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Journal ArticleDOI

On Computational Issues of Market-Based Optimal Power Flow

TLDR
In this article, trust region based augmented Lagrangian method (TRALM), step-controlled primal-dual interior point method (SCIPM), and constrained cost variable (CCV) OPF formulation are proposed.
Abstract
The deregulated electricity market calls for robust optimal power flow (OPF) tools that can provide a) deterministic convergence; b) accurate computation of nodal prices; c) support of both smooth and nonsmooth costing of a variety of resources and services, such as real energy, reactive energy, voltages support, etc.; d) full active and reactive power flow modeling of large-scale systems; and e) satisfactory worst-case performance that meets the real-time dispatching requirement. Most prior research on OPF has focused on performance issues in the context of regulated systems, without giving much emphasis to requirements a)-c). This paper discusses the computational challenges brought up by the deregulation and attempts to address them through the introduction of new OPF formulations and algorithms. Trust-region- based augmented Lagrangian method (TRALM), step-controlled primal-dual interior point method (SCIPM), and constrained cost variable (CCV) OPF formulation are proposed. The new formulations and algorithms, along with several existing ones, are tested and compared using large-scale power system models.

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Journal ArticleDOI

MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education

TL;DR: The details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture, are presented, which are used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits.
Journal ArticleDOI

Zero Duality Gap in Optimal Power Flow Problem

TL;DR: In this article, a necessary and sufficient condition is provided to guarantee the existence of no duality gap for the optimal power flow problem, which is the dual of an equivalent form of the OPF problem.
Journal ArticleDOI

Pandapower—An Open-Source Python Tool for Convenient Modeling, Analysis, and Optimization of Electric Power Systems

TL;DR: Pandapower is a Python-based BSD-licensed power system analysis tool aimed at automation of static and quasi-static analysis and optimization of balanced power systems and allows comfortable extension with third-party libraries.
Journal ArticleDOI

Optimal power flow: a bibliographic survey I

TL;DR: Optimal power flow (OPF) has become one of the most important and widely studied nonlinear optimization problems as mentioned in this paper, and there is an extremely wide variety of OPF formulations and solution methods.
Journal ArticleDOI

State-of-the-art, challenges, and future trends in security constrained optimal power flow

TL;DR: In this paper, the main challenges to the security constrained optimal power flow (SCOPF) computations are discussed, focusing mainly on: approaches to reduce the size of the problem by either efficiently identifying the binding contingencies and including only these contingencies in the SCOPF or by using approximate models for the post-contingency states, and the handling of discrete variables.
References
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Book

Practical Methods of Optimization

TL;DR: The aim of this book is to provide a Discussion of Constrained Optimization and its Applications to Linear Programming and Other Optimization Problems.
Book

Nonlinear Programming: Theory and Algorithms

TL;DR: The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques.
Journal ArticleDOI

An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds

TL;DR: In this paper, a trust region approach for minimizing nonlinear functions subject to simple bounds is proposed, where the trust region is defined by minimizing a quadratic function subject only to an ellipsoidal constraint and the iterates generated by these methods are always strictly feasible.
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