Open AccessMicro Grid Operation Cost Reduction Using Particle Swarm Optimizer and Eagle Strategy
Author(s) -
M. Gnanaprakash
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.37019
Subject(s) - particle swarm optimization , computer science , renewable energy , metaheuristic , electricity , grid , parallel metaheuristic , mathematical optimization , wind power , automotive engineering , multi swarm optimization , engineering , electrical engineering , algorithm , geometry , mathematics
As a result of rapid financial development and natural disasters, energy efficiency research, and high-quality electricity alternative energy options, as well as efficient electricity sources. In particular, the use of green energy sources has become a hot issue; As a result, distributed electricity supply in the micro grid is the basis for the achievement of the vital objectives of successfully providing the customer with currency and stability. The article proposes a hybrid metaheuristic approach based on the Eagle strategy Technique (ES) and Particular Swarm Optimizing (PSO) Technology, which will minimize low-voltage running costs from a renewable energy source such as an electricity generator, solar panels, wind generators, micro turbines and fuel cells. The cost optimization problem is set up as a nonlinearly constrained problem. In order to maximize distributed generation, a mathematical problem must be solved. The proposed hybrid solution is evaluated on low-voltage micro grids, and its optimal performance is compared to that of other hybrid approaches and variety of other metaheuristic techniques