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Dynamic voltage regulation of grid-tied renewable energy system with ANFIS

机译:用ANFIS网格栓可再生能源系统的动态电压调节

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Increased interconnection of stochastic renewable distributed generators (DGs) with low voltage distribution networks arises challenging issues in voltage regulation, protection, stability and power quality of the system. Due to nonlinear nature of DG generations and dynamic load demands, voltage at point of common coupling (PCC) of grid-tied renewable energy system (RES) varies all the time and may exceed the allowable voltage limit. A novel Adaptive Neuro-Fuzzy Inference System (ANFIS) control strategy has been proposed and assessed in this paper while implemented on grid interfacing inverter for regulating PCC voltage under any nonlinear and fluctuating operating conditions. Performance of the proposed ANFIS-based voltage regulation scheme has been evaluated in several case studies with versatile operating conditions like minimal RES generation or excess RES generation comparing to dynamic load demands, sudden voltage fluctuations at point of common coupling etc. The proposed ANFIS-based control strategy is developed and simulated in MATLAB/ Simulink environment and its dynamic performance is compared with conventional PID control schemes.
机译:随机可再生分布式发电机(DGS)的互连与低电压分布网络引起了系统的电压调节,保护,稳定性和功率质量的挑战性问题。由于DG世代的非线性性质和动态负载需求,网格连接可再生能源系统(RES)的公共耦合点(PCC)点的电压始终变化,并且可能超过允许电压限制。本文提出和评估了一种新型自适应神经模糊推理系统(ANFIS)控制策略,同时在网格接口逆变器上进行了用于调节任何非线性和波动的操作条件下的PCC电压。所提出的基于ANFIS电压调节方案的性能已经在几个情况下研究中评价与多功能像最小RES生成或过量生成RES进行比较来动态负载需求操作条件下,在公共耦合点等突然电压波动所提出的基于ANFIS在Matlab / Simulink环境中开发和模拟控制策略,并将其动态性能与传统的PID控制方案进行了比较。

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