Real-time Simulation Environment Research Articles

Low-frequency oscillations damping with doubly-fed induction generators embodying grid-forming control with hardware-in-the-loop simulation

The integration of wind power generation into modern power systems necessitates the development of advanced control strategies to enhance grid stability and reliability. Among these strategies, grid-forming control has emerged as a promising solution, enabling converter-interfaced generation technologies to provide services traditionally supplied by conventional generation. This paper specifically addresses the challenge of low-frequency oscillations damping in power systems incorporating Doubly-Fed Induction Generators embodying grid-forming control. In this paper, two low-frequency oscillations damping strategies are proposed and tested, designed to complement a doubly-fed induction generator grid-forming control strategy. The first, called POD-Q, uses reactive power; while the second, POD-P, acts on the active power injection. Both strategies are analyzed through small-signal stability analysis and experimental testing. For the small-signal stability analysis, a dynamic model of a conventional system with a certain penetration of doubly-fed induction generation has been employed. Experimental results are obtained within a real-time simulation environment, using the hardware-in-the-loop technique to communicate a real controller board with the real-time simulator. The results indicate that the POD-P strategy is more efficient in low-frequency oscillations damping compared to a synchronous generator with a conventional power system stabilizer and also in comparison to the POD-Q strategy. However, both proposed strategies have demonstrated improvements in low-frequency oscillations damping.

Virtual inertia support based frequency and dynamic voltage control for grid-connected SPMSG-based wind turbine

The Challenge to stabilize the grid frequency increases with the increment of renewable energy resources. System inertia/frequency control is a significant concern for maintaining system stability with a fast response time during the load transition. This manuscript proposes surface-mounted permanent magnet synchronous generator (SPMSG) based wind energy conversion system (WECS) with a frequency support DC-link controlling loop and a converter protective DC-link voltage-controller frequency support system. To achieve power exchange, the frequency control system (FCS) for the SPMSG-based wind turbine supports the grid-side virtual inertia. The DC-link voltage is disturbed during the load transition to maintain the frequency, while the electrolytic capacitor requires extra care regarding the DC bus voltage. This manuscript incorporates the FCS system with a supercapacitor and dynamic voltage limiter to avoid additional care of the DC bus voltage. A detailed analysis of system frequency with the additional load increment, normal connected load decrement, and various fault scenarios has been done. The proposed system is compared with the existing virtual inertia support (VIS). The simulation results show that the proposed frequency control system-based VIS efficiently limits the frequency deviations & DC-link voltage. The results are verified in the OPAL-RT 4510 real-time simulator environment to ensure the efficacy of the proposed system.

Synchrophasor-Based Out-of-Step Prediction in Large Grids

Out-of-step (OOS) condition is a potential problem in the power system and uncontrolled islanding is one of the severe consequences of out-of-step condition which leads to cascaded tripping of the system. To avoid this undesired cascaded tripping, early prediction of out-of-step condition is essential before losing the synchronization of generators and between the system areas. Controlled islanding is the last emergency action that can be taken by splitting the system intentionally into coherent islands. Conventionally, OOS condition has been detected with impedance-based measurement techniques which have their own limitations. With the implementation of a wide-area measurement system with synchrophasor measurement units (PMUs) in the power system, it is now possible to measure the bus voltage angle at a much faster rate than with SCADA. In this paper, synchrophasor-based bus voltage angle measurement has been used for early prediction of OOS condition in power systems. A new algorithm has been formulated for both generator and tie lines based on the trajectory of first and second derivatives of the bus voltage phase angle for early detection of OOS condition. The prediction speed of proposed method is found to be between 5% and 70% of time to OOS, after disturbance clearance. The proposed algorithm has been mathematically formulated and evaluated with three benchmark systems in real-time simulation environment with an OPAL-RT real-time simulator and a HYPERSIM platform.

Establishment of Real-Time Simulation Test Environment for Electric Propulsion System of Unmanned Aerial Vehicle Using KDECAN Communication

This paper proposes the construction of a real-time simulation testing environment for the electric propulsion systems of unmanned aerial vehicles (UAVs) using a real-time simulator and KDECAN communication equipment. The proposed real-time simulation environment enables the testing of flight controllers and control algorithms using real-time control communication commands that are identical to those used during actual flight. The KDECAN protocol is analyzed and utilized in the proposed real-time simulation environment for control communication. A reduced-size lift–cruise UAV with eight lift motors (for takeoff) and one cruise motor (for cruising) is used as the target hardware for real-time simulation. This is used to verify the construction of the real-time simulation environment. The final goal of this work is to construct a real-time simulation environment for the stable application of propeller-driven devices, and the findings confirm the independent operation of the lift and cruise motors in the constructed testing environment. Additionally, the real-time monitoring of the state of the electronic speed controllers is verified, suggesting that the testing environment can be utilized as a verification tool for the control algorithms and system design data of electric propulsion systems in actual devices in the future.

