A Convex Solution-Sequential Linear Programming Methodology for the Quadratized-OPF Problem

Modernization of the economic function in the operating center cand result in improved reliability as well as economic savings for power system operators. Specifically, the development of accurate and computationally efficient methods for formulating and solving the alternative current optimal power...

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Vydané v:IEEE Power & Energy Society General Meeting s. 1 - 5
Hlavní autori: Ilunga, Gad, Sakis Meliopoulos, A. P.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 16.07.2023
Predmet:
Convex relaxations
Economics
Linear programming
Mathematical models
Object oriented modeling
Optimal Power Flow (OPF)
Power system reliability
Runtime
Sequential Linear Programming (SLP)
Syntactics
ISSN:1944-9933
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Shrnutí:Modernization of the economic function in the operating center cand result in improved reliability as well as economic savings for power system operators. Specifically, the development of accurate and computationally efficient methods for formulating and solving the alternative current optimal power flow (ACOPF) problem. In this paper, we utilize the Q-ACOPF formulation, which is an object-oriented quadratized formulation based on rigorous physically based mathematical modeling of the modern power system. The mathematical objects of power systems components are cast into a universal syntax that consists of linear and quadratic equations, the Quadratized Device Model (QDM) syntax. The optimization problem is constructed in an objected oriented fashion by operating solely on the component QDMs; the resulting problem consists of constraints that are at most quadratic with a quadratic objective function; hence why it is named Quadratic-OPF. We propose a convex solution-sequential linear programming (CS-SLP) approach for the solution of the Q-OPF. We introduce a generalized convexification method and apply it to the Q-OPF. The two-step CS-SLP algorithm leverages commercial convex solvers, such as Gurobi, as well as LP solvers to efficiently obtain an optimal and feasible solution. We compare the results with those obtained from mature convex formulations QC and SOC (implemented in PowerModel.js) on a five systems.
ISSN:1944-9933
DOI:10.1109/PESGM52003.2023.10252171