Detection of loss of grid event in distributed generation systems using pattern recognition

迫切需要扩大可再生能源发电系统的使用，以满足英国政府的目标。并网可再生能源的扩展必须以不降低配电系统安全性的方式进行。配电系统安全性不可或缺的是分布式发电机可靠地检测电网状况损失的能力。这对于防止系统的不必要的孤岛部分是重要的，这些孤岛部分在电网连接丢失后继续通电。当电网系统的一部分与网络的其余部分断开连接，但继续由本地分布式发电系统供电时，就会发生孤岛系统。孤岛系统（i）对电力系统工作人员具有潜在危险，（ii）可能在电压和频率容差之外运行，（iii）可能接地不充分，以及（iv）可能无法正确重新同步，导致不希望的保护跳闸。现有的孤岛检测方法要么具有它们无法工作的操作区域，要么需要将人工信号注入到电网中，这会影响电能质量。最困难的操作条件是当分布式发电机和其本地负载网络之间存在功率平衡时。在这种情况下，许多系统不会检测到电网连接已经丢失，因为事件不会改变基频量。许多可再生发电系统需要并网逆变器将功率传输到电网。这是必要的，因为发电源本身很少能够以电网频率发电。并网逆变器必须能够检测到失网事件。本提案将研究一种新的方法，使用模式识别与高采样率。需要模式识别系统来分析逆变器输出电压和电流，以确定是否发生了失网事件。该建议的新奇在于，在实时分析中包括由于PWM效应而产生的高频信息。这样做的好处是，当存在功率平衡条件时，信息仍将可用于模式识别系统。人们担心，许多孤立的检测系统不能免受其他相邻设备的影响。该设备可以是电力电子负载或其他并网逆变器。所提出的方法的基础是，模式识别系统将能够区分电网连接的存在和不存在，尽管来自相邻设备的潜在干扰信号。所提出的方案的一个主要优点是，它利用高频信号产生的PWM开关在逆变器。这些信号是通过使用高采样率从输出电压和电流中提取的，其中在一个PWM周期内采集多个样本。当平衡负载条件存在时，这些信号将仍然存在，因此将在这种困难条件期间提供有价值的诊断信息。这些高频信号将添加到与基频分量相关的信号中，以检测电网事件的丢失。重要的是，该方案将通过实验进行验证，因此将制作一个包含一系列典型负载和其他并网发电机的试验台。该装置将用于评估在其他邻近电力电子设备存在的情况下拟议方案的性能。如果成功，该研究将对可再生能源发电与配电系统的整合产生重大影响。这将对配电系统的安全性和并网逆变器的制造商带来重大利益。

There is an urgent need to expand the use of renewable energy generation systems to meet UK government targets. The expansion of grid-connected renewable energy sources must be done in a way which does not reduce the security of the power distribution system. Integral to power distribution system security is the ability of distributed generators to reliably detect a loss of grid condition. This is important to prevent unwanted islanded sections of the system which continue to be energised after the grid connection is lost. An islanding system occurs when a part of the grid system become disconnected from the rest of the network but continues to be energised by localised distributed generation systems. Islanded systems are (i) potentially hazardous to power system workers, (ii) may operate outside voltage and frequency tolerance, (iii) may be inadequately grounded and (iv) may not re-synchronise properly leading to undesirable protection trips. The existing approaches to islanding detection either have operational regions in which they fail to work or are required to have artificial signals injected into the grid which can impact on power quality. The most difficult operational condition is when there is a power balance between a distributed generator and its local load network. During this condition many systems will not detect that the grid connection has been lost because the fundamental frequency quantities are not altered by the event.Many renewable generation systems require a grid-connected inverter to transfer power into the grid. This is necessary because the generating source itself is rarely capable of producing power at grid frequency. A grid-connected inverter must be able to detect the loss of grid event. This proposal will investigate a novel approach using pattern recognition with a high sampling rate. The pattern recognition system is required to analyse the inverter output voltages and currents to determine if a loss of grid event has taken place. The novelty in this proposal is to include the high frequency information due to PWM effects in the real-time analysis. The benefit of doing this is that information will still be available to the pattern recognition system when a power balance condition exists.There is concern that many islanded detection systems are not immune from the effects of other neighbouring equipment. This equipment may be power electronic loads or other grid-connected inverters. The basis of the proposed approach is that the pattern recognition system will be able to discriminate between the presence and absence of the grid connection despite potential interference signals from neighbouring equipment. A major advantage of the proposed scheme is that it makes use of high frequency signals generated by the PWM switching in the inverter. These signals are extracted from the output voltages and currents by using high sampling rates where a number of samples are taken during one PWM cycle. These signals will still be present when a balance load condition exits and therefore will provide valuable diagnostic information during this difficult condition. These high frequency signals will add to the signals associated with the fundamental frequency components to detect the loss of grid event.It is important that this scheme is demonstrated experimentally and therefore a test rig will be produced which contains a range of typical loads and other grid-connected generators. The rig will be used to evaluate the performance of the proposed scheme in the presence of other neighbouring power electronic equipment.If successful the research will have major impact on the integration of renewable energy generation into power distribution systems. There will be significant benefits to power distribution system security and to the manufacturers of grid-connected inverters.