Comparative analysis and validation of advanced control modules for standalone renewable micro grid with droop controller

A micro grid system with renewable source operation control is a complex part as each source operates at different parameters. This renewable micro grid with multiple sources like solar plants, wind farm, fuel cell, battery backup has to be operated in both grid connected and standalone condition. During grid connection the micro grid, inverter has to inject power to the grid and compensate load in synchronization to the grid voltages. And during standalone condition the inverter is controlled with droop control module which stabilizes the voltage and frequency of the system even during grid disconnection. The droop control module is further updated with new advanced controllers like fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) replacing the traditional proportional integral derivative (PID) and proportional integral (PI) controllers improving the response rate and for achieving better stabilization. This paper has comparative analysis of the micro grid system with different droop controllers under various operating conditions. Parameters like voltage magnitude (Vmag), frequency (F), load and inverter powers (Pload and Pinv) of the test system are compared with different controllers. A numeric comparison table is given to determine the optimal controller for the inverter operation. The analysis is carried out in MATLAB/Simulink software with graphical and parametric validations.具备可再生能源运行控制功能的微电网系统属于复杂系统，因各能源单元的运行参数存在差异。此类集成光伏电站、风电场、燃料电池及备用蓄电池等多类能源单元的可再生能源微电网，需支持并网与孤岛两种运行模式。并网模式下，微电网逆变器需向电网注入功率，并同步电网电压以补偿负载；孤岛模式下，则通过下垂控制（droop control）模块对逆变器进行控制，即便电网断开也能维持系统电压与频率稳定。该下垂控制模块可进一步集成先进控制器，如模糊推理系统（FIS）与自适应神经模糊推理系统（ANFIS），以替代传统的比例积分微分（PID）及比例积分（PI）控制器，从而提升系统响应速率并实现更优的稳定性。本文针对配置不同下垂控制器的微电网系统，开展了多运行工况下的对比分析。以测试系统的电压幅值（Vmag）、频率（F）、负载功率与逆变器功率（Pload及Pinv）等参数为评估指标，对不同控制器的性能展开对比。本文提供了量化对比表格，用于筛选适用于逆变器运行的最优控制器。本分析基于MATLAB/Simulink软件开展，并通过图形化与参数化手段完成验证。