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

2020 IEEE Calcutta Conference (CALCON) Pub Date : 2020-02-01 DOI:10.1109/CALCON49167.2020.9106493

Dipayan Guha, P. Roy, Subrata Banerjee

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引用次数: 2

Abstract

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.

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自适应共生生物搜索算法优化的3DOF-PID混合动力系统负荷频率控制

本文研究了混合能源分布式电力系统(HEDPS)在恒定和可变负载扰动下的动态性能。HEDPS由可再生能源组成，并与多机组热液发电厂相协调。为了缓解可再生能源间歇性输出带来的频率和功率偏差，提出了3自由度比例-积分-导数PID (3- dof比例-积分-导数PID)。将3DOF-PID控制器得到的结果与2DOF-PID、PID和PI控制器进行比较，以量化其有效性。采用共生生物搜索(SOS)算法搜索上述控制器增益。考虑了效益因子生成的自适应方案，以保证SOS算法在探索和开发阶段之间的平衡。结果表明，自适应SOS算法的调谐能力优于SOS算法和其他群体智能算法。结果表明，自适应sos调谐的3DOF-PID控制器比其他同类控制器具有更好的控制效果。最后，通过对系统参数和负载条件的敏感性分析，验证了所设计控制器的鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2020 IEEE Calcutta Conference (CALCON)

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