Smart Distributed Generation System Event Classification using Recurrent Neural Network-based Long Short-term Memory

High penetration of distributed generation (DG) sources into a decentralized power system causes several disturbances, making the monitoring and operation control of the system complicated. Moreover, because of being passive, modern DG systems are unable to detect and inform about these disturbances related to power quality in an intelligent approach. This paper proposed an intelligent and novel technique, capable of making real-time decisions on the occurrence of different DG events such as islanding, capacitor switching, unsymmetrical faults, load switching, and loss of parallel feeder and distinguishing these events from the normal mode of operation. This event classification technique was designed to diagnose the distinctive pattern of the time-domain signal representing a measured electrical parameter, like the voltage, at DG point of common coupling (PCC) during such events. Then different power system events were classified into their root causes using long short-term memory (LSTM), which is a deep learning algorithm for time sequence to label classification. A total of 1100 events showcasing islanding, faults, and other DG events were generated based on the model of a smart distributed generation system using a MATLAB/Simulink environment. Classifier performance was calculated using 5-fold cross-validation. The genetic algorithm (GA) was used to determine the optimum value of classification hyper-parameters and the best combination of features. The simulation results indicated that the events were classified with high precision and specificity with ten cycles of occurrences while achieving a 99.17% validation accuracy. The performance of the proposed classification technique does not degrade with the presence of noise in test data, multiple DG sources in the model, and inclusion of motor starting event in training samples

Study on the effectiveness of commercial anti‐islanding algorithms in the prospect of mass penetration of PVs in low‐voltage distribution networks

In the coming years, distribution grids will be progressively flooded by renewable energy sources (RES) that will be interconnected with the main grid through power electronic converters. Photovoltaics (PVs) are one of the most promising renewable technologies even for densely built-up areas where space problems are inevitable. The high penetration prospect of PV facilities on low-voltage distribution networks raises questions regarding the necessity of advanced functions that will enable electronically coupled RES to support the operation of distribution grids and to enhance their reliability. In this context, the objective of this study is to investigate the effectiveness of various islanding prevention measures installed in commercial PV inverters, when multiple inverters are operating in parallel with a low-voltage distribution network (LVDN). Extensive experiments were performed under various PV penetration levels, linear/non-linear load and over/under voltage and over/under frequency conditions, as well as for various values of total harmonic distortion of the mains voltage. Further to the primary statistical analysis, the results were analysed in depth by advanced mathematical methods such as box plot and cluster analysis. The findings of this study indicate that commercial anti-islanding techniques present a high probability of failure in the case of multiple PV units at the same point of common coupling, calling for new and more advanced algorithms.European Commission, H2020, 65411

Management of Islanded Operation of Microgirds

Distributed generations with continuously growing penetration levels offer potential solutions to energy security and reliability with minimum environmental impacts. Distributed Generations when connected to the area electric power systems provide numerous advantages. However, grid integration of distributed generations presents several technical challenges which has forced the systems planners and operators to account for the repercussions on the distribution feeders which are no longer passive in the presence of distributed generations. Grid integration of distributed generations requires accurate and reliable islanding detection methodology for secure system operation. Two distributed generation islanding detection methodologies are proposed in this dissertation. First, a passive islanding detection technique for grid-connected distributed generations based on parallel decision trees is proposed. The proposed approach relies on capturing the underlying signature of a wide variety of system events on a set of critical system parameters and utilizes multiple optimal decision tress in a parallel network for classification of system events. Second, a hybrid islanding detection method for grid-connected inverter based distributed generations combining decision trees and Sandia frequency shift method is also proposed. The proposed method combines passive and active islanding detection techniques to aggregate their individual advantages and reduce or eliminate their drawbacks. In smart grid paradigm, microgrids are the enabling engine for systematic integration of distributed generations with the utility grid. A systematic approach for controlled islanding of grid-connected microgrids is also proposed in this dissertation. The objective of the proposed approach is to develop an adaptive controlled islanding methodology to be implemented as a preventive control component in emergency control strategy for microgrid operations. An emergency power management strategy for microgrid autonomous operation subsequent to inadvertent islanding events is also proposed in this dissertation. The proposed approach integrates microgrid resources such as energy storage systems, demand response resources, and controllable micro-sources to layout a comprehensive power management strategy for ensuring secure and stable microgrid operation following an unplanned islanding event. In this dissertation, various case studies are presented to validate the proposed methods. The simulation results demonstrate the effectiveness of the proposed methodologies

