Energy Systems

, Volume 3, Issue 3, pp 259–289 | Cite as

Optimal power flow: a bibliographic survey II

Non-deterministic and hybrid methods
  • Stephen Frank
  • Ingrida Steponavice
  • Steffen Rebennack
Original Paper

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.

Keywords

Electric power systems Optimal power flow Non-deterministic optimization Stochastic search Hybrid methods Heuristics Global optimization Survey 

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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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Stephen Frank
    • 1
  • Ingrida Steponavice
    • 2
  • Steffen Rebennack
    • 3
  1. 1.Department of Electrical Engineering and Computer ScienceColorado School of MinesGoldenUSA
  2. 2.AgoraFinland
  3. 3.Division of Economics and BusinessColorado School of MinesGoldenUSA

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