal to be sufficiently slow or constant, and ignore the potential dynamics of the integral controller when tracking more varying power references. Therefore, in this paper we present an improvement for such controls by deriving the stability condition utilizing generalized Nyquist criterion. The stability condition is quantified by a set of integral gains that guarantee stability in closed-loop system without assuming a constant integral signal. A rule-of-thumb criterion is also derived to instruct the design of the consensus topology that can provide faster convergence rate for the closed-loop system. Here, the stability and convergence improvements developed in this paper are demonstrated and verified through numerical examples.

• Research Organization: Univ. of Central Florida, Orlando, FL (United States)
• Sponsoring Organization: USDOE Office of Science (SC); USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• Grant/Contract Number: EE0009028; EE0007998
• OSTI ID: 2324948
• Journal Information: Proceedings of the IEEE Conference on Decision & Control (Online), Journal Name: Proceedings of the IEEE Conference on Decision & Control (Online) Vol. 2021; ISSN 2576-2370
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English