Performance Evaluation of Active Islanding-Detection Algorithms in Distributed-Generation Photovoltaic Systems: Two Inverters Case

Grid-connected photovoltaic (PV) inverters employ an islanding-detection functionality in order to determine the status of the electrical grid. In fact, the inverter must be stopped once the islanding operating mode is detected according to standards and grid-code limits. Diverse islanding-detection algorithms have been proposed in literature to cope with this safety requirement. Among them, active methods based on the deliberate perturbation of the inverter behavior can minimize the so-called nondetection zone, which is a range of conditions in which the inverter does not recognize that it is operating in an undesired island. In most cases, the performances of these methods have been analyzed considering a highly dispersed generation scheme, where only one distributed-generation power system is connected to the local electrical power system (EPS). However, in some studies, it has been highlighted that if two or more PV inverters are connected to the same local EPS, their anti-islanding algorithms do not behave ideally and can fail in detecting the islanding condition. However, there is no systematic study that has investigated the overall capability of different anti-islanding methods employed on several inverters connected to the same EPS to detect islanding condition. This paper is a first attempt to carry out a systematic study of the performances of the most common active detection methods in a case of two inverters connected to the same EPS. In order to evaluate the global capability of the two systems to detect islanding condition, a new performance index is introduced and applied also to the case when the two inverters employ different anti-islanding algorithms

An active Anti-islanding method based on phase-PLL perturbation

This paper presents a new active anti-islanding detection method for distributed power generation systems. This method is based on introducing a disturbance at the inverter output and observing the behavior of the voltage at the point of common coupling (PCC), which depends on the impedance connected to the PCC in an islanding situation. The islanding detection is based on the Goertzel algorithm.Velasco De La Fuente, D.; Trujillo Rodríguez, CL.; Garcerá Sanfeliú, G.; Figueres Amorós, E. (2011). An active Anti-islanding method based on phase-PLL perturbation. IEEE Transactions on Power Electronics. 26(4):1056-1066. doi:10.2089643S1056106626

A robust islanding detection method with zero-non-detection zone for distribution systems with DG

This paper proposes a strategy for detecting unintentional islanding operations (IOs) in distribution networks (DNs) with distributed generation (DG), which eliminating the non-detection zone (NDZ). This hybrid method achieves a zero-NDZ by taking advantage of both passive and active methodologies for an inverter-based DG scenario. The passive-based part of the proposed method considers settings with low thresholds and is activated whenever they are surpassed. The following step uses a three-phase static RC load. This load is connected to intentionally force the frequency and its derivative to exceed the established thresholds. Thus, the events with zero power imbalance can be identified. Unlike other existing methods, this technique does not degrade the power quality (PQ) and does not require DG output power curtailment. The evaluation of the proposed strategy has been carried out through an extensive set of scenarios considering both islanding and non-islanding events. The islanding detection capabilities of the proposed method have been explored considering a custom-made DN test system and the test system recommended by the IEEE 929-2000 standard. The proposed method has a simple implementation, requires a low level of computational complexity, provides a high degree of reliability, and assures fast islanding detection.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.3 - Per a 2030, duplicar la taxa mundial de millora de l’eficiència energèticaObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats SosteniblesPostprint (published version

Effects of energy storage systems grid code requirements on interface protection performances in low voltage networks

The ever-growing penetration of local generation in distribution networks and the large diffusion of energy storage systems (ESSs) foreseen in the near future are bound to affect the effectiveness of interface protection systems (IPSs), with negative impact on the safety of medium voltage (MV) and low voltage (LV) systems. With the scope of preserving the main network stability, international and national grid connection codes have been updated recently. Consequently, distributed generators (DGs) and storage units are increasingly called to provide stabilizing functions according to local voltage and frequency. This can be achieved by suitably controlling the electronic power converters interfacing small-scale generators and storage units to the network. The paper focuses on the regulating functions required to storage units by grid codes currently in force in the European area. Indeed, even if such regulating actions would enable local units in participating to network stability under normal steady-state operating conditions, it is shown through dynamic simulations that they may increase the risk of unintentional islanding occurrence. This means that dangerous operating conditions may arise in LV networks in case dispersed generators and storage systems are present, even if all the end-users are compliant with currently applied connection standards