Real-time Simulation Platform Research Articles

Coordinated Control of Intentional Islanding and Phase Sequence Exchange for Enhancing Transient Stability of Isolated Power Grid

An isolated power grid (IPG) is electrically weakly connected to the utility power grid, and intentional controlled islanding (ICI) can secure IPG from external faults. Phase Sequence Exchange (PSE) is a recently developed emergency control technology in which power electronic devices are used to switch the three-phase sequence, thereby reducing the power angle of the generator by 120° and preventing the system from losing stability. This paper proposed a coordinated control scheme for PSE and ICI. After the system is disturbed, the local measurement of the interconnection line between IPG and the utility grid is used to assess the system's stability. PSE is adopted to adjust the power flow direction to reduce the transient energy of IPG. At the same time, using the internal measurement of IPG, the transient energy of IPG is calculated in real-time, and the critical energy is rolling refreshed based on offline information. After PSE reduces the energy of IPG to lower than the critical energy, IPG is safely disconnected from the utility grid. The proposed scheme needless to adjust the internal generator or load of IPG and is verified on the real-time digital simulator (RTDS) platform with a PSE prototype.

Entirely Coupled Recurrent Neural Network-Based Backstepping Control for Global Stability of Power System Networks

In an interconnected power system network, global performance is affected by various unknown power system parameters subjected to system uncertainties. These unknown parameters in the control expression deteriorate the performance of the power system network. Therefore, these terms associated with the control expression must be estimated precisely. This paper proposes an adaptive backstepping scheme using an entirely coupled recurrent neural network (ECRNN) to estimate these control terms. Three continuous differentiable functions are used to design control input, virtual signals, and adaptive control laws to achieve global performance. The objective of ECRNN is to reduce the control complexity by estimating the associated nonlinear term in the control expression. It will facilitate the complex formulation of the controller and improve system performance. The robust functional estimation ability of ECRNN will make the system immune to uncertainties that may appear due to external disturbances. In ECRNN, feedback loops are added to each neuron layer to achieve additional estimation accuracy. The proposed adaptive law enhances the online weight update speed and accuracy. Verification of the proposed scheme is carried out in MATLAB/Simulink. It is also verified in the real-time digital simulator (RTDS) platform using the IEEE standard New England 39-bus, 10-machine power system model. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the existing limitations in the global performance of a multimachine power system network due to uncertainty in the system parameters. Uncertainties in the power system network primarily appeared due to penetration of renewable power sources, load uncertainty, or occurrence of an uncertain fault in the network. As power system networks are complex nonlinear interconnected systems, these perturbations in the generator states may cause economic losses, load demand uncertainty, or electric scarcity. Thus, a control scheme is required to address the global performance of such networks. This article proposes uniform ultimate bounded stability of synchronous generators in a multimachine power system network with a robust ECRNN-based backstepping control design. The other available technique has not adequately addressed the global performance under uncertainties. The efficacy of the proposed scheme is verified in a real-time environment via a real-time digital simulator which may be a feasible solution for designing excitation control for the synchronous machine in an extensive industrial network.

A privacy-preserving anomaly diagnosis scheme for AC microgrids

The integration of cyber infrastructure in renewable energy source based AC microgrids (MGs) raises concerns about potential cyber attacks on such systems. An adversary can fabricate the information being exchanged between system components, which may cause false tripping of the installed protection devices. This creates the need for an anomaly diagnosis scheme that can distinguish between faults and cyber attacks to attain a reliable and secure system under large signal disturbances. This work presents a machine learning-based anomaly diagnosis scheme which characterizes these anomalies. The scheme uses the well-known XGBoost approach, and requires local measurements (such as, active power, reactive power, and frequency) of inverter-interfaced distributed energy resources (IIDERs). Since such measurements may be difficult for participants in a system to share across organizational boundaries due to commercial or regulatory concerns, the proposed approach obfuscates the measurements by additive noise while preserving detection accuracy. This scheme was tested on an AC MG network with four IIDERs, modeled on a real-time simulation platform in an OPAL-RT environment. The results validate the effectiveness and accuracy of the proposed scheme under different conditions.

