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Optimal power flow: a bibliographic survey II

Non-deterministic and hybrid methods

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Abstract

Over the past half-century, Optimal Power Flow (OPF) has become one of the most important and widely studied nonlinear optimization problems. In general, OPF seeks to optimize the operation of electric power generation, transmission, and distribution networks subject to system constraints and control limits. Within this framework, however, there is an extremely wide variety of OPF formulations and solution methods. Moreover, the nature of OPF continues to evolve due to modern electricity markets and renewable resource integration. In this two-part survey, we survey both the classical and recent OPF literature in order to provide a sound context for the state of the art in OPF formulation and solution methods. The survey contributes a comprehensive discussion of specific optimization techniques that have been applied to OPF, with an emphasis on the advantages, disadvantages, and computational characteristics of each. Part I of the survey provides an introduction and surveys the deterministic optimization methods that have been applied to OPF. Part II of the survey (this article) examines the recent trend towards stochastic, or non-deterministic, search techniques and hybrid methods for OPF.

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Abbreviations

AC:

Alternating Current

ACO:

Ant Colony Optimization

AIS:

Artificial Immune Systems

ANN:

Artificial Neural Network

BFA:

Bacterial Foraging Algorithm

COA:

Chaos Optimization Algorithm

DBFA:

Dynamic Bacterial Foraging Algorithm

DC:

Direct Current

DE:

Differential Evolution

EA:

Evolutionary Algorithm

EP:

Evolutionary Programming

FACTS:

Flexible AC Transmission Systems

GA:

Genetic Algorithm

IA:

Immune Algorithm

IPM:

Interior Point Method

KKT:

Karush-Kuhn-Tucker (conditions for optimality)

LP:

Linear Programming

MINLP:

Mixed Integer-Nonlinear Programming

NLP:

Nonlinear Programming

NN:

Neural Network

OPF:

Optimal Power Flow

ORPF:

Optimal Reactive Power Flow

PC:

Predictor-Corrector

PDIPM:

Primal-Dual Interior Point Method

PSO:

Particle Swarm Optimization

SA:

Simulated Annealing

SCED:

Security-Constrained Economic Dispatch

SLP:

Sequential Linear Programming

SQP:

Sequential Quadratic Programming

TS:

Tabu Search

UPFC:

Unified Power Flow Controller

VAR:

Volt-Ampere Reactive

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  1. Department of Electrical Engineering and Computer Science, Colorado School of Mines, 1500 Illinois St., Golden, CO, 80401, USA

    Stephen Frank

  2. P.O. Box 35, Agora, 40014, Finland

    Ingrida Steponavice

  3. Division of Economics and Business, Colorado School of Mines, 1500 Illinois St., Golden, CO, 80401, USA

    Steffen Rebennack

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Frank, S., Steponavice, I. & Rebennack, S. Optimal power flow: a bibliographic survey II. Energy Syst 3, 259–289 (2012). https://doi.org/10.1007/s12667-012-0057-x

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