800 research outputs found
Distributed Power Flow and Distributed Optimization - Formulation, Solution, and Open Source Implementation
Solving the power flow problem in a distributed fashion empowers different
grid operators to compute the overall grid state without having to share grid
models-this is a practical problem to which industry does not have
off-the-shelf answers. In cooperation with a German transmission system
operator we propose two physically consistent problem formulations
(feasibility, least-squares) amenable to two solution methods from distributed
optimization (the Alternating direction method of multipliers (ADMM), and the
Augmented Lagrangian based Alternating Direction Inexact Newton method
(Aladin)); with Aladin there come convergence guarantees for the distributed
power flow problem. In addition, we provide open source matlab code for rapid
prototyping for distributed power flow (rapidPF), a fully matpower-compatible
software that facilitates the laborious task of formulating power flow problems
as distributed optimization problems; the code is available under
https://github.com/KIT-IAI/rapidPF/. The approach to solving distributed power
flow problems that we present is flexible, modular, consistent, and
reproducible. Simulation results for systems ranging from 53 buses (with 3
regions) up to 4662 buses (with 5 regions) show that the least-squares
formulation solved with aladin requires just about half a dozen coordinating
steps before the power flow problem is solved.Comment: 35 pages, 6 figures, 7 tables, journal submissio
Distributed AC Optimal Power Flow for Generic Integrated Transmission-Distribution Systems
Coordination of transmission and distribution power systems is increasingly critical in the context of the ongoing energy transition. However, traditional centralized energy management faces challenges related to privacy and/or sovereignty concerns, leading to growing research interests in distributed approaches. Nevertheless, solving distributed AC optimal power flow (OPF) problems encounters difficulties due to their nonlinearity and nonconvexity, making it challenging for state-of-the-art distributed approaches. To solve this issue, the present paper focuses on investigating the distributed AC OPF problem of generic integrated transmission-distribution (ITD) systems, considering complex grid topology, by employing a new variant of the Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN). In contrast to the standard ALADIN, we introduce a second-order correction into ALADIN to enhance its numerical robustness and properly convexify distribution subproblems within the ALADIN framework for computing efficiency. Moreover, a rigorous proof shows that the locally quadratic convergence rate can be preserved for solving the resulting distributed nonconvex problems. Extensive numerical simulations with varying problem sizes and grid topologies demonstrate the effectiveness of the proposed algorithm, outperforming state-of-the-art approaches in terms of numerical robustness, convergence speed, and scalability
Distributed Optimization with Application to Power Systems and Control
Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized—all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization
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