1-D Convolutional Graph Convolutional Networks for Fault Detection in Distributed Energy Systems

This paper presents a 1-D convolutional graph neural network for fault detection in microgrids. The combination of 1-D convolutional neural networks (1D-CNN) and graph convolutional networks (GCN) helps extract both spatial-temporal correlations from the voltage measurements in microgrids. The fault detection scheme includes fault event detection, fault type and phase classification, and fault location. There are five neural network model training to handle these tasks. Transfer learning and fine-tuning are applied to reduce training efforts. The combined recurrent graph convolutional neural networks (1D-CGCN) is compared with the traditional ANN structure on the Potsdam 13-bus microgrid dataset. The achievable accuracy of 99.27%, 98.1%, 98.75%, and 95.6% for fault detection, fault type classification, fault phase identification, and fault location respectively.Comment: arXiv admin note: text overlap with arXiv:2210.1517

Control of Four-Wire Inverter-Interfaced DGs for Accurate Fault Type Classification

Inverter-interfaced distributed generators (IIDGs) generate fault currents that are different from those generated by conventional synchronous generators (SGs). As a result, commercial relays—that utilize current-angle-based phase selection measurements—misidentify faulty phase(s), which adversely impact the grid resiliency and reliability. In this thesis, a new control scheme is proposed to regulate the sequence components of the IIDG currents during unbalanced faults to ensure accurate fault type classification by commercial relays. The proposed controller controls the positive-sequence and negative-sequence currents in the dq-frame with a decoupled synchronous reference frame (DDSRF) based phase-locked loop (PLL) for components extraction and synchronization. It also uses a second order generalized integrator (SOGI) based PLL to synchronize the zero-sequence components. This scheme forces the angles of the negative-sequence and zero-sequence fault IIDG currents to behave like those of an SG while preserving the inverter’s current limits. This leads to proper fault type classification. The proposed control scheme pertains to three-wire IIDGs as well as four-wire IIDGs, which are common in low-voltage distribution networks. A performance evaluation using time-domain simulations is used on a benchmark network to confirm the success of the proposed control scheme under different fault conditions

The recent development of protection coordination schemes based on inverse of AC microgrid: A review

Integration of distributed generation systems and diversity of microgrid operations led to a change in the structure of the power system. Due to this conversion, new challenges have arisen when employing traditional overcurrent protection schemes. As a consequence, non‐classical protection schemes have attracted significant attention in the last few years. Engineers and scholars have proposed different non‐standard methods to increase the power protection system and ensure the highly selectivity performance. Although the non‐standard characteristics and their requirements, in general, have been outlined and analyzed in the available literature, protection coordination based on voltage current–time inverse, as a branch of non‐standard optimization methods, has not yet been thoroughly discussed, compared, or debated in detail. To close this gap, this review introduces a broad overview of recent research and developments of the voltage current–time inverse based protection coordination. Focuses on assessing the potential advantages and disadvantages of related studies and provide a classification and analysis of these studies. The future trends and some recommendations have been included in this review for improving fault detection sensitivity and coordination reliability

On the assessment of cyber risks and attack surfaces in a real-time co-simulation cybersecurity testbed for inverter-based microgrids

The integration of variable distributed generations (DGs) and loads in microgrids (MGs) has made the reliance on communication systems inevitable for information exchange in both control and protection architectures to enhance the overall system reliability, resiliency and sustainability. This communication backbone in turn also exposes MGs to potential malicious cyber attacks. To study these vulnerabilities and impacts of various cyber attacks, testbeds play a crucial role in managing their complexity. This research work presents a detailed study of the development of a real-time co-simulation testbed for inverter-based MGs. It consists of a OP5700 real-time simulator, which is used to emulate both the physical and cyber layer of an AC MG in real time through HYPERSIM software; and SEL-3530 Real-Time Automation Controller (RTAC) hardware configured with ACSELERATOR RTAC SEL-5033 software. A human–machine interface (HMI) is used for local/remote monitoring and control. The creation and management of HMI is carried out in ACSELERATOR Diagram Builder SEL-5035 software. Furthermore, communication protocols such as Modbus, sampled measured values (SMVs), generic object-oriented substation event (GOOSE) and distributed network protocol 3 (DNP3) on an Ethernet-based interface were established, which map the interaction among the corresponding nodes of cyber-physical layers and also synchronizes data transmission between the systems. The testbed not only provides a real-time co-simulation environment for the validation of the control and protection algorithms but also extends to the verification of various detection and mitigation algorithms. Moreover, an attack scenario is also presented to demonstrate the ability of the testbed. Finally, challenges and future research directions are recognized and discussed

Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems

Fault diagnostics are extremely important to decide proper actions toward fault isolation and system restoration. The growing integration of inverter-based distributed energy resources imposes strong influences on fault detection using traditional overcurrent relays. This paper utilizes emerging graph learning techniques to build a new temporal recurrent graph neural network models for fault diagnostics. The temporal recurrent graph neural network structures can extract the spatial-temporal features from data of voltage measurement units installed at the critical buses. From these features, fault event detection, fault type/phase classification, and fault location are performed. Compared with previous works, the proposed temporal recurrent graph neural networks provide a better generalization for fault diagnostics. Moreover, the proposed scheme retrieves the voltage signals instead of current signals so that there is no need to install relays at all lines of the distribution system. Therefore, the proposed scheme is generalizable and not limited by the number of relays installed. The effectiveness of the proposed method is comprehensively evaluated on the Potsdam microgrid and IEEE 123-node system in comparison with other neural network structures

Fault Management in DC Microgrids:A Review of Challenges, Countermeasures, and Future Research Trends

The significant benefits of DC microgrids have instigated extensive efforts to be an alternative network as compared to conventional AC power networks. Although their deployment is ever-growing, multiple challenges still occurred for the protection of DC microgrids to efficiently design, control, and operate the system for the islanded mode and grid-tied mode. Therefore, there are extensive research activities underway to tackle these issues. The challenge arises from the sudden exponential increase in DC fault current, which must be extinguished in the absence of the naturally occurring zero crossings, potentially leading to sustained arcs. This paper presents cut-age and state-of-the-art issues concerning the fault management of DC microgrids. It provides an account of research in areas related to fault management of DC microgrids, including fault detection, location, identification, isolation, and reconfiguration. In each area, a comprehensive review has been carried out to identify the fault management of DC microgrids. Finally, future trends and challenges regarding fault management in DC-microgrids are also discussed

Control and estimation techniques applied to smart microgrids : a review

DATA AVAILABILITY : No data was used for the research described in the article.The performance of microgrid operation requires hierarchical control and estimation schemes that coordinate and monitor the system dynamics within the expected manipulated and control variables. Smart grid technologies possess innovative tools and frameworks to model the dynamic behaviour of microgrids regardless of their types, structures, etc. Various control and estimation technologies are reviewed for developing dynamic models of smart microgrids. The hierarchical system of a microgrid control consists of three architectural layers, primary, secondary and tertiary, which need to be supported by real-time monitoring and measurement environment of the system variables and parameters. Various control and estimation schemes have been devised to handle the dynamic performance of microgrids in the function of control layers requirement. Firstly, control schemes in the innovative grid environment are evaluated to understand the dynamics of the developed technologies. Six control technologies, linear, non-linear, robust, predictive, intelligent and adaptive, are mainly used to model the control design within the layer(s) regardless of the types of microgrids. Secondly, the estimation technologies are evaluated based on the state of variables, locations and modelling of microgrids that can efficiently support the performance of the controllers and operating microgrids. Finally, a future vision for designing hierarchical and architectural control techniques for the optimal operation of intelligent microgrids is also provided. Therefore, this study will serve as a fundamental conceptual framework to select a perfect optimal design modelling strategy and policy-making decisions to control, monitor and protect the innovative electrical network.http://www.elsevier.com/locate/rserhj2023Electrical, Electronic and Computer Engineerin

A Virtual Space Vectors based Model Predictive Control for Three-Level Converters