An novel oscillation suppression strategy for permanent magnetic synchronous generator based on grid-forming control

With the increase of permeability of renewable energy and power electronic equipment, the inertia and damping parameters of the direct-drive wind turbine based on grid-forming control have a large impact on the system stability, and the system oscillation will be triggered when the parameters are not set properly. In this paper, the problem is addressed by establishing the small-signal model of two permanent magnetic synchronous generators connected to the grid in detail, analyzing the influence of the active control parameters on the system stability through the root locus of the dominant characteristic root, and proposing the adaptive control of damping and inertia to suppress the system oscillations. Finally, a real-time simulation platform for grid-connected wind turbine systems was built, and the experimental results verify the correctness of the small-signal modelling for stability analysis of grid-forming wind turbines established in this paper.

Nonintrusive Condition Monitoring of FCEV Using System-Level Digital Twin Model

High maintenance costs and short lifecycles are two main issues in fuel cell electric vehicle (FCEV) development. With the development of digital technology, the concept of digital twins provides new opportunities for monitoring and predicting the behavior of FCEV. However, the constitution of the digital model of FCEV faces many challenges caused by the multi-physical domain. In this paper, a digital model is built for condition monitoring of FCEV in both short-term and long-term. The built model reflects the interaction of multi-physicals domains by representing the FCEV using the energetic macroscopic representation (EMR) method. Moreover, by considering different road condition, the effect of different driving modes can be shown through the energy flow between the battery and the fuel cell. And the model can give a visible reflection of the electric, magnetic, mechanical, and chemical inside the vehicle. To further investigate the effect of all the above factors on the long-term operation status, the echo state network (ESN) is used to predict the degradation phenomenon of the proton exchange membrane fuel cells (PEMFC), which is used for prognostic purposes. At last, the digital twin test bench is shown with a real-time simulation platform of the OPAL-RT.

Asynchronous co-simulation of photovoltaic power generation system based on FPGA-CPU

In order to realize the real-time electromagnetic transient simulation of grid-connected photovoltaic power generation system with small time step, a heterogeneous multiplexed parallel real-time simulation method based on field programmable gate array (FPGA) and central processor is studied. According to the simulation accuracy requirements of the high and low frequency decoupling module, a differentiated simulation step size is used to solve the problem, and a 1us/50us FPGA-CPU multi-rate real-time simulation platform is constructed, in which the FPGA simulation part meets the real-time requirements of small-step transient simulation through the optimization of the response matching method and the EMTP algorithm, the offline simulation results are compared with Simulink, and the model before and after optimization is analyzed, the real-time electromagnetic transient simulation results are compared with Simulink, and the model before and after optimization is analyzed. By comparing the offline simulation results with Simulink and analyzing the FPGA resource consumption before and after model optimization, the accuracy and real-time performance of the co-simulation method for real-time simulation of grid-connected photovoltaic systems are verified.

A robust damping control for battery energy storage integrated power systems to mitigate inter-area oscillations

This paper presents the effect of a Battery Energy Storage System (BESS) on the power system inter-area oscillations under changing load conditions. The dynamic interaction between the BESS control modes and synchronous generators, along with BESS control parameters, influence the damping of prominent inter-area oscillations under different loading conditions. Furthermore, H∞ mixed sensitivity scheme-based Wide-Area Damping Controller (WADC) is proposed for BESS. This controller is designed using the Linear Matrix Inequality (LMI) framework to mitigate the prominent inter-area oscillation of the power system. Sensitivity to control parameter variation and the geometric measure of the observability are utilized to select the location and feedback signal for the WADC. The performance of the proposed WADC is compared with an Energy Storage System-based stabilizer and WADC proposed in an existing work on a modified New England ten-machine benchmark system. The Real-Time Digital Simulator (RTDS) platform is used to assess the real-time viability of the proposed WADC. The simulation results demonstrate that the proposed WADC can effectively diminish several inter-area modes. Additionally, it offers robust performance under varying load conditions, contingencies and with communication delays in feedback signals. The proposed controller is also effective under the system integrated with Doubly Fed Induction Generator-based Wind Turbine System.