Path Loss and Auxiliary Communication Analysis of VANET in Tunnel Environments

Vehicular ad hoc network (VANET) communications face severe fading problems due to the signal reflections and diffractions within tunnels. Unlike the open road, the space of a tunnel is very limited, so VANET communication performance in a tunnel is seriously affected. In the process of signal transmission, the reflected signal is symmetrical with the incident signal after it is reflected by the road and the wall. In this paper, we establish a mathematical model of path loss for V2V (Vehicle-to-Vehicle) communication based on the principle of signal reflection symmetry in tunnels and considering several factors, such as the tunnel surface and the color of the tunnel wall. In addition, we use cooperative communication to form a virtual multiple-input multiple-output (V-MIMO) system, to improve the communication quality in tunnels. In the proposed system, the OBU (On-Board-unit) and RSU (Road-Side-Unit) share each other’s antennas, so that wireless cooperative communication can be employed, without increasing the number of antennas in a one-way tunnel. Therefore, this multipath fading internal electromagnetic wave propagation model can be used to improve performance. A deep reinforcement learning algorithm was used to solve the pairing problem to obtain a more accurate OBU and RSU pair, to form a V-MIMO system. Here, the RSU is regarded as an agent and interacts with the OBU in the tunnel. The optimal strategy was learned in a real-time changing simulation environment, and the experiment verified the convergence of the algorithm. The simulation results showed that, compared with the Q-learning based scheme, the optimal matching algorithm based on V-MIMO and a DQN (Deep Q-network) could effectively reduce the probability of transmission outages and improve the communication efficiency in tunnels.

Development of Control Strategies for Operation of Cluster of Interconnected Hybrid Microgrids in Islanded Mode

This article presents the architecture and control techniques for interconnections of islanded hybrid smart microgrids (MGs, both dc and ac), for transferring the bidirectional power between different MGs. Three ring-type MGs, i.e., one ac microgrid (acMG) and two dc microgrids (dcMGs) operating at different voltages are interconnected to form a power park. A bidirectional dc–dc converter has been used to interconnect two dcMGs, and bidirectional three-phase voltage source converter (VSC) is used to interconnect the dcMG and acMG. The control techniques of these bidirectional VSCs are also proposed to control the operation of interconnected MGs system. The feedforward and feedback control signals are suggested in the proposed control techniques. The objectives of the proposed control techniques are to control the bidirectional power flow between the interconnected MGs, and to establish the constant rated voltages of all MGs, under islanded mode, for various operating scenarios. To check the effectiveness and robustness of the developed interconnected MGs system and proposed control techniques, the simulations have been carried out for the different operating conditions, in the real-time digital simulator environment.

Development of a Scalable MMC Pulsed Power Supply through HIL Methodology

Nuclear fusion experiments are becoming one of the most interesting focuses of research, given the hope of generating programmable, safe, and green energy. Among them, ASDEX (axially symmetric divertor experiment) upgrade has been operating at the Max Planck Institute for Plasma Physics (IPP) research center since 1991. To ignite and confine the plasma, several coils must be supplied through controllable high-current pulsed power supplies. The toroidal field magnets are here considered and a modular multilevel converter (MMC)-like system was designed and tested thanks to a small-scale prototype in previous works. The MMC-like topology, consisting of full-bridge submodules (SMs) with IGBTs and supercapacitor and exploitable also for other industrial applications, was chosen because of its modularity, redundancy, fault tolerance, and large amount of stored energy. The prototype, made of four SMs, was necessary to highlight critical key points in the design process. However, its scalability must be further tested before building a full-scale power supply, meant to reach almost 2400 SMs to guarantee the energy required by the load. This paper aims at validating hardware-in-the-loop (a powerful, safe, and relatively inexpensive real-time simulation environment that enables testing with real control boards) as a useful technology for power supply scalability studies and not only for control strategy tests. The results obtained previously from the prototype will allow us to finally increase the number of SMs and test the MMC-like scalability.