Three-phase three-level (3-L) voltage source converters (VSC), e.g., neutral-point clamped (NPC) converters, T-type converters, etc., have been deemed to be suitable for a wide range of medium- to high-power applications in microgrids (MGs) and bulk power systems. Compared to their two-level (2-L) counterparts, adopting 3-L VSCs in the MG applications not only reduces the voltage stress across the power semiconductor devices, which allows achieving higher voltage levels, but also improves the quality of the converter output waveforms, which further leads to considerably smaller output ac passive filters. Various control strategies have been proposed and implemented for 3-L VSCs. Among all the existing control methods, finite-control-set model predictive control (FCS-MPC) has been extensively investigated and applied due to its simple and intuitive design, fast-dynamic response and robustness against parameter uncertainties. However, to implement an FCS-MPC on a 3-L VSC, a multi-objective cost function, which consists of a term dedicated specifically to control the dc-link capacitor voltages such that the neutral-point voltage (NP-V) oscillations are minimized, must be designed. Nevertheless, selecting proper weighting factors for the multiple control objectives is difficult and time consuming. Additionally, adding the dc-link capacitor voltages balancing term to the cost function distributes the controller effort among different control targets, which severely impacts the primary goal of the FCS-MPC. Furthermore, to control the dc-link capacitor voltages, additional sensing circuitries are usually necessary to measure the dc-link capacitor voltages and currents, which consequently increases the system cost, volume and wiring complexity as well as reduces overall reliability. To address all the aforementioned challenges, in this dissertation research, a novel FCS-MPC method using virtual space vectors (VSVs), which do not affect the dc-link capacitor voltages of the 3-L VSCs, was proposed, implemented and validated. The proposed FCS-MPC strategy has the capability to achieve inherent balanced dc-link capacitor voltages. Additionally, the demonstrated control technique not only simplifies the controller design by allowing the use of a simplified cost function, but also improves the quality of the 3-L VSC output waveforms. Furthermore, the execution time of the proposed control algorithm was significantly reduced compared to that of the existing one. Lastly, the proposed FCS-MPC using the VSVs reduces the hardware cost and complexity as the additional dc-link capacitor voltages and current sensors are not required, which further enhances the overall system reliability

Practical Implementation of Hybrid Energy Systems for Small Loads in Rural South Africa

DissertationHybrid renewable energy systems (HRESs), are alternative off-grid methods of generating power to remote rural areas, where power lines are not economically viable. Most of the research studies on renewable hybrid systems or microgrids (MGs) in South Africa, focus mainly on the optimal sizing and optimal control of different systems, by making use of renewable energy simulation softwares, however, there is a lack of research carried out on the implementation of these hybrid systems in real time. The aim is to develop a real time control method for an isolated hybrid system submitted to a variable load, as well as resources. The first step towards achieving this aim, was to critically review available published research works, to describe recent developments in improving the optimum operating concept of microgrid controllers for stand-alone or grid-connected systems. Secondly, to investigate any real-time implementation established by either hierarchical or distributed control. Then to, analyze their reliability and functionality in practical set up of the controller, in managing power in the system to the variable load. The study provided a brief overview of microgrid prototype systems, microgrid controls, operating modes and multi-DER microgrid types built into a hybrid system, which introduces a number of strategies or techniques for managing remote rural application prototypes in an isolated or grid-connected system. However, hierarchical control was found to be more appropriate for large microgrids with multiple types of distributed energy resources (DERs), compared to distributed control, particularly when combined with energy storage systems (ESSs), in isolated mode. The rising of hybrid system controllers in real-time renewable energy for the optimum energy management system (EMS), required the design of a real-time controller to operate the entire system in real time. Increasing popularity of renewable energy (RE) has a control strategy that determined the overall efficiency of the hybrid system (HS), although the energy management system of these systems is particularly complex to be managed. The study's main contribution is to investigate the feasible controller and, later, to present an advanced control strategy for managing and controlling the flow of hybrid renewable energy with a diesel generator (DG) and battery (BT) as a backup in a rural application of SA. EMS would be implemented, using a fuzzy logic controller (FLC) in MATLAB / SIMULINK. This study analysed input and output variables for the design of a controller, with a set of rules and a three-dimension (3D) surface. Simulation results of related studies with different objectives were analysed, with the aim of sussing out an appropriate controller for the current study. Arduino Mega was used for coding and uploaded to the implementation of practical implementation of the study. The system operated successfully by supplying the load. This study finally answered the question of the feasibility of the controller in real-time applications