Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm

In this paper, power distribution planning (PDP) considering distributed generators (DGs) is investigated as a dynamic multi-objective optimization problem. Moreover, Monte Carlo simulation (MCS) is applied to handle the uncertainty in electricity price and load demand. In the proposed model, invest...

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Main Authors: A. Rastgou, J. Moshtagh, S. Bahramara
Format: Article
Language:English
Published: University of Mohaghegh Ardabili 2018-06-01
Series:Journal of Operation and Automation in Power Engineering
Subjects:
Online Access:http://joape.uma.ac.ir/article_642_63ddbe72ff7b225c90115d12937ae5dd.pdf
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spelling doaj-aa65d4fcd6414819b04b5fec1e17d2802020-11-24T21:28:33ZengUniversity of Mohaghegh ArdabiliJournal of Operation and Automation in Power Engineering2322-45762423-45672018-06-016111112510.22098/joape.2018.3908.1309642Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search AlgorithmA. Rastgou0J. Moshtagh1S. Bahramara2گروه مهندسی برق-دانشکده مهندسی - دانشگاه کردستان-سنندج ایرانگروه مهندسی برق- دانشکده مهندسی- دانشگاه کردستان- سنندج- ایرانگروه مهندسی برق- واحد سنندج- دانشگاه آزاد اسلامی- سنندج ایرانIn this paper, power distribution planning (PDP) considering distributed generators (DGs) is investigated as a dynamic multi-objective optimization problem. Moreover, Monte Carlo simulation (MCS) is applied to handle the uncertainty in electricity price and load demand. In the proposed model, investment and operation costs, losses and purchased power from the main grid are incorporated in the first objective function, while pollution emission due to DGs and the grid is considered in the second objective function. One of the important advantages of the proposed objective function is a feeder and substation expansion in addition to an optimal placement of DGs. The resulted model is a mixed-integer non-linear one, which is solved using a non-dominated sorting improved harmony search algorithm (NSIHSA). As multi-objective optimization problems do not have a unique solution, to obtain the final optimum solution, fuzzy decision making analysis tagged with planner criteria is applied. To show the effectiveness of the proposed model and its solution, it is applied to a 9-node distribution system.http://joape.uma.ac.ir/article_642_63ddbe72ff7b225c90115d12937ae5dd.pdfPower distribution planningHarmony search algorithmMonte Carlo simulationFuzzy decision-making
collection DOAJ
language English
format Article
sources DOAJ
author A. Rastgou
J. Moshtagh
S. Bahramara
spellingShingle A. Rastgou
J. Moshtagh
S. Bahramara
Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm
Journal of Operation and Automation in Power Engineering
Power distribution planning
Harmony search algorithm
Monte Carlo simulation
Fuzzy decision-making
author_facet A. Rastgou
J. Moshtagh
S. Bahramara
author_sort A. Rastgou
title Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm
title_short Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm
title_full Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm
title_fullStr Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm
title_full_unstemmed Probabilistic Power Distribution Planning Using Multi-Objective Harmony Search Algorithm
title_sort probabilistic power distribution planning using multi-objective harmony search algorithm
publisher University of Mohaghegh Ardabili
series Journal of Operation and Automation in Power Engineering
issn 2322-4576
2423-4567
publishDate 2018-06-01
description In this paper, power distribution planning (PDP) considering distributed generators (DGs) is investigated as a dynamic multi-objective optimization problem. Moreover, Monte Carlo simulation (MCS) is applied to handle the uncertainty in electricity price and load demand. In the proposed model, investment and operation costs, losses and purchased power from the main grid are incorporated in the first objective function, while pollution emission due to DGs and the grid is considered in the second objective function. One of the important advantages of the proposed objective function is a feeder and substation expansion in addition to an optimal placement of DGs. The resulted model is a mixed-integer non-linear one, which is solved using a non-dominated sorting improved harmony search algorithm (NSIHSA). As multi-objective optimization problems do not have a unique solution, to obtain the final optimum solution, fuzzy decision making analysis tagged with planner criteria is applied. To show the effectiveness of the proposed model and its solution, it is applied to a 9-node distribution system.
topic Power distribution planning
Harmony search algorithm
Monte Carlo simulation
Fuzzy decision-making
url http://joape.uma.ac.ir/article_642_63ddbe72ff7b225c90115d12937ae5dd.pdf
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