Programmable Crypto-Control for IoT Networks: An Application in Networked Microgrids

In collaborative networked microgrids (NMs), distributed energy resources (DERs) utilize intelligent IoT based controllers to coordinately support various smart community functions. Meanwhile, privacy and security issues occur when IoT-based controllers interact with each other. This paper presents a cryptography-based, programmable control (crypto-control) scheme to provably preserve the privacy of DERs while ensuring fast, flexible distributed control in NMs. Specifically, it makes the following contributions: 1) a programmable crypto-control-based NMs (PCNMs) architecture, where crypto-controllers are fully virtualized, is devised; 2) a novel dynamic encrypted weight addition (DEWA) approach, which integrates an enhanced partial homomorphic encryption and a secret sharing scheme, is devised to ensure privacy preserving of distributed controls; 3) the DEWA privacy-preserving property is mathematically analyzed; and 4) a real-time DEWA-based PCNMs testbed is deployed by incorporating DEWA, real software defined networking switches, and IoT devices. The deployable crypto-control scheme is interfaced with and thoroughly verified in a Real-Time Digital Simulator environment, and the experimental results validate the effectiveness, benefits, and superiority of DEWA-based PCNMs. The inherent resilience of the DEWA-based PCNMs is validated by small signal stability analyses.

Chaos-based optimal path planning of humanoid robot using hybridized regression-gravity search algorithm in static and dynamic terrains

The present work deals with the navigational analysis of humanoids in complex terrains by tuning the classical approach with reactive techniques. Here, the linear regression (LR)-based classical approach is merged with the gravitational search algorithm (GSA), called RGSA, and Chaos is added to achieve an optimum path. To improve upon the local traps, Chaos is introduced into the basic structure of the RGSA model to attain a global solution without effecting the higher convergence rate of the RGSA model. The Chaos further adds ergodicity to the dynamical system, gaining an optimal path length in the shortest time possible. The use of the proposed hybridization technique is found to be effective as compared to its counterparts. Various chaotic maps like the logistic map, Gauss map, piecewise linear chaotic map, and sinusoidal maps are used, and the results are compared. Also, the smoothness of the path is ensured during trajectory planning. The analysis is done in real-time lab conditions and simulation environments using single and multiple humanoids (Nao robots) with static and dynamic obstacles within the search space. The simulation for the path planning is done using the Webot software, while the choregraphe software is used for experimental path planning. The simulation and experimental work presented in the current paper shows good agreement and are within 6% acceptable limits. The proposed controller is then compared with a vision-based approach and another parallel sensor-based approach for optimum operational cost and smoother trajectory. The current work is a novel approach in which the humanoid’s interaction with the mobile robot is also analyzed. The proposed approach successfully avoided the dynamic obstacle in the form of the KHEPERA-II mobile robot. This concept can find potential applications in soccer scenarios employing mobile robots as opponent players to the Nao robots. Further, because of the lower operational cost, the proposed methodology can also be applied to other areas, such as multitasking, cooperative scheduling, power distribution systems, etc.

Evaluation of a real-time simulation environment for helicopter air-to-air refuelling investigations

AbstractThe ability to perform air-to-air refuelling (AAR) can dramatically extend the utility of helicopters, through effectively providing unlimited range. For helicopters, AAR is typically performed utilising the probe-and-drogue aerial refuelling method. This is a complex manoeuver, where normally both the helicopter and tanker aircraft are operating at the limits of their flight envelopes. In addition, the wake flow from the tanker aircraft can cause a significant disturbance on the refuelling helicopter. This paper presents the initial evaluation of an AAR scenario constructed within DLR’s flight simulator, the Air Vehicle Simulator (AVES), based on current procedures and pilot interviews. A mission task was defined to assess the scenario in AVES and results are subsequently discussed. For pilots unfamiliar to formation flight or HAAR, the results show the difficulty of the flying task itself at the given cueing. Measures for improvement in future investigations are suggested.

