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Optimization techniques applied to planning of electric power distribution systems: a bibliographic survey

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Abstract

Optimization models for the solution of planning problems related to power distribution system (PDS) have been studied and used for decades. The main objective is to optimize investments and minimize total costs, including investment and operation costs. Some of the major concerns of the short-term expansion planning carried out by utilities are high energy losses, low power factor, and inadequate voltage magnitudes. A common solution to address these concerns and improve the performance of a PDS is the installation of capacitor banks (CBs) and voltage regulators (VRs). These devices can be installed at many different points along the PDS, leading to so-called optimal CB and VR allocation problems. Another common alternative is the replacement of conductors of feeders, which leads to the problem of optimal selection of conductors. These can be viewed as classical optimization problems regarding the PDS expansion. This paper presents a comprehensive survey of the models and methods used to solve planning problems of PDS expansion, the focus being on classical optimization problems. Furthermore, models including distributed energy resources in a modern power system era are discussed, showing future research possibilities and trends.

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Abbreviations

ABC:

Artificial Bee Colony

AC:

Ant Colony

BA:

Bat algorithm

BFA:

Bacterial foraging algorithm

CB:

Capacitor bank

CSA:

Cuckoo search algorithm

DE:

Differential evolution

DER:

Distributed energy resource

DG:

Distributed generation

DP:

Dynamic programming

ESS:

Energy storage systems

FPA:

Flower pollination algorithm

GA:

Genetic algorithm

GSA:

Gravitational search algorithm

HS:

Harmony search

IA:

Immune-based algorithm

IHA:

Improved Harmony algorithm

IMDE:

Intersect mutation differential evolution

MILP:

Mixed integer-linear programming

MINLP:

Mixed integer-nonlinear programming

MIQP:

Mixed integer quadratic programming

MS:

Monkey search

NSGA:

Nondominated sort genetic algorithm

OPF:

Optimal power flow

PABC:

Particle Artificial Bee Colony

PDS:

Power distribution system

PEV:

Plug-in electric vehicles

PGSA:

Plant growth simulation algorithm

PS:

Pattern search

PSO:

Particle swarm optimization

SA:

Simulated annealing

SOCP:

Second-order cone programming

SSO:

Shark smell optimization

TLBO:

Teaching learning based optimization

TS:

Tabu search

VR:

Voltage regulator

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Acknowledgements

Work of P.M. Pardalos is partially supported by the Paul and Heidi Brown Preeminent Professorship at ISE, University of Florida.

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  1. Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil

    Mariana Resener, Sérgio Haffner & Luís A. Pereira

  2. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

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Resener, M., Haffner, S., Pereira, L.A. et al. Optimization techniques applied to planning of electric power distribution systems: a bibliographic survey. Energy Syst 9, 473–509 (2018). https://doi.org/10.1007/s12667-018-0276-x

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