Multi-objective optimal probabilistic planning in distribution systems considering load growth

Distribution network planning is critical to meet load growth and ensure the reliability of the network. the load demands of electrical distribution networks is increased gradually over time, which raises active and reactive power losses and lowers bus voltages below allowable levels. The modern pow...

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Main Author: Ayat Saleh
Format: Article
Language:Arabic
Published: Assiut University, Faculty of Engineering 2025-01-01
Series:JES: Journal of Engineering Sciences
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Online Access:https://jesaun.journals.ekb.eg/article_395158_c33563badfbda2d792ceedca80ba49c2.pdf
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author Ayat Saleh
author_facet Ayat Saleh
author_sort Ayat Saleh
collection DOAJ
description Distribution network planning is critical to meet load growth and ensure the reliability of the network. the load demands of electrical distribution networks is increased gradually over time, which raises active and reactive power losses and lowers bus voltages below allowable levels. The modern power system has experienced significant structural modifications as a result of the annual expansion in load. This paper presents the operation of distribution networks with dispatch able mix of different types of distributed energy resources (DERs) units considering load growth up to planning period based on Multi Variant Differential Evolution algorithm (MVDE). The electric power system is supplied by numerous capacity resources including renewable and non-renewable power resources like photovoltaic system (PV), wind turbine system (WT), fuel cell (FC), and micro-turbine (MT). The main objectives of DERs allocation are to maximize technical, economic and environmental benefits by reducing the power losses, annual cost, and greenhouse gas. The WT, PV, MT, and FC units' capacity is increased by capacity expansion planning in the radial distributed network, which is carried out over a five-year planning horizon. A comprehensive stochastic strategy is offered for a number of uncertainties, such as load increase and output power from renewable energy sources. Two IEEE bus networks are used to illustrate the suggested method's efficacy. The optimization results based on proposed algorithm are compared with some existing algorithms.
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spelling doaj-art-96950ca3e2604e26982156db6a843b3c2025-08-20T02:43:54ZaraAssiut University, Faculty of EngineeringJES: Journal of Engineering Sciences1687-05302356-85502025-01-01531388110.21608/jesaun.2024.329451.1377395158Multi-objective optimal probabilistic planning in distribution systems considering load growthAyat Saleh0Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, EgyptDistribution network planning is critical to meet load growth and ensure the reliability of the network. the load demands of electrical distribution networks is increased gradually over time, which raises active and reactive power losses and lowers bus voltages below allowable levels. The modern power system has experienced significant structural modifications as a result of the annual expansion in load. This paper presents the operation of distribution networks with dispatch able mix of different types of distributed energy resources (DERs) units considering load growth up to planning period based on Multi Variant Differential Evolution algorithm (MVDE). The electric power system is supplied by numerous capacity resources including renewable and non-renewable power resources like photovoltaic system (PV), wind turbine system (WT), fuel cell (FC), and micro-turbine (MT). The main objectives of DERs allocation are to maximize technical, economic and environmental benefits by reducing the power losses, annual cost, and greenhouse gas. The WT, PV, MT, and FC units' capacity is increased by capacity expansion planning in the radial distributed network, which is carried out over a five-year planning horizon. A comprehensive stochastic strategy is offered for a number of uncertainties, such as load increase and output power from renewable energy sources. Two IEEE bus networks are used to illustrate the suggested method's efficacy. The optimization results based on proposed algorithm are compared with some existing algorithms.https://jesaun.journals.ekb.eg/article_395158_c33563badfbda2d792ceedca80ba49c2.pdfrenewableenergysourceuncertainty
spellingShingle Ayat Saleh
Multi-objective optimal probabilistic planning in distribution systems considering load growth
JES: Journal of Engineering Sciences
renewable
energy
source
uncertainty
title Multi-objective optimal probabilistic planning in distribution systems considering load growth
title_full Multi-objective optimal probabilistic planning in distribution systems considering load growth
title_fullStr Multi-objective optimal probabilistic planning in distribution systems considering load growth
title_full_unstemmed Multi-objective optimal probabilistic planning in distribution systems considering load growth
title_short Multi-objective optimal probabilistic planning in distribution systems considering load growth
title_sort multi objective optimal probabilistic planning in distribution systems considering load growth
topic renewable
energy
source
uncertainty
url https://jesaun.journals.ekb.eg/article_395158_c33563badfbda2d792ceedca80ba49c2.pdf
work_keys_str_mv AT ayatsaleh multiobjectiveoptimalprobabilisticplanningindistributionsystemsconsideringloadgrowth