Faults in power systems cause voltage sags, which, in turn, provoke large current peaks in gridconnected equipment. Then, a complete knowledge of the inverter behaviour is needed to meet fault ridethrough capability. The aim of this paper is to propose a mathematical model that describes the behaviour of the currents that a three-phase inverter with RL filter inject to a faulty grid with symmetrical and unsymmetrical voltage sags. The voltage recovery process is considered, i.e., the fault is assumed to be cleared in the successive zero-cross instants of the fault current. It gives rise to a voltage recovery in different steps (discrete voltage sag), which differs from the usual model in the literature, where the voltage recovers instantaneously (abrupt voltage sag). The analytical model shows that the fault-clearing process has a strong influence on the injected currents. Different sag durations and depths have also been considered, showing that there exist critical values for these magnitudes, which provoke the highest current peaks. The analytical study is validated through simulations in MATLAB TM and through experimental results.
Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.
Recently, the global concern for protection coordination is growing with the impact of distributed generators connected to medium voltage distribution system. Effective protection strategies need to be developed in order to avoid undesirable tripping when distributed generators based on Voltage Source Inverters are connected to the medium voltage grid. According to Spanish grid code requirements, the inverter controller response in this paper is assessed under grid faults integrating low voltage ride through capabilities. This paper presents a novel use of a communication‐based directional relay system with artificial neural network, an appropriate option for smart grids protection. A protection strategy is proposed using two algorithms. The first algorithm is based on gathering data of all the protective devices in the grid and send it to a centralized controller. The second algorithm is based on a zone controller using the communication between the peer protection devices in the same line. One of the main advantages of the zone controller is that no need to modify the protection devices setting in case of temporary grid reconfigurations. The behaviour of the protection algorithms is validated through both simulations in MATLAB‐Simulink and experimental results.
Abstract. Most of the Maximum Power Point Tracking(MPPT) techniques for Photovoltaic (PV) system utilize the PV voltage and current measurements. An MPPT technique for grid connected PV system, which does not require PV measurements, is proposed and implemented. This approach utilizes post-stage inverter current instead of calculating solar array power. This approach is called Power Conditioning System (PCS). PCS requires a searching engine to track the Maximum Power Point (MPP) of the PV system. Fuzzy logic is one of the most powerful MPPT engines, which has high performance and robustness. Therefore, Fuzzy Logic Control (FLC) method is implemented and compared with the other methods. Moreover a proposed method that combines FLC with PCS is designed and tested. In addition, the PCS employing an adaptive fuzzy controller is also designed in order to enhance system performance and robustness. To compare between classical MPPT techniques and the proposed techniques, simulations of overall system using different MPPT techniques are performed. The simulation results are analysed. Moreover, Practical implementation is carried out to validate the simulation results.
Transformer Rectifier Units (TRUs) are a reliable way for DC generation in several electric applications. These units are formed by multiple three-phase uncontrolled bridge rectifiers connected according to two main topologies (parallel and series), and fed by a phase-shifting transformer, which can have different configurations. Fault diagnosis of the uncontrolled bridge rectifier diodes is one of the most important concerns on the electronic devices, nonetheless, rectifier units are inherently not protected in front of Open-Circuit (O/C) faults, which cause malfunction and performance deterioration. In order to solve this drawback, the proposed fault diagnosis method is based on the O/C fault signature observed in the DC-link output voltage of TRUs rectifier. It allows detecting the O/C diodes of parallel and series TRUs with different phase-shifting transformer configurations and for the most usual fault scenarios. Moreover, it also helps the prediction of diodes that could be exposed to failure after the fault, which provides corrective maintenance for the TRU development. The proposed method is illustrated from MATLAB TM numerical simulations of a 12-pulse TRU, and is validated with experimental tests.
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