Multiperiod DER Coordination using ADMM-based Three-Block Distributed AC Optimal Power Flow Considering Inverter Volt-Var Control

• Published in: IEEE transactions on smart grid 2023-07, Vol.14 (4), p.1-1
• Main Authors: Gebbran, Daniel, Mhanna, Sleiman, Chapman, Archie C., Verbic, Gregor
• Format: Article
• Language: English
• Subjects: Algorithms; Alternating Direction Method of Multipliers (ADMM); Australia; Control methods; Coordination; demand response; distributed energy resources (DER); Distributed generation; distributed optimal power flow (DOPF) Volt-Var control (VVC); Electric potential; Energy sources; Inverters; numerical oscillations; Optimization; Oscillators; Power flow; prosumers; Reactive power; Real-time systems; Robustness (mathematics); Slopes; Voltage; Voltage control
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2022.3227635

The uptake of behind-the-meter distributed energy resources (DER) raises the likelihood of voltage problems in low-voltage distribution networks. Network operators increasingly require solar inverters to provide reactive power support using Volt-Var control (VVC) to reduce voltage stress. However, VVC can cause instability in real-time control because of its instantaneous response to voltage deviations, which has been previously addressed using delayed control methods. Coincidentally, optimization-based multiperiod DER coordination faces a similar problem, where numerical oscillations can prevent the convergence of a distributed algorithm. This paper aims to fill this gap by proposing a distributed three-block algorithm, based on the alternating direction method of multipliers (ADMM), for solving the DER coordination problem using AC optimal power flow (OPF) with VVC constraints. This approach decomposes the network at the prosumer level, resulting in an aggregator, a prosumer, and a VVC block. A key feature of the proposed algorithm is the introduction of carefully tuned delays in the VVC block update to circumvent unstable numerical behavior. This novel approach is numerically demonstrated to solve the distributed OPF problem to feasible solutions with (i) objective function values within less than 2.5% compared to those from centralized computations for tractable cases, (ii) robustness against changes in load/generation profiles and steepness of VVC curves, and (iii) an algorithmic performance that scales linearly with an increase in network size.