Distributed AC Optimal Power Flow using ALADIN * *TF is indebted to the Baden-Württemberg Stiftung for the financial support of this research by the Elite Programme for Postdocs. TF and BH are supported by the Deutsche Forschungsgemeinschaft, Grants WO 2056/1 and WO 2056/4-1. YJ and BH are supported by the National Natural Science Foundation China (NSFC), Nr. 61473185, as well as ShanghaiTech University, Grant-Nr. F-0203-14-012. This work was also supported by the Helmholtz Association under the Joint Init

Engelmann, Alexander; Mühlpfordt, Tillmann; Jiang, Yuning; Houska, Boris; Faulwasser, Timm

doi:10.1016/j.ifacol.2017.08.1095

Cited by 18 publications

(3 citation statements)

References 23 publications

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“…However, the resulting optimization problem is again nonconvex, which makes it much harder to solve. The development of algorithms for this problem is an active field of research; see Erseghe (2014) and Engelmann et al (2017).…”

Section: B Optimal Power Flowmentioning

confidence: 99%

Collective nonlinear dynamics and self-organization in decentralized power grids

et al. 2022

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The ongoing transition to renewable energy supply comes with a restructuring of power grids, changing their effective interaction topologies, more and more strongly decentralizing them and substantially modifying their input, output, and response characteristics. All of these changes imply that power grids become increasingly affected by collective, nonlinear dynamic phenomena, structurally and dynamically more distributed and less predictable in space and time, more heterogeneous in its building blocks, and as a consequence less centrally controllable. Here cornerstone aspects of datadriven and mathematical modeling of collective dynamical phenomena emerging in real and model power grid networks by combining theories from nonlinear dynamics, stochastic processes and statistical physics, anomalous statistics, optimization, and graph theory are reviewed. The mathematical background required for adequate modeling and analysis approaches is introduced, an overview of power system models is given, and a range of collective dynamical phenomena are focused on, including synchronization and phase locking, flow (re)routing, Braess's paradox, geometric frustration, and spreading and localization of perturbations and cascading failures, as well as the nonequilibrium dynamics of power grids, where fluctuations play a pivotal role.

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Section: B Optimal Power Flowmentioning

confidence: 99%

Collective nonlinear dynamics and self-organization in decentralized power grids

et al. 2022

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“…Distributed control : Requires higher investments, a distributed consensus is performed between all the distributed generators in order to operate (together) optimally the grid, it is more reliable since it could operate even if a given communication line (or DG) goes out of operation (known as single-point failure) (Engelmann et al, 2019(Engelmann et al, , 2017.…”

Section: Tertiary Controlmentioning

confidence: 99%

Optimal Operation of Active Distribution Networks

2024

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“…6 and 7. We assume quadratic generator cost functions as in [18] (see Table 3) and one Algorithm 1 ADMM 1: Initialization: Weighting matrix W , tolerance ; for all k ∈ R: initial guesses z k , penalty parameters ρ k = ρ, dual variables λ k = 0, local solutions x k = ∞, local residues Γ k = ∞. 2: while ||Ax|| ∞ > and ||x − z|| ∞ > do 3:…”

Section: Test Scenariomentioning

confidence: 99%

Multi-area Coordination of Security-Constrained Dynamic Optimal Power Flow in AC-DC Grids with Energy Storage

Huebner

Schween

Suriyah

et al. 2019

Trends in Mathematics

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In times of growing integrated electricity markets and needed coordination of large interregional physical power flows, multi-area Optimal Power Flow (OPF), also referred to as distributed OPF, has gained importance in research. However, the conventional OPF is only of limited use since a TSO is strongly interested in N-1 security. Furthermore, time-dependent constraints such as generator ramping or energy storage limits play a growing role. Consequently, a Security-Constrained Dynamic OPF (SC-D-OPF) includes both N-1 security and quasi-stationary dynamics. We present a decoupling approach to compute an SC-D-OPF by coordination among interconnected areas. Privacy is maintained by implementing an Alternating Direction of Multipliers Method (ADMM), where only results of boundary variables are exchanged with a neighbor. We show the functionality of the approach in a small test case, where the distributed result is close to that of a centralized optimization.

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Cited by 18 publications

References 23 publications

Collective nonlinear dynamics and self-organization in decentralized power grids

Collective nonlinear dynamics and self-organization in decentralized power grids

Optimal Operation of Active Distribution Networks

Multi-area Coordination of Security-Constrained Dynamic Optimal Power Flow in AC-DC Grids with Energy Storage

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