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Adaptive Symbiotic Organism Search Algorithm Optimized 3DOF-PID Controller for Load Frequency Control of Hybrid Power System

机译:混合动力系统负荷频率控制的自适应共生生物搜索算法优化3DOF-PID控制器

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This work investigates the dynamic performance of a hybrid energy distributed power system (HEDPS) against constant and variable load perturbations. The HEDPS comprises renewable energy resources coordinated with a multi-unit hydrothermal power plant. To alleviate the frequency and power deviation against intermittent outputs of renewable energy resources, 3 degree-of-freedom (3-DOF) proportional-integral-derivative (PID) has been proposed. The results obtained with 3DOF-PID controller are compared with 2DOF-PID, PID, and PI controllers to quantify the effectiveness of the same. Symbiotic organism search (SOS) algorithm is applied to search the controller gains mentioned above. An adaption scheme in the generation of benefit factors has been considered to ensure balance between exploration and exploitation phases of SOS algorithm. The tuning competence of the adaptive SOS has been shown over SOS and other swarm intelligence algorithms. The inspection of the results demonstrates that adaptive-SOS tuned 3DOF-PID controller delivers comparatively better result than its other counterpart. Finally, sensitivity analysis is performed to affirm robustness of the developed controller by varying system parameters and loading condition.
机译:这项工作研究了混合动力分布式电源系统(HEDPS)对恒定和可变负载扰动的动态性能。 HEDPS包含可再生能源,并与一个多单元水热电厂协调。为了减轻频率和功率对可再生能源间歇输出的偏差,提出了3自由度(3-DOF)比例积分微分(PID)。将使用3DOF-PID控制器获得的结果与2DOF-PID,PID和PI控制器进行比较,以量化其有效性。应用共生生物搜索(SOS)算法来搜索上述控制器增益。为了确保SOS算法的探索和开发阶段之间的平衡,已经考虑了在利益因子生成中采用一种适应方案。自适应SOS的调优能力已经超过了SOS和其他群体智能算法。对结果的检查表明,自适应SOS调谐的3DOF-PID控制器比其他同类产品提供了更好的结果。最后,进行灵敏度分析,以通过改变系统参数和加载条件来确定所开发控制器的鲁棒性。

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