Optimization Algorithms in Smart Grids: A Systematic Literature Review
- URL: http://arxiv.org/abs/2301.07512v1
- Date: Mon, 16 Jan 2023 12:31:06 GMT
- Title: Optimization Algorithms in Smart Grids: A Systematic Literature Review
- Authors: Sidra Aslam, Ala Altaweel, Ali Bou Nassif
- Abstract summary: This paper focuses on novel features and applications of smart grids in domestic and industrial sectors.
Specifically, we focused on Genetic algorithm, Particle Swarm Optimization, and Grey Wolf Optimization.
- Score: 4.301367153728695
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Electrical smart grids are units that supply electricity from power plants to
the users to yield reduced costs, power failures/loss, and maximized energy
management. Smart grids (SGs) are well-known devices due to their exceptional
benefits such as bi-directional communication, stability, detection of power
failures, and inter-connectivity with appliances for monitoring purposes. SGs
are the outcome of different modern applications that are used for managing
data and security, i.e., modeling, monitoring, optimization, and/or Artificial
Intelligence. Hence, the importance of SGs as a research field is increasing
with every passing year. This paper focuses on novel features and applications
of smart grids in domestic and industrial sectors. Specifically, we focused on
Genetic algorithm, Particle Swarm Optimization, and Grey Wolf Optimization to
study the efforts made up till date for maximized energy management and cost
minimization in SGs. Therefore, we collected 145 research works (2011 to 2022)
in this systematic literature review. This research work aims to figure out
different features and applications of SGs proposed in the last decade and
investigate the trends in popularity of SGs for different regions of world. Our
finding is that the most popular optimization algorithm being used by
researchers to bring forward new solutions for energy management and cost
effectiveness in SGs is Particle Swarm Optimization. We also provide a brief
overview of objective functions and parameters used in the solutions for energy
and cost effectiveness as well as discuss different open research challenges
for future research works.
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