A novel power control scheme for distributed DFIG based on cooperation of hybrid energy storage system and grid-side converter

Due to the uncertainty of wind energy, the wind power is difficult to be dispatched and may cause the voltage fluctuations for distributed network. Therefore, a novel power control scheme is proposed to manage the output power of the distributed doubly-fed induction generator (DFIG) by cooperating the hybrid energy storage system (HESS). In the proposed scheme, the grid-side converter of DFIG is controlled to manage overall output power of the DFIG/HESS hybrid system in accordance to the power dispatching command. The HESS is utilized to deal with the power difference between DFIG generation power and the power dispatching command. The HESS is embedded in the DC-link bus of DFIG and is composed of superconducting magnetic energy storage and batteries. Additionally, in order to avoid HESS from overcharging and over-discharging, the pitch angle control and power dispatching command are adjusted by considering the state of charge (SOC) of HESS. Finally, the simulation model of distributed DFIG and HESS is built on the real-time digital simulation (RTDS) platform, and the simulation results validate the effectiveness and reliability of the proposed power control scheme.

Advanced Frequency Control Technique Using GTO with Balloon Effect for Microgrids with Photovoltaic Source to Lower Harmful Emissions and Protect Environment

Renewable energy (RE) resources such as wind and PV solar power are crucial for transitioning to carbon-free and sustainable energy systems, especially for agricultural and domestic applications in the desert and rural areas. However, implementing RE resources may lead to frequency penetrations, especially in isolated microgrids (µGs). This study proposes an adaptive load frequency control (LFC) technique for power systems. An integral controller can be tuned online using an artificial gorilla troops optimization algorithm (GTO), which is supported using a balloon effect (BE) identifier. Adaptive control is used to control the system frequency in case of variable loads and fluctuation due to 6 MW photovoltaic (PV). Three other optimization methods have been compared with the GTO + BE technique, namely the Grey Wolf Optimization method (GWO), the standard artificial gorilla troops optimization (GTO) and the Jaya technique. Digital simulation tests approved the efficiency of (GTO + BE) during system difficulties such as load disturbance and system parameter variations. In addition, the same test conditions have been repeated using a real-time simulation platform. The real-time simulation results supported the digital outcomes.

Fixed time adaptive fault tolerant sliding mode control of PEMFC air supply system

Guaranteeing rapid management of oxygen excess ratio (OER) for proton exchange membrane fuel cells (PEMFC) under load variations is a challenge with practical significance. To improve the controller response of PEMFC air supply system, a fixed time fault-tolerant control strategy is proposed in this paper. A fixed convergence time of PEMFC air supply control system is quantified and guaranteed by the proposed method and the control response can be accelerated by reducing the setting time. The contributions of this paper is fourfold. Firstly, the manifold leakage fault is estimated by fixed time fault observer, which can improve the real-time fault tracking performance of the control system. Secondly, a hierarchical fixed time sliding mode controller is proposed to regulate the OER rapidly. Furthermore, a novel adaptive term is employed to reduce the effects of the chattering from fault observer in the outer loop. Finally, the effectiveness of the proposed method is verified on a real-time PEMFC simulation platform. Experimental results on a Hardware-in-the-loop (HIL) platform show that the proposed fixed time fault tolerant control strategy has the characteristics of fast response and high robustness.

