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Network Reduction for Optimal Power Flow Problems


M. Fetzner

Semester Thesis, HS15 (10466)

By the large penetration of decentralized renewable energy sources, the uncertainty of the net load demand has increased in recent years. In order to cope with this challenge, governments enforce the expansion of supervisory control and data acquisition (SCADA) systems, better known in this context as smart grids. For the economic efficiency of such systems precise and fast optimal power ow (OPF) solvers are essential. This thesis provides advances in computational performance of AC-OPF by integrating a preprocessing routine into the solver. The idea behind the routine is to eliminate the uncontrollable load nodes of the power grid with Kron Reduction. Thereby, the characteristic of power grids to have few controllable nodes is exploited. Specifically, a semidefinite programming (SDP) relaxation of the nonconvex AC-OPF problem is regarded. It is shown, that under the assumption of constant impedance loads, the number of problem variables can be reduced significantly. In the next step, the validity of the Kron Reduction for general power networks is discussed and characteristics of the reduced admittance matrices are investigated. On the basis of different standard and real-life test cases, the computational performance of the OPF problem with and without the network reduction is compared and analyzed.

Supervisors: Adrian Hauswirth, Sandro Merkli, Florian Dörfler


Type of Publication:

(13)Semester/Bachelor Thesis

F. Dörfler

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2016:IFA_5373
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