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Comparison of the Lagrange's and Particle Swarm Optimisation solutions of an Economic Emission Dispatch problem with transmission constraints

机译:具有传输约束的经济排放调度问题的拉格朗日和粒子群优化解决方案比较

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The power demand is increased rapidly and hence the power systems become more complex, so it is necessary to solve the dispatch problem with less computation time. This paper uses the optimization approach (Lagrange's) and random variables selection approach Particle Swarm Optimisation (PSO) to solve the dispatch problem with transmission constraints and to compare the obtained solution and the time for its calculation. Formulation of a bi-criteria Combined Economic Emission Dispatch (CEED) problem is given. The application of Lagrange's and PSO methods to the CEED problem is described and the algorithms for calculations are given. The computational time of the Lagrange's algorithm depends on the selection of the initial values of the Lagrange's variable (λ), and on the swarms, positions, and velocity selection in PSO algorithm. The IEEE 30 bus system is considered to validate the simulation results in MATLAB environment. It concludes that Lagrange's algorithm provides better results for CEED problem in comparison to the PSO algorithm.
机译:电力需求迅速增加,因此电力系统变得更加复杂,因此有必要以更少的计算时间来解决调度问题。本文使用优化方法(拉格朗日方法)和随机变量选择方法粒子群优化方法(PSO)来解决具有传输约束的调度问题,并比较所获得的解决方案和计算时间。给出了双标准联合经济排放调度(CEED)问题的公式。描述了Lagrange方法和PSO方法在CEED问题上的应用,并给出了计算算法。拉格朗日算法的计算时间取决于拉格朗日变量(λ)的初始值的选择,以及PSO算法中的群,位置和速度选择。考虑使用IEEE 30总线系统来验证MATLAB环境中的仿真结果。结论是,与PSO算法相比,拉格朗日算法为CEED问题提供了更好的结果。

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