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Energy Management of an Active Distribution Network Considering Correlation Between Uncertain Input Variables

  • Research Article-Electrical Engineering
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Abstract

This paper deals with the probabilistic energy management of an active distribution network in the presence of plug-in hybrid electric vehicle loads and power electronic devices like the soft open point and the smart transformer. The energy management scheme aims to simultaneously reduce the average voltage deviation, improve voltage stability, and maximize the daily profit. The proposed energy management measures involve simultaneous optimal scheduling of the soft open point, the smart transformer, the battery energy storage system, and an optimal power procurement from renewable sources. A probabilistic method models input uncertainties (load, renewable generation, plug-in hybrid electric vehicle charging load, and grid energy price). The correlation between uncertain input variables is incorporated by modifying the “Hong’s 2m point estimate method”. The multi-objective optimization problem is solved using a normalized weighted average technique. Simulation studies on a 33-bus active distribution network elucidate the benefits of the proposed approach. The expected daily profit improves by \(\sim 2.95\%\), the voltage stability by \(\sim 17.94 \%\), and the average voltage deviation reduces by \(\sim 75\%\) with the energy management approach presented in this paper. To validate the proposed method of solving a multi-objective problem, the combined objective has also been solved using the ubiquitous “controlled elitist genetic algorithm” of the MATLAB toolbox. The optimal solution yielded by the weighted sum method lies on the Pareto front obtained by the controlled elitist genetic algorithm.

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Abbreviations

ADN:

Active distribution network

AVD:

Average voltage deviation

BESS:

Battery energy storage system

DDP:

Discrete dynamic programming

DG:

Distributed generation

DNO:

Distribution network operator

EV:

Electric vehicles

IC:

Internal combustion

LA:

Lead-acid

Li-ion:

Lithium-ion

LSC:

Load side converter

MG:

Microgrid

NaS:

Sodium-sulphur

pdf:

Probability density functions

PE:

Power electronic

PEM:

Point estimate method

PHEV:

Plug-in hybrid vehicles

POPF:

Probabilistic optimal power flow

PPFP:

Probabilistic power flow program

PSG:

SPG active power output

PSO:

Particle swarm optimization

PV:

Photovoltaic

PWG:

WPG power output

SOC:

State of charge

SOP:

Soft open points

SPG:

Solar photovoltaic generator

ST:

Smart transformer

TCPD:

Total cost per day

VSCs:

Voltage source converters

VSI:

Voltage stability index

WPG:

Wind power generator

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  1. Department of Electrical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, 221005, India

    Abhishek Singh & Avirup Maulik

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  1. Abhishek Singh
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Singh, A., Maulik, A. Energy Management of an Active Distribution Network Considering Correlation Between Uncertain Input Variables. Arab J Sci Eng 48, 6377–6398 (2023). https://doi.org/10.1007/s13369-022-07379-z

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