This paper proposes a modified bias (MB) and coefficient diagram method (CDM) based PID controller as a first attempt in controlling frequency of a self-reliant microgrid (MG) system under extreme unfavourable scenarios. Recently developed meta-heuristic algorithm, Grey Wolf Optimizer (GWO), is used for optimizing the parameters of the proposed controller GWO). Frequency deviation arises in the system due to active power mismatch between load power demand and actual power generation. In order to overcome this problem the CDM based gain values and frequency biased parameters of the MG system are used for determining the ranges of the control parameters for optimization with GWO which ensures that the search points generated by the search algorithm are stable ones. Simulation of the proposed GWO optimized MB-CDM controller-based MG system has been successfully implemented in real time simulation platform using digital simulator OPAL-RT. The performance of the system is obtained using proposed controller under different real-life scenarios and results are minutely analysed. The results are further compared with other relevant recent controllers including particle swarm optimization (PSO) MB-CDM controller to demonstrate that the proposed controller is superior to all other controllers. In addition, sensitivity analysis of the proposed controller for the MG system is studied under varying system parameters. The Simulink results illustrate that the proposed controller gives the best dynamic response amongst all other considered controllers in terms of peak transient deviation and settling time.

中文翻译：

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使用基于灰狼优化的修正偏置系数图法 (GWO-MBCDM) 控制器实时仿真多源微电网系统的负载频率控制

本文提出了一种基于修正偏置 (MB) 和系数图法 (CDM) 的 PID 控制器，作为在极端不利情况下控制自力微电网 (MG) 系统频率的首次尝试。最近开发的元启发式算法灰狼优化器（GWO）用于优化所提出的控制器 GWO 的参数。由于负载功率需求与实际发电量之间的有功功率不匹配，系统中会出现频率偏差。为了克服这个问题，MG 系统的基于 CDM 的增益值和频率偏置参数被用于确定控制参数的范围，以使用 GWO 进行优化，从而确保搜索算法生成的搜索点是稳定的。所提出的基于 GWO 优化 MB-CDM 控制器的 MG 系统的仿真已在使用数字仿真器 OPAL-RT 的实时仿真平台上成功实现。系统的性能是使用建议的控制器在不同的现实生活场景下获得的，并且对结果进行了细致的分析。结果与包括粒子群优化 (PSO) MB-CDM 控制器在内的其他相关的近期控制器进行了进一步比较，以证明所提出的控制器优于所有其他控制器。此外，在变化的系统参数下研究了所提出的 MG 系统控制器的灵敏度分析。Simulink 结果表明，在峰值瞬态偏差和稳定时间方面，建议的控制器在所有其他考虑的控制器中提供最佳动态响应。