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A TLBO algorithm based optimal load scheduling of generators for power system network

机译:基于TLBO算法的电力系统发电机最优负荷调度。

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This paper discusses about ELD Problem is modeled by non-convex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a newly known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This projected algorithm is implemented to resolve the ELD problem for 6 unit and 10 unit test systems along with the other algorithms. This comparison investigation explored various merits of TLBO with respect to PSO, DE, and HSA in the field economic load dispatch.
机译:本文讨论了用非凸函数建模ELD问题。使用凸优化技术无法解决这些问题。因此,需要使用启发式方法。在这样的方法中,基于教学的优化(TLBO)是一种新的算法,并显示出令人鼓舞的结果。本文利用该算法来提供负荷分配解决方案。该解决方案与其他标准算法(例如粒子群优化(PSO),差分演化(DE)和和声搜索算法(HSA))的比较。实施此投影算法可解决6个单元测试系统和10个单元测试系统的ELD问题以及其他算法。这项比较研究探索了TLBO在现场经济负荷分配方面在PSO,DE和HSA方面的各种优点。

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