Interoperability of classical and advanced controllers in MMC based MTDC power system

This paper presents the modular-multilevel-converter (MMC) control interoperability (IOP) and interaction within the High Voltage Direct Current (HVDC)-based power system. IOP is a crucial issue in the large-scale HVDC grid with different suppliers. To accommodate future multi-vendor HVDC grids developments, this article comprehensively investigates the MMC control IOP issue. Firstly, the most commonly adopted proportional-integral (PI) control and other non-linear controllers, e.g., model predictive control (MPC), back-stepping control (BSC), and sliding mode control (SMC), are constructed for MMC. Then, the IOP simulations are carried out in a multi-terminal direct current (MTDC) system in real-time digital simulator (RTDS) environment. The most frequent transients of the practical projects, e.g., power flow changing, wind speed changing, and DC/AC grid faults, are simulated with eight different scenarios. Each scenario presents different control capabilities in maintaining system stability, more precisely, the scenarios with non-linear controllers show faster settling time and fewer DC voltage and power variations. Controller switchings are also achieved without bringing large system oscillations. This paper provides the optimal allocation strategy of controllers to cope with system transients.

A real-time simulation environment architecture for autonomous vehicle design

Otonom sürüş için önerilen çeşitli yaklaşımlar temelde bir görüntü işleme ve bir makine öğrenmesi sürecini içermektedir. Bu süreçlerin başarıya ulaşması için uygun görüntü işleme tekniklerinin ve kapsamlı bir veri setinin kullanılması son derece önemlidir. Bununla birlikte, gerçek dünyada uygulanabilir bir model ortaya koymak adına, önerilen modelin gerçek zamanlı çalışması gerekir. Öte yandan, bir otonom araç modelinin tasarlanması, imalatı ve test süreçleri ciddi donanım maliyetleri ile sonuçlanmaktadır. Ayrıca, yeni yaklaşımların geliştirilmesi ve uygulanması için ciddi donanım değişikliklerine ihtiyaç duyulması durumunda, tasarım ve imalat süreçlerinin tekrarlanması gerekmektedir. Bu bağlamda, gerçek zamanlı bir benzetim mimarisinden faydalanmak, modelin daha az maliyetle bir ön doğrulaması için uygun bir yaklaşımdır. Bu yüzden, bu çalışmada, bir otonom sürüş modelini sınamak üzere, Unity kütüphanesi ve gerekli diğer bileşenler ile gerçek zamanlı bir benzetim ortamı mimarisi önerilmektedir. Ayrıca, şerit takip ve nesne tanıma yaklaşımlarının uygun bir bileşimin içeren bir otonom sürüş modeli tanıtılarak, önerilen benzetim mimarisinde hazırlanan bir parkur üzerinde, bir otonom araç benzetimi oluşturulmaktadır. Son olarak, literatürde yer alan bir veri seti üzerinde, evrişimsel sinir ağları tabanlı YOLO algoritması versiyonları ile önerilen benzetim mimarisinin uygulanabilirliği sınanmaktadır. Çalışmadan elde edilen bulgular göz önüne alındığında, otonom sürüş modeline sahip bir araç benzetiminin, önerilen sistem mimarisinde başarılı bir şekilde sınandığı savunulmaktadır.

Object recognition and localization enhancement in visual prostheses: a real-time mixed reality simulation

Blindness is a main threat that affects the daily life activities of any human. Visual prostheses have been introduced to provide artificial vision to the blind with the aim of allowing them to restore confidence and independence. In this article, we propose an approach that involves four image enhancement techniques to facilitate object recognition and localization for visual prostheses users. These techniques are clip art representation of the objects, edge sharpening, corner enhancement and electrode dropout handling. The proposed techniques are tested in a real-time mixed reality simulation environment that mimics vision perceived by visual prostheses users. Twelve experiments were conducted to measure the performance of the participants in object recognition and localization. The experiments involved single objects, multiple objects and navigation. To evaluate the performance of the participants in objects recognition, we measure their recognition time, recognition accuracy and confidence level. For object localization, two metrics were used to measure the performance of the participants which are the grasping attempt time and the grasping accuracy. The results demonstrate that using all enhancement techniques simultaneously gives higher accuracy, higher confidence level and less time for recognizing and grasping objects in comparison to not applying the enhancement techniques or applying pair-wise combinations of them. Visual prostheses could benefit from the proposed approach to provide users with an enhanced perception.

Data Analytics Based Power Quality Investigations in Emerging Electric Power System Using Sparse Decomposition

Modern electric grid usages extensive non-linear loads leading to the increased harmonic current injection in the system. This paper proposes a data-driven algorithm based on a sparse decomposition approach with the Overcomplete Hybrid Dictionary (OHD) and provides in-depth mathematical analysis to detect and mitigate harmonics in emerging electric power systems. The sparse decomposition method is widely used in image processing applications with significant advantages to big-data applications. However, its application is not properly addressed in electric grids’ applications despite massive data generation in a smart grid environment. Hence, in this paper, the performance evaluation of a sparse decomposition-based algorithm using a greedy approach is proposed and carried out in a real-time simulation environment for Distribution Static Compensator (DSTATCOM) application for the real-time detection, classification, and mitigation of PQ events to show its suitability and effectiveness. Finally, the experimental results on a small-scale laboratory setup are presented to validate the effectiveness of the proposed sparse-based control algorithm for DSTATCOM in real-time applications. The comparative result shows that the proposed sparse-based method is advantageous for off-line PQ signal processing and capable of real-time detection, classification, and control of the power apparatus for harmonics mitigation.