Analytical voltage sensitivity-based distributed Volt/Var control for mitigating voltage-violations in low-voltage distribution networks

Integrating solar photovoltaic system in low-voltage distribution networks leads to significant voltage violations. This issue can be alleviated using the cutting-edge control techniques (Volt/Var control, Volt/Watt control, etc.) of smart inverters. Moreover, the smart inverters absorb/inject the necessary amount of reactive power from/into the substation to alleviate the over/under voltages. This increases the reactive power burden on the substation and deteriorates its power factor. Therefore, this paper proposes a novel distributed Volt/Var control technique to reduce the dependency on substations for reactive power support and improve its power factor. The proposed technique is based on analytical voltage sensitivity analysis. By developing suitable relations, the feeder nodes are categorized into two groups, one operating in lagging mode, while the other in leading mode. This ensures proper utilization of reactive power capability of the inverters. An IEEE 13-node low voltage distribution network with the solar photovoltaic system at different load conditions is used to test the proposed and other existing Volt/Var control techniques. Compared to other distributed Volt/Var control techniques, the proposed method requires a minimum reactive power support to regulate the feeder voltage. Additionally, the obtained results by the proposed method are closer to those by the optimal reactive power support approach using GAMS software and are validated on a real-time digital simulator platform.

Real-time simulation for detailed wind turbine model based on heterogeneous computing

The deployment of sophisticated and costly large-capacity wind turbines continues to rise. It is urgent for precise real-time simulation to accurately identify and address potential problems. However, the existing solutions, which joint various simulation platforms, suffer from the disadvantages of complex architecture and high cost. This paper proposes a CPU-FPGA heterogeneous computing-based real-time simulation platform for detailed wind turbine model (DWTM). DWTM encompasses the turbine model (covering the inflow wind, aerodynamic, and mechanical dynamic), the electrical model (covering the electromagnetic transient), and the control system. The real-time operating system is introduced to guarantee the real-time performance of the turbine model and control system in the CPU. FPGA is used to perform real-time electrical model calculation. Furthermore, a general FPGA solver for electromagnetic transients is designed. It can accommodate various circuit topologies without the need for recompiling the FPGA code. Finally, the real-time simulation performance and accuracy are verified. The coupled dynamics between the turbine and electrical models are investigated under multiple power grid and wind conditions.

ECS-Grid: Data-Oriented Real-Time Simulation Platform for Cyber-Physical Power Systems

ECS-Grid is the first data-oriented real-time electromagnetic transient simulation platform for cyber-physical power systems (CPPS). Traditional simulation tools are constrained by object-oriented programming (OOP) architecture, which is now a significant obstruction to creating a comprehensive cyber-physical simulation. Therefore, the proposed ECS-Grid platform follows a new data-oriented paradigm based on an Entity-Component-System (ECS) framework, which delivers higher flexibility, extensibility, scalability, and performance to support cyber-physical system research. ECS-Grid proposes a layer of virtual intelligent electronic devices (vIEDs) to model IEDs in CPPSs. The vIEDs directly talk to physical components and communicate asynchronously with cyber services via the proposed high-performance JSON-like binary protocol. Tests with the islanding and the man-in-the-middle cyber attack scenarios on a 711-node AC-DC microgrid cluster based on a modified CIGRE 15-Bus system are performed and give accurate results. A faster-than-real-time performance is achieved on the 10th Gen Intel <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> Core <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TM</sup> i7 computer, and real-time performance is achieved on distributed embedded NVIDIA <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> Jetson platform. The ECS-Grid design and test results demonstrate the potential of the ECS data-oriented paradigm and may inspire the renovation of industrial simulation software.

Performance Analysis of 9, 11, 13, and 15 – Level Back-to-Back Connected Modular Multilevel Converters fed Doubly Fed Induction Machine

In this paper, back-to-back Modular Multilevel Converters are used to feed the Doubly Fed Induction Machine. The MMC with 9, 11, 13, and 15 – Level output voltages are generated and fed to the DFIM and the performance of the DFIM is analyzed, when the machine is working as Doubly Fed Induction Generator (DFIG) and when the machine is working as Doubly Fed Induction Motor. The performance of the DFIG is analyzed in terms of power factor at Grid Side Converter (GSC) for different levels of operation of MMC. The results show that the power factor is maintained near to unity power factor at grid side. The performance of the Doubly Fed Induction Motor is analyzed in terms of variation of the load torque being applied to motor. The results show that there is clear variation of the speed for two different load conditions. The work is carried out by using Typhoon HIL Real-Time Simulation platform, i.e., both Software and Hardware.

