A genetic algorithm and a particle swarm optimizer hybridized with Nelder-Mead simplex search
Computers and Industrial Engineering - Special issue: Sustainability and globalization: Selected papers from the 32 nd ICC&IE
Expert Systems with Applications: An International Journal
Particle swarm optimization with crazy particles for nonconvex economic dispatch
Applied Soft Computing
Economic environmental dispatch using multi-objective differential evolution
Applied Soft Computing
Solving economic emission load dispatch problems using hybrid differential evolution
Applied Soft Computing
Multiagent based differential evolution approach to optimal power flow
Applied Soft Computing
Implementing the Nelder-Mead simplex algorithm with adaptive parameters
Computational Optimization and Applications
Artificial bee colony algorithm solution for optimal reactive power flow
Applied Soft Computing
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
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In this paper, we solve the optimal power flow problem using by the new hybrid fuzzy particle swarm optimisation and Nelder-Mead (NM) algorithm (HFPSO-NM). The goal of combining the NM simplex method and the particle swarm optimisation (PSO) method is to integrate their advantages and avoid their disadvantages. The NM simplex method is a very efficient local search procedure, but its convergence is extremely sensitive to the selected starting point. In addition, PSO belongs to the class of global search procedures, but it requires significant computational effort. In the other side, in the PSO algorithm, two variables (@F"1,@F"2) are traditionally constant; in this case, due to the importance of these two factors, we decided to obtain these two as fuzzy parameters. The proposed method is firstly examined on some benchmark mathematical functions. Then, it is tested an IEEE 30-bus standard test system by considering different objective functions for normal and contingency conditions to solve optimal power flow. The simulation results indicate that the FPSO-NM algorithm is effective in solving the mathematical functions and the OPF problem.