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Andreas Grothey
Researcher at University of Edinburgh
Publications - 45
Citations - 1294
Andreas Grothey is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Interior point method & Stochastic programming. The author has an hindex of 18, co-authored 44 publications receiving 1135 citations. Previous affiliations of Andreas Grothey include University of Dundee.
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Local Solutions of the Optimal Power Flow Problem
TL;DR: In this paper, local optima can occur because the feasible region is disconnected and/or because of nonlinearities in the constraints, and the standard local optimization techniques are shown to converge to these locally optimal solutions.
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Optimization-Based Islanding of Power Networks Using Piecewise Linear AC Power Flow
TL;DR: A flexible optimization-based framework for intentional islanding is presented that provides islands that are balanced in real and reactive power, satisfy AC power flow laws, and have a healthy voltage profile.
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Exploiting structure in parallel implementation of interior point methods for optimization
Jacek Gondzio,Andreas Grothey +1 more
TL;DR: OOPS is an object-oriented parallel solver using the primal–dual interior point methods to exploit nested block structure that is often present in truly large-scale optimization problems such as those appearing in Stochastic Programming.
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MILP formulation for controlled islanding of power networks
TL;DR: In this paper, a mixed integer linear programming (MILP) formulation is given for the problem of deciding simultaneously on the boundaries of the islands and adjustments to generators, so as to minimize the expected load shed while ensuring no system constraints are violated.
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Parallel interior-point solver for structured quadratic programs: Application to financial planning problems
Jacek Gondzio,Andreas Grothey +1 more
TL;DR: A object-oriented parallel solver that can be used to exploit virtually any nested block structure arising in practical problems, eliminating the need for highly specialised linear algebra modules needing to be written for every type of problem separately is presented.