Multi-objective Optimal Scheduling of a Micro-grid Consisted of Renewable Energies using Multiobjective Ant lion Optimizer

Multi-objective Optimal Scheduling of a Micro-grid Consisted of Renewable Energies using Multiobjective Ant lion Optimizer

this paper proposes a sustainable simulation method for managing energy resources from the point of view of virtual power players (VPP) operating in a smart grid. The proposed energy resource management schedule in a micro-grid, including fuel cells, micro turbines, solar panels, wind turbines, and batteries, intelligently meets the needs of the grid. Apart from using the aforementioned resources, VPP can also purchase additional energy from upper utility to respond to the load. In addition, the proposed method plans suitably a micro-grid using a multi-objective framework, which minimizes the total operation cost and emission caused by the generating units simultaneously. To achieve this goal, the multi-objective Ant Lion Optimizer (MOALO) has been used to solve the multi-objective optimization problem and to produce Pareto optimal solutions. The fuzzy technique has been used for the decision making process. Finally, to demonstrate the effectiveness of the proposed method, the results have been compared with multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which shows that the use of the MOALO method in the presence of fuzzy technique attain the superior solutions on the operation cost and the emission of pollutant.

this paper proposes a sustainable simulation method for managing energy resources from the point of view of virtual power players (VPP) operating in a smart grid. The proposed energy resource management schedule in a micro-grid, including fuel cells, micro turbines, solar panels, wind turbines, and batteries, intelligently meets the needs of the grid. Apart from using the aforementioned resources, VPP can also purchase additional energy from upper utility to respond to the load. In addition, the proposed method plans suitably a micro-grid using a multi-objective framework, which minimizes the total operation cost and emission caused by the generating units simultaneously. To achieve this goal, the multi-objective Ant Lion Optimizer (MOALO) has been used to solve the multi-objective optimization problem and to produce Pareto optimal solutions. The fuzzy technique has been used for the decision making process. Finally, to demonstrate the effectiveness of the proposed method, the results have been compared with multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which shows that the use of the MOALO method in the presence of fuzzy technique attain the superior solutions on the operation cost and the emission of pollutant.