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University of Tennessee at Chattanooga

Distributed online algorithms for energy management in smart grids

Abstract

dc:description.abstract

The 21st-century electric power grid is transitioning from a centralized structure designed for bulk-power transfer to a distributed paradigm that integrates the variable renewable energy (VRE) resources spatially distributed across the grid. This work proposes algorithmic solutions for distributed economic dispatch based on Subgradient method and Alternating Direction Method of Multipliers (ADMM), both designed to be agnostic with any initialization vector. The proposed distributed online solutions leverage a dynamic average consensus algorithm to track the time-variant linearly coupled constraint that allows an abrupt change in power demand of the network because of the high penetration of VRE resources. The problems are modeled as discrete dynamic systems to investigate the stability and convergence of the algorithm. The update procedures are designed such that the iterates converge to the optimal solution of the original optimization problem, steered by the gain parameter corresponding to the second largest eigenvalue of the system matrix.

Degree

thesis:*
Grantor dc:publisher
University of Tennessee at Chattanooga
Year dc:date.available
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wasti, Shailesh
Contributors dc:contributor
  • Disfani, Vahid R.
  • Karrar, Abdelrahman A.; Ofoli, Abdul R.; Ahmed, Raga
  • College of Engineering and Computer Science

Subjects

dc:subject × 4

Rights

dc:rights
Language dc:language
English, eng

Identifiers

dc:identifier.*
Repository record dc:identifier
https://scholar.utc.edu/theses/684
OAI identifier oai:identifier
oai:scholar.utc.edu:theses-1845

Chain of custody

source
Harvested from
University of Tennessee - Chattanooga
Base URL
scholar.utc.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Wasti, Shailesh. Distributed online algorithms for energy management in smart grids. University of Tennessee at Chattanooga, 2021. https://scholar.utc.edu/theses/684