Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization
In this paper, the optimal location and sizing of DESS are proposed for transmission congestion management. Transmission Congestion Cost (TCC) is used to find the optimal location of DESS, whereas hybrid optimization based on Flower Pollination Algorithm (FPA) and Differential Evolution (DE) is prop...
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doaj-9c2f54e02a884b51bc6c3f76e630b81d2020-11-25T03:08:38ZengESRGroupsJournal of Electrical Systems1112-52091112-52092020-06-01162257275Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid OptimizationVATSALA SHARMA0PRATIMA WALDE1ANWAR SHAHZAD SIDDIQUI 2School of Electrical, Electronics and Communication Engineering, Galgotias University, Greater Noida, Uttar Pradesh-226001, IndiaSchool of Electrical, Electronics and Communication Engineering, Galgotias University, Greater Noida, Uttar Pradesh-226001, IndiaDepartment of Electrical Engineering, JamiaMilliaIslamia (A Central University), New Delhi-110025, IndiaIn this paper, the optimal location and sizing of DESS are proposed for transmission congestion management. Transmission Congestion Cost (TCC) is used to find the optimal location of DESS, whereas hybrid optimization based on Flower Pollination Algorithm (FPA) and Differential Evolution (DE) is proposed for optimal sizing of DESS. The methodology considering Solar PV and Energy Storage System (ESS) as sources of energy. 24 hours real temperature and solar irradiance data of Delhi are taken to mathematically model the generation from Solar PV to manage congestion throughout the 24 hours. ESS is used to store surplus energy. The proposed approach is tested on IEEE-30 and IEEE-57 bus system, and 24 hours demand is assumed to follow the hourly load shape (summer season) of the IEEE reliability test system. The performance of the proposed approach is validated by comparing the results obtained through hybrid (FPA-DE) based hybrid optimization with the results obtained through DE optimization. It is observed from the experiment that both the optimization techniques (DE, Hybrid) performed well in managing congestion. However, DE has a higher consumption of resources that lead to shortage of resources at the end of the day; hence fail to manage congestion the next day, when solar irradiance is not available. In contrast, hybrid optimization provides very encouraging results, and at the end of the day saves approx. 39% of ESS, thus can participate in congestion management for the next day in the absence of solar irradiancehttp://journal.esrgroups.org/jes/papers/16_2_10.pdfenergy storage systemtransmission congestion costlocational marginal priceflower pollination algorithmdifferential evolutionhybrid optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
VATSALA SHARMA PRATIMA WALDE ANWAR SHAHZAD SIDDIQUI |
spellingShingle |
VATSALA SHARMA PRATIMA WALDE ANWAR SHAHZAD SIDDIQUI Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization Journal of Electrical Systems energy storage system transmission congestion cost locational marginal price flower pollination algorithm differential evolution hybrid optimization |
author_facet |
VATSALA SHARMA PRATIMA WALDE ANWAR SHAHZAD SIDDIQUI |
author_sort |
VATSALA SHARMA |
title |
Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization |
title_short |
Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization |
title_full |
Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization |
title_fullStr |
Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization |
title_full_unstemmed |
Hourly Congestion Management by Adopting Distributed Energy Storage System using Hybrid Optimization |
title_sort |
hourly congestion management by adopting distributed energy storage system using hybrid optimization |
publisher |
ESRGroups |
series |
Journal of Electrical Systems |
issn |
1112-5209 1112-5209 |
publishDate |
2020-06-01 |
description |
In this paper, the optimal location and sizing of DESS are proposed for transmission congestion management. Transmission Congestion Cost (TCC) is used to find the optimal location of DESS, whereas hybrid optimization based on Flower Pollination Algorithm (FPA) and Differential Evolution (DE) is proposed for optimal sizing of DESS. The methodology considering Solar PV and Energy Storage System (ESS) as sources of energy. 24 hours real temperature and solar irradiance data of Delhi are taken to mathematically model the generation from Solar PV to manage congestion throughout the 24 hours. ESS is used to store surplus energy. The proposed approach is tested on IEEE-30 and IEEE-57 bus system, and 24 hours demand is assumed to follow the hourly load shape (summer season) of the IEEE reliability test system. The performance of the proposed approach is validated by comparing the results obtained through hybrid (FPA-DE) based hybrid optimization with the results obtained through DE optimization. It is observed from the experiment that both the optimization techniques (DE, Hybrid) performed well in managing congestion. However, DE has a higher consumption of resources that lead to shortage of resources at the end of the day; hence fail to manage congestion the next day, when solar irradiance is not available. In contrast, hybrid optimization provides very encouraging results, and at the end of the day saves approx. 39% of ESS, thus can participate in congestion management for the next day in the absence of solar irradiance |
topic |
energy storage system transmission congestion cost locational marginal price flower pollination algorithm differential evolution hybrid optimization |
url |
http://journal.esrgroups.org/jes/papers/16_2_10.pdf |
work_keys_str_mv |
AT vatsalasharma hourlycongestionmanagementbyadoptingdistributedenergystoragesystemusinghybridoptimization AT pratimawalde hourlycongestionmanagementbyadoptingdistributedenergystoragesystemusinghybridoptimization AT anwarshahzadsiddiqui hourlycongestionmanagementbyadoptingdistributedenergystoragesystemusinghybridoptimization |
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