Robustness Assessment of Distributed Optimal Power Flow Under Communication Non-Idealities

In recent years, distributed optimal power flow (OPF) algorithms have found applications to distribution system operations. These algorithms decompose the system into small areas, each solving a local optimization problem and periodically sharing boundary variable values with neighbors. Unlike centralized approaches, the performance of distributed algorithms is significantly affected by non-ideal communication conditions. This article assesses the performance of a fast distributed algorithm, named Equivalent Network Approximation method (ENApp), for three-phase radial distribution system under four different non-ideal communication scenarios, erroneous data transfer, packet loss, additive noise effect, and communication delays. First, the paper proposes ENApp-based distributed OPF algorithms for normal and stressed main grid conditions. Communication non-idealities are considering the physical aspects of two widely used wide-area network mediums, viz. power line communication and optical fiber. The performance is evaluated using the IEEE 123 bus test system in a cyber-physical co-simulation environment based on the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS), providing insights into ENApp's robustness in terms of convergence time and success rate.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2024-12-27
DOI
https://doi.org/10.1109/tia.2024.3523463
Citations
4
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.83

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robustness Assessment of Distributed Optimal Power Flow Under Communication Non-Idealities

Anamika Dubey, Subho Paul, Nathan Gray, Anjan Bose et al.
4 citations
IEEE Transactions on Industry Applications
Optimal Power Flow Distribution
0.83
article

Robustness Assessment of Distributed Optimal Power Flow Under Communication Non-Idealities

Anamika Dubey, Subho Paul, Nathan Gray, Anjan Bose, James Ogle, Md Touhiduzzaman
article en
4 citations

Abstract

In recent years, distributed optimal power flow (OPF) algorithms have found applications to distribution system operations. These algorithms decompose the system into small areas, each solving a local optimization problem and periodically sharing boundary variable values with neighbors. Unlike centralized approaches, the performance of distributed algorithms is significantly affected by non-ideal communication conditions. This article assesses the performance of a fast distributed algorithm, named Equivalent Network Approximation method (ENApp), for three-phase radial distribution system under four different non-ideal communication scenarios, erroneous data transfer, packet loss, additive noise effect, and communication delays. First, the paper proposes ENApp-based distributed OPF algorithms for normal and stressed main grid conditions. Communication non-idealities are considering the physical aspects of two widely used wide-area network mediums, viz. power line communication and optical fiber. The performance is evaluated using the IEEE 123 bus test system in a cyber-physical co-simulation environment based on the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS), providing insights into ENApp's robustness in terms of convergence time and success rate.

IEEE Transactions on Industry ApplicationsVol. 61(2)
Pacific Northwest National Laboratory (US), Washington State University (US)
U.S. Department of Energy
Affordable and clean energy
Openalex Percentile: Top 26%
Optimal Power Flow Distribution
0.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.