Generation and transmission expansion management using grasshopper optimization algorithm

Generation and transmission expansion management using grasshopper optimization algorithm

This article explores how generation and transmission expansion plans (GTEPs) vary and become better suited for the accessibility of smart grid technology (SGT), essentially comprising load shifting, environmental assets and cost rebates. Demand response (DR) resources in smart grids have emerged in...

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Main Authors: Ponnambalam Suriya, Srikrishna Subramanian, Sivarajan Ganesan, Manoharan Abirami
Format: Article
Language:English
Published: SAGE Publishing 2019-01-01
Series:International Journal of Engineering Business Management
Online Access:https://doi.org/10.1177/1847979018818320
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spelling doaj-ac480571be8c45f7b18c69e28d8ecabf2021-04-02T15:35:27ZengSAGE PublishingInternational Journal of Engineering Business Management1847-97902019-01-011110.1177/1847979018818320Generation and transmission expansion management using grasshopper optimization algorithmPonnambalam Suriya0Srikrishna Subramanian1Sivarajan Ganesan2Manoharan Abirami3 Department of Electrical Engineering, Annamalai University, Chidambaram, Tamil Nadu, India Department of Electrical Engineering, Annamalai University, Chidambaram, Tamil Nadu, India Department of Electrical and Electronics Engineering, Government College of Engineering, Dharmapuri, Tamil Nadu, India Department of Electrical and Electronics Engineering, Government College of Engineering, Srirangam, Tiruchirappalli, Tamil Nadu, IndiaThis article explores how generation and transmission expansion plans (GTEPs) vary and become better suited for the accessibility of smart grid technology (SGT), essentially comprising load shifting, environmental assets and cost rebates. Demand response (DR) resources in smart grids have emerged in debates on GTEP, especially with respect to compromising system security. The planned model is designed as an innovative GTEP solution with DR resources that minimize cost by decreasing the peak load of the basic plan. A chaotic grasshopper optimization algorithm (CGOA) is used to optimize the results of the proposed GTEP model.https://doi.org/10.1177/1847979018818320
collection DOAJ
language English
format Article
sources DOAJ
author Ponnambalam Suriya
Srikrishna Subramanian
Sivarajan Ganesan
Manoharan Abirami
spellingShingle Ponnambalam Suriya
Srikrishna Subramanian
Sivarajan Ganesan
Manoharan Abirami
Generation and transmission expansion management using grasshopper optimization algorithm
International Journal of Engineering Business Management
author_facet Ponnambalam Suriya
Srikrishna Subramanian
Sivarajan Ganesan
Manoharan Abirami
author_sort Ponnambalam Suriya
title Generation and transmission expansion management using grasshopper optimization algorithm
title_short Generation and transmission expansion management using grasshopper optimization algorithm
title_full Generation and transmission expansion management using grasshopper optimization algorithm
title_fullStr Generation and transmission expansion management using grasshopper optimization algorithm
title_full_unstemmed Generation and transmission expansion management using grasshopper optimization algorithm
title_sort generation and transmission expansion management using grasshopper optimization algorithm
publisher SAGE Publishing
series International Journal of Engineering Business Management
issn 1847-9790
publishDate 2019-01-01
description This article explores how generation and transmission expansion plans (GTEPs) vary and become better suited for the accessibility of smart grid technology (SGT), essentially comprising load shifting, environmental assets and cost rebates. Demand response (DR) resources in smart grids have emerged in debates on GTEP, especially with respect to compromising system security. The planned model is designed as an innovative GTEP solution with DR resources that minimize cost by decreasing the peak load of the basic plan. A chaotic grasshopper optimization algorithm (CGOA) is used to optimize the results of the proposed GTEP model.
url https://doi.org/10.1177/1847979018818320
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AT srikrishnasubramanian generationandtransmissionexpansionmanagementusinggrasshopperoptimizationalgorithm
AT sivarajanganesan generationandtransmissionexpansionmanagementusinggrasshopperoptimizationalgorithm
AT manoharanabirami generationandtransmissionexpansionmanagementusinggrasshopperoptimizationalgorithm
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