Implementation and Verification of Real-Time Hybrid Simulation for the Dynamic Performance Assessment of Base-Isolated Structures

Real-time hybrid simulation (RTHS) is an economical and reliable method for the evaluation of structural dynamic performances, and the fixed analytical substructure model is often used in RTHS which may affect the accuracy of results. In this study, a real-time hybrid simulation platform (RTHSP) developed by configuring a generic National Instruments (NI) controller with hybrid programming strategy is presented in detail. The dynamic performances of a scaled base isolated structure, where the unscented Kalman filter (UKF) was used to update the analytical substructure Bouc–Wen model during the RTHSs was evaluated by presented RTHSP. RTHS of a base-isolated structure was performed where a lead rubber bearing (LRB) was tested physically as the experimental substructure of a part of the isolation layer and the superstructure with the rest of the isolation layer model updated by UKF was considered as the analytical substructure. Under the excitation of three natural earthquakes, the RTHSs with and without UKF updating were compared and analyzed the differences between the two. The results indicated that the displacements of experimental substructure generated by RTHS with UKF updating are the largest, while the relative displacements and acceleration of superstructure are the smallest overall, and the dynamic characteristics of the isolation layer of the analysis substructure updated by UKF are different from that without updated, which reflected the more authentic dynamic mechanical performance of the base-isolated structure under earthquake excitation. In addition, the RTHSP and the hybrid programming strategy are verified to be reliable in tests and experiments, and the components and implementation of a RTHSP for base-isolated structures is described in detail, providing a reference for research on RTHS method.

Spatiotemporal Pattern Analysis of Nodal Inertia Using Convex Combination of Walks of Generator Nodes in Varying Inertia System

The distinct requirement of high control and faster frequency regulation from wind turbine generator (WTG) needs to look at the network's local and global vulnerabilities. In line with the above objective, the article elucidates 1) The role of generation units' contribution in handling the disturbances and their propagation in the network, and 2)The behavior of dynamic response of the nodes in the presence of faster frequency regulation action from WTG. The authors propose a novel online Nodal Inertia Index (NII) that considers the network's structural features and generator dynamic response in the varying inertia system. NII investigates the inherent property of the distribution of inertia in the system by the concept of graph theory convex combination of walks of generator nodes. Further, the article explores the dynamic response of nodes (DRN) in terms of disturbance location from the generator bus and also considers generators' internal interactions. DRN employs the Fiedler vector to observe the global response and locational impact. The application of NII and DRN in selecting reserve percentages of the WTG is showcased. All the analyses are performed in the modified IEEE 9,39 and 68 bus, coordinating between the Real-Time Digital Simulator (RTDS) and MATLAB platform.

Development of a real-time framework between MATLAB and PLC through OPC-UA: A case study of a microgrid energy management system

Numerous research laboratories engaged in developing advanced algorithms for controlling Renewable Energy Systems (RES) face constraints due to the absence of specialized equipment for conducting research and experiments. Real-time simulation platforms are well-suited for creating fast or real-time computation models, offering prompt, accurate, and reliable insights for RES control implementation. Nevertheless, the high cost of real-time platforms renders them unaffordable for many laboratories. To address this issue, a cost-effective platform is designed to assist researchers in their activities. The hardware solution involves utilizing a Programmable Logic Control (PLC) to acquire data from diverse sensors and regulate the system through actuators and PI controllers. From a software perspective, a communication framework between MATLAB and the PLC is developed using OPC-UA (Open Platform Communications Unified Architecture) technology. In this paper, the operation and efficiency of the platform have been tested using the Software in the Loop (SIL) technique. The operating model is designed using MATLAB/Simulink to simulate and analyze the appropriate control technique suitable for PLC implementation, whereas the control is executed through Siemens S7–1200 PLC using TIA PORTAL. A visualization interface is established using WinCC-RT. Moreover, this paper presents the platform's design, discusses its application, and illustrates its usage through a case study. Indeed, a complex algorithm developed in MATLAB/Simulink can be automatically executed by any PLC using the designed framework.

