Network-Level Optimization for Unbalanced Power Distribution System: Approximation and Relaxation

The nonlinear programming (NLP) problem to solve distribution-level optimal power flow (D-OPF) poses convergence issues and does not scale well for unbalanced distribution systems. The existing scalable D-OPF algorithms either use approximations that are not valid for an unbalanced power distributio...

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Veröffentlicht in:	IEEE transactions on power systems Jg. 36; H. 5; S. 4126 - 4139
Hauptverfasser:	Jha, Rahul Ranjan, Dubey, Anamika
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.09.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation Approximation algorithms conic constraints current operating point D-OPF solution distribution-level optimal power flow Electric power distribution equivalent NLP D-OPF model feasible power flow solution Flow equations Iterative second order cone programming Linear programming linear programming problem Load flow Mathematical model multiple iterations network-level optimization nonlinear power flow equations Nonlinear programming nonlinear programming problem Optimization Power distribution Power flow POWER TRANSMISSION AND DISTRIBUTION scalable D-OPF algorithms second-order cone programming problem SOCP problem successive linear approximation successive linear programming Three-phase electric power three-phase optimal power flow Unbalance unbalanced power distribution system
ISSN:	0885-8950, 1558-0679
Online-Zugang:	Volltext
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