Work

A Distributed Model Identification Algorithm for Multi-Agent Systems: Preprint

Year: 2024

Type: article

Abstract: In this study, we investigate agent-based approach for system model identification with emphasis on power distribution system applications. Departing from conventional practices of relying on historical data for offline model identification, we adopt online update approach utilizing real-time data by employing the latest data points for gradient computation. This methodology offers advantages including a large reduction in the communication network's bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt in real-time to disturbances. Furthermore, we extend our model identification process from linear frameworks to more complex non-linear convex models. This extension is validated through numerical studies demonstrating improved control performance for a synthetic IEEE test case.

Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)

Author: Khatana, Vivek; Chang, Chin-Yao; Wang, Wenbo

Institution: National Laboratory of the Rockies

Language: English

Topic: Power System Optimization and Stability

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: green

Funders: U.S. Department of Energy, Office of Electricity, National Renewable Energy Laboratory