Reproduction of transport-induced vibration of paintings based on a multi-channel FxLMS controller

Monitoring the vibration of the painting canvas during transport is of great significance to protect paintings from damage. However, limited to the narrow structure of the transport crate, the lack of an inertial reference, and the limitations to attach sensors to the canvas, this is a difficult task. For this reason, based on vibration data measured on the strainer that is easily obtained during transport, this contribution proposes to reproduce these with high accuracy in the laboratory. There, the resulting vibration of the canvas can be conveniently observed in a controlled environment with respect to an inertial reference. A real-time simulation platform based on the multi-channel Filtered-x Least Mean Square (FxLMS) algorithm controls four actuators simultaneously and reproduces the vibration of the strainer obtained from a real transport experiment. The vibration of the canvas is then measured by a laser Doppler vibrometer without contact. The experimental results show that the vibration reproduction system has sufficient reproduction accuracy for the vibration response. Even though some overshoot in the reproduced acceleration can be observed in some cases, the overall reproduction is very good. A long-term reproduction experiment verifies its stable reproducibility. Therefore, the designed vibration reproduction system provides a reference for the unknown canvas response during transport, and further helps art conservators to evaluate the transport process of the painting.

A novel decentralized inverter control algorithm for loss minimization and LVRT improvement

Algorithms that adjust the reactive power injection of converter-connected RES to minimize losses may compromise the converters’ fault-ride-through capability. This can become crucial for the reliable operation of the distribution grids, as they could lose valuable resources to support grid voltage at the time they need them the most. This paper explores how two novel loss-minimizing algorithms can both achieve high reduction of the system losses during normal operation and remain connected to support the voltage during faults. The algorithms we propose are decentralized and model-free: they require no communication and no knowledge of the grid topology or the grid location of the converters. Using local information, they control the reactive power injection to minimize the system losses. In this paper, we extend these algorithms to ensure the low voltage ride through (LVRT) capability of the converters, and we integrate them with state-of-the-art Wavelet-CNN–LSTM RES forecasting methods that enhance their performance. We perform extensive simulations on the real-time digital simulation (RTDS) platform, where we demonstrate that the algorithms we propose can achieve a substantial decrease in power losses while remaining compliant with the grid codes for LVRT makes them suitable for the implementation across the distribution system.

Design and implementation of a real-time simulation platform for embedded applications on general-purpose operating systems

In recent years, the number of invested resources adopted in experiments of embedded applications dropped significantly as many simulation technologies are widely used. However, the efficiency of simulations is seriously influenced by some expensive and difficult-to-obtain devices. It is urgent and of great significance to build a universal simulation platform for embedded applications on general-purpose operating systems with an objective of improving the efficiency and effectiveness of system development and implementation. Since virtualization technology can greatly enhance the simulation efficiency by providing virtual models to simulate the behaviors of real devices, this paper designs and realizes a real-time simulation platform on general-purpose operating systems with the virtualization technology such that embedded applications would be correctly and efficiently debugged and tested on the general-purpose operating systems. The proposed simulation platform contains four layers named hardware resource, virtualization, virtual runtime environment, and interface adaptation, allowing dynamic debugging and testing of embedded applications without requiring the actual presence of real devices. Experiments are conducted to verify the functionalities of the proposed simulation platform, and results demonstrate that the proposed simulation platform can meet the real-time and high reliability requirements of embedded applications.