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
- Anamika Dubey (ORCID: https://orcid.org/0000-0001-5147-9961)
- Subho Paul (ORCID: https://orcid.org/0000-0002-7242-5652)
- Nathan Gray (ORCID: https://orcid.org/0009-0008-0234-7207)
- Anjan Bose (ORCID: https://orcid.org/0000-0002-8854-5712)
- James Ogle (ORCID: https://orcid.org/0000-0002-9654-5448)
- Md Touhiduzzaman (ORCID: https://orcid.org/0000-0003-0487-3709)
Institutions
- Pacific Northwest National Laboratory (US)
- Washington State University (US)
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
- U.S. Department of Energy