Title:Enhancing the Efficiency of Wind Power Using Hybrid Fire Fly and Genetic Algorithm - Economic Load Dispatch Model
VOLUME: 13 ISSUE: 1
Author(s):M.P. Varghese* and A. Amudha
Affiliation:Dept. of Electronics and Electrial Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, Dept. of Electronics and Electrial Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu
Keywords:Economic load dispatch, fire fly algorithm, genetic algorithm, meta-heuristic algorithms, power optimization.
Abstract:Background: Economic Load Dispatch (ELD) is the process of applying necessary
load demand between generators in power system that satisfies all units, so as to decrease the cost
of operation. In order to solve the ELD problem, meta-heuristic algorithms are preferred. The
combination of Fire Fly (FF) algorithm and Genetic Algorithm (GA) is used in this research to
solve the ELD problem and optimize the wind energy output.
Methods: The wind turbine rotates by the force of the wind from nature. The optimum values
of the input parameters of wind turbine such as Cp, λ are predicted using Genetic Algorithm. Thus,
the wind turbine output is optimized. The output of the generator is optimized by the MPPT
methods in practice. The MPPT method deployed here is Incremental Conductance method. The
wind energy output is AC in nature. It is converted to DC using rectifier action. Then the boost
converter further boosts the output value. The inverter action converts the DC into AC and fed to
grid. The fuel operating cost of the wind energy system is reduced by means of the FFA thus
solves the ELD problem. The wind energy system with optimized power to grid is implemented
using MATLAB SIMULINK tool and ELD is solved and executed by means of MATLAB
coding.
Results: The input parameters of wind turbine such as Cp and λ values are predicted by means of
genetic algorithm, in order to obtain optimal output from the turbine. The power coefficients (CP)
and tip speed λ value of the wind turbine are found out, thus the wind turbine output is optimized.
The generator output is optimized by MPPT technique.
Conclusion: By adopting Genetic Algorithm the input parameter value required for wind turbine is
predicted. The economic load dispatch problem is solved and cost function is minimized by deploying
Firefly algorithm. The wind power output is optimized by hybrid GA-FFA and the optimized
power is fed to grid thus enhancing grid efficiency. The results obtained were tested using
MATLAB/SIMULINK platform.
