Self - adaptive Differential Evolution Based Optimal Power Flow for Units with Non - smooth Fuel Cost Functions JES
نویسنده
چکیده
This paper presents a self-adaptive differential evolution with augmented Lagrange multiplier method (SADE_ALM) for solving optimal power flow (OPF) problems with non-smooth generator fuel cost curves. The SADE_ALM is a modified version of conventional differential evolution (DE) by integrating mutation factor (F ) and crossover constant (CR ) as additional control variables. An augmented Lagrange multiplier method (ALM) is applied to handle inequality constraints instead of traditional penalty function method, whereas the sum of the violated constraint (SVC ) index is employed to ensure that the final result is the feasible global or quasi-global optimum. The proposed algorithm has been tested with the IEEE 30-bus system with different fuel cost characteristics, i.e. 1) quadratic cost curve model, and 2) quadratic cost curve with rectified sine component model (valve-point effects). Numerical results show that the SADE_ALM provides very impressive results compared with the previous reports.
منابع مشابه
Self-Adaptive Differential Evolution Based Power Economic Dispatch of Generators with Valve-Point Effects and Multiple Fuel Options
This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evo...
متن کاملGenetic evolving ant direction HDE for OPF with non-smooth cost functions and statistical analysis
This paper proposes an evolving ant direction differential evolution (EADDE) algorithm for solving the optimal power flow problem with non-smooth and non-convex generator fuel cost characteristics. The EADDE employs ant colony search to find a suitable mutation operator for differential evolution (DE) whereas the ant colony parameters are evolved using genetic algorithm approach. The NewtoneRap...
متن کاملDifferential Evolution Approach for Optimal Power Flow Solution
This paper presents an algorithm for solving optimal power flow problem through the application of Differential Evolution (DE). The objective is to minimize the total fuel cost of thermal generating units having quadratic cost characteristics subjected to limits on generator real and reactive power outputs, bus voltages, transformer taps and power flow of transmission lines. The proposed method...
متن کاملحل مسئله پخش بار بهینه در شرایط نرمال و اضطراری با استفاده از الگوریتم ترکیبی گروه ذرات و نلدر مید (PSO-NM)
In this paper, solving optimal power flow problem has been investigated by using hybrid particle swarm optimization and Nelder Mead Algorithms. The goal of combining Nelder-Mead (NM) simplex method and particle swarm optimization (PSO) is to integrate their advantages and avoid their disadvantages. NM simplex method is a very efficient local search procedure but its convergence is extremely sen...
متن کاملAn Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems
The Economic Load Dispatch (ELD) problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA), for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to lim...
متن کامل