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A solution to the economic dispatch using EP based SA algorithm on large scale power system

机译:基于EP的SA算法在大型电力系统经济调度中的解决方案。

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This paper develops a new approach for solving the Economic Load Dispatch (ELD) using an integrated algorithm based on Evolutionary Programming (EP) and Simulated Annealing (SA) on large scale power system. Classical methods employed for solving Economic Load Dispatch are calculus-based. For generator units having quadratic fuel cost functions, the classical techniques ignore or flatten out the portions of the incremental fuel cost curves and so may be have difficulties in the determination of the global optimum solution for non-differentiable fuel cost functions. To overcome these problems, the intelligent techniques, namely, Evolutionary Programming and Simulated Annealing are employed. The above said optimization techniques are capable of determining the global or near global optimum dispatch solutions. The validity and effectiveness of the proposed integrated algorithm has been tested with 66-bus Indian utility system, IEEE 5-bus, 30-bus, 118-bus system. And the test results are compared with the results obtained from other methods. Numerical results show that the proposed integrated algorithm can provide accurate solutions within reasonable time for any type of fuel cost functions.
机译:本文针对大规模电力系统,采用基于进化规划(EP)和模拟退火(SA)的集成算法,开发了一种解决经济负荷分配(ELD)的新方法。解决经济负荷分配的经典方法是基于演算的。对于具有二次燃料成本函数的发电机单元,传统技术忽略或展平了增量燃料成本曲线的部分,因此在确定不可微分燃料成本函数的全局最优解时可能会遇到困难。为了克服这些问题,采用了智能技术,即进化规划和模拟退火。上述优化技术能够确定全局或接近全局的最佳调度解决方案。所提出的集成算法的有效性和有效性已在66总线印度公用事业系统,IEEE 5总线,30总线,118总线系统中进行了测试。并将测试结果与其他方法获得的结果进行比较。数值结果表明,所提出的集成算法可以在合理的时间内为任何类型的燃料成本函数提供准确的解决方案。

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