Paper Info
Title
Augmented Grasshopper Optimization Algorithm By Differential Evolution: A Power Scheduling Application In Smart Homes
Abstract
With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26 % enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.
Year
DOI
Venue
2021
10.1007/s11042-021-11099-1
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Hybrid Method, Grasshopper Optimization Algorithm, Differential Evolution, Power scheduling, Smart homes, Smart grid
Journal
80
Issue
ISSN
Citations 
21-23
1380-7501
1
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Ahmad Ziadeh110.34
Laith Mohammad Abualigah224411.47
Mohamed Abd El Aziz328421.93
Canan Batur Sahin410.34
Abdulwahab Ali Almazroi511.69
Mahmoud Omari610.34