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Day ahead demand side management using firefly algorithm.

Authors :
Debbarma, Sophia
Kumar, Kothalanka K. Pavan
Soren, Nirmala
Jha, Dhiraj
Roy, Amit Kumar
Gao, Xiao-Zhi
Ghadai, Ranjan Kumar
Kalita, Kana
Shivakoti, Ishwer
Kilickap, Erol
Kundu, Tanmoy
Das, Soham
Source :
AIP Conference Proceedings. 2020, Vol. 2273 Issue 1, p1-17. 17p.
Publication Year :
2020

Abstract

The demand for electricity has increased With the increase in the number of electrical gadgets and appliances, it is now very important to emphasize in the concept of demand side management to meet the required demand of electricity. DSM assures efficient use of available energy resources. DSM along with smart grid allows the consumer to have details of power consumption information and allows the sup pliers to lower the overall load demand during the peak period and modify the load curve. Necessary data of the energy consumption and price have been taken from different papers. In this research work, the primary aim is to mainly lower the overall load demand and thus the operational cost and utility bills. The work is done in different areas – residential, commercial and industrial. To get the optimized result, Meta- heuristic algorithm was developed to minimize the problem. Because of the flexibility, gradient free mechanisms and local optima avoidance of the algorithms, meta-heuristic techniques are gaining popular. The evolutionary algorithms used to solve the demand side management problem are Particle Swarm Optimization, Firefly Algorithm and Salp Swarm Algorithm. The three algorithms are used to obtain the objective of the project work in three different areas- residential, commercial and industrial area. Firefly algorithm is found out to provide the best cost as compared to other two algorithms PSO and SSA. Firefly Algorithm is able to provide better accuracy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2273
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
146803470
Full Text :
https://doi.org/10.1063/5.0024786