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Improved Demand Response with Particle Swarm Optimization

Suparna Dey1 , Monalisa Dasgupta2 , Soumesh Chatterjee3 , Gagari Deb4

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-18 , Page no. 235-239, May-2019

Online published on May 25, 2019

Copyright © Suparna Dey, Monalisa Dasgupta, Soumesh Chatterjee, Gagari Deb . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Suparna Dey, Monalisa Dasgupta, Soumesh Chatterjee, Gagari Deb, “Improved Demand Response with Particle Swarm Optimization,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.18, pp.235-239, 2019.

MLA Style Citation: Suparna Dey, Monalisa Dasgupta, Soumesh Chatterjee, Gagari Deb "Improved Demand Response with Particle Swarm Optimization." International Journal of Computer Sciences and Engineering 07.18 (2019): 235-239.

APA Style Citation: Suparna Dey, Monalisa Dasgupta, Soumesh Chatterjee, Gagari Deb, (2019). Improved Demand Response with Particle Swarm Optimization. International Journal of Computer Sciences and Engineering, 07(18), 235-239.

BibTex Style Citation:
@article{Dey_2019,
author = {Suparna Dey, Monalisa Dasgupta, Soumesh Chatterjee, Gagari Deb},
title = {Improved Demand Response with Particle Swarm Optimization},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {18},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {235-239},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1370},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1370
TI - Improved Demand Response with Particle Swarm Optimization
T2 - International Journal of Computer Sciences and Engineering
AU - Suparna Dey, Monalisa Dasgupta, Soumesh Chatterjee, Gagari Deb
PY - 2019
DA - 2019/05/25
PB - IJCSE, Indore, INDIA
SP - 235-239
IS - 18
VL - 07
SN - 2347-2693
ER -

           

Abstract

Among all the power management strategies in smart grid, demand response is quiet popular because of its significance impact on saving in peak demand and reduced energy consumption. Electricity price revealed by utility companyis mainly accountable for the demand response to lead the consumer in electricity scheduling.The mutual benefits for both customer and supply side are ensured with the use of price conferring mechanism through demand response.This paper proposes anapproach to minimize the elastic load through price weight given by the utility company. Three types of consumers are designed as residential, industrial and commercial. The ‘per day electricity use’ for these consumers has been reducedby scheduling elastic loads using Particle Swarm Optimization(PSO) technique. The outcome of simulation results show that the recommended algorithm reduces the cost while balancing the peak demand.

Key-Words / Index Term

Demand Response, Dynamic pricing, Elastic Loads, Load Scheduling, Particle Swarm Optimization(PSO)

References

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