In a power distribution system, faults occurring can cause voltage sag that can affect critical loads connected in the power network which can cause serious effects in the oil and gas industry. The objective of this paper is to design and implement an efficient and economical dynamic voltage restorer (DVR) to compensate for voltage sag conditions in the oil and gas industry. Due to the complexity and sensitivity of loads, a short voltage sag duration can still cause severe power quality problems to the entire system. Dynamic Voltage Restorer (DVR) is a static series compensating type custom power device. The overall efficiency of the DVR largely relies on the effectiveness of the control strategy governing the switching of the inverters. It can be said that the heart of the DVR control strategy is the derivation of reference currents. This paper deals with the extraction of reference current values using a controller based on a combination of probabilistic and fuzzy set theory. The basis of the proposed controller is that Gaussian Mixture Model (GMM) which is a probabilistic approach can be translated to an additive fuzzy interface system i.e. Generalized Fuzzy Model (GFM). The proposed controller (GMM-GFM) initially optimizes the membership functions using GMM and the final output is calculated using GFM in a single iteration i.e. with no recursions. In the control scheme two control loops are used: a feed-forward loop that uses the Proportional and Integral (PI) controller and the feedback loop uses GMM-GFM based controller. The controller is implemented and respective simulations are performed in the MATLAB SIMULINK environment for three-phase, three-wire distribution system with various issues. A comparative analysis is then done amongst all the three controllers which are based on the T-S, ML, and GMM-GFM modes respectively. The simulation results of this comparison rank the DVR with the GMM-GFM controller first, followed by the fuzzy logic Mamdani model and then with the fuzzy logic T-S model.

中文翻译：

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使用概率和模糊控制的动态电压恢复器进行石油和天然气行业的电压调节

在配电系统中，发生的故障会导致电压暂降，从而影响连接在电网中的关键负载，从而对石油和天然气行业造成严重影响。本文的目的是设计和实施一种高效且经济的动态电压恢复器 (DVR)，以补偿石油和天然气行业中的电压暂降情况。由于负载的复杂性和敏感性，短暂的电压暂降持续时间仍然会对整个系统造成严重的电能质量问题。动态电压恢复器（DVR）是一种静态串联补偿型定制功率器件。DVR 的整体效率很大程度上取决于控制逆变器切换的控制策略的有效性。可以说，DVR 控制策略的核心是参考电流的推导。本文涉及使用基于概率和模糊集理论组合的控制器提取参考电流值。所提出的控制器的基础是高斯混合模型（GMM），它是一种概率方法，可以转化为一个加性模糊接口系统，即广义模糊模型（GFM）。所提出的控制器 (GMM-GFM) 最初使用 GMM 优化隶属函数，最终输出使用 GFM 在单次迭代中计算，即没有递归。在控制方案中，使用了两个控制环：使用比例积分 (PI) 控制器的前馈环和使用基于 GMM-GFM 的控制器的反馈环。在 MATLAB SIMULINK 环境中实现了控制器并分别进行了三相仿真，三线制配电系统存在各种问题。然后在分别基于 TS、ML 和 GMM-GFM 模式的所有三个控制器之间进行比较分析。该比较的仿真结果将 DVR 与 GMM-GFM 控制器排序，其次是模糊逻辑 Mamdani 模型，然后是模糊逻辑 TS 模型。