A SDTOGI based speed control method for SPMSG in WECS

Abstract The sensorless techniques are incorporated to optimize the cost and performance of the Surface Mounted Permanent Magnet Synchronous Generator (SPMSG) in the Wind Energy Conversion System (WECS) in this manuscript. Strengthen Dual third-Order Generalized Integrator (SDTOGI) with Synchronous Reference Frame-Phase Locked Loop (SRF-PLL) is applied in SPMSG to estimate the speed & position of the measured generator stator current. The proposed technique is applied in low-speed direct-driven 1.5 MW SPMSG. SDTOGI with SRF-PLL technique is compared with conventional techniques to investigate the efficacy of the proposed sensorless technique due to rapid change in the torque of the turbine. The stability of the proposed system is higher, as shown in the Nyquist plot. Further, the obtained simulation result shows that the proposed method estimates position and speed efficiently. The results are verified in the OPAL-RT 4510 real-time simulator environment to ensure the efficacy of the proposed technique.

Adaptive control-based Isolated bi-directional converter for G2V& V2G charging with integration of the renewable energy source

In this research paper, Adaptive control-based Isolated bi-directional converter for modernized electric vehicle system is introduced with control on charge and discharge of the electric vehicle (EV) battery as per the reference value. The EV battery is operated in two modes, such as charge (Grid-to-Vehicle) mode and discharge (vehicle-to-grid) mode. In charging mode, constant current and constant voltage (CCCV) control is adopted with control on charging voltage and current. Whereas in discharging mode, constant current (CC) control is adopted for control on discharge current from battery into the grid. The grid is also interconnected to PV system for renewable energy power sharing. In both the control techniques, ANFIS is integrated for better performance of the battery during charge and discharge conditions. The ANFIS takes input from error generated by comparison of reference and measured value and produces the required duty ratio value. The training of the fuzzy structure is done using data generated from the PI controller input and output. The training uses hybrid algorithm for adapting the data points considered from the PI controller. The EV battery is charged using the conventional AC grid and the renewable energy source in G2V mode, and the EV battery and renewable energy sources are used to supply power to the AC load in the V2G mode, which reducing the load demand on the AC grid. The DC-Link voltage and power to the AC load are kept constant in both modes of operation by using a synchronous reference frame controlled VSC and an ANFIS controlled dual active full bridge converter. The incremental conductance MPPT algorithm is used to control the Photo Voltaic Array (PVA). The proposed work is implemented using MATLAB/Simulink and HIL performance of the proposal system is examined in the RT-LAB OP-5700 real time simulator environment.

Event-Based Emergency Detection for Safe Drone

Quadrotor drones have rapidly gained interest recently. Numerous studies are underway for the commercial use of autonomous drones, and distribution businesses especially are taking serious reviews on drone-delivery services. However, there are still many concerns about urban drone operations. The risk of failures and accidents makes it difficult to provide drone-based services in the real world with ease. There have been many studies that introduced supplementary methods to handle drone failures and emergencies. However, we discovered the limitation of the existing methods. Most approaches were improving PID-based control algorithms, which is the dominant drone-control method. This type of low-level approach lacks situation awareness and the ability to handle unexpected situations. This study introduces an event-based control methodology that takes a high-level diagnosing approach that can implement situation awareness via a time-window. While low-level controllers are left to operate drones most of the time in normal situations, our controller operates at a higher level and detects unexpected behaviors and abnormal situations of the drone. We tested our method with real-time 3D computer simulation environments and in several cases, our method was able to detect emergencies that typical PID controllers were not able to handle. We were able to verify that our approach can provide enhanced double safety and better ensure safe drone operations. We hope our discovery can possibly contribute to the advance of real-world drone services in the near future.

Implementation of Creator-Based Virtual Simulation in News Interview

With the development of network information technology, the application of virtual simulation technology in medicine, electromechanical, military, and other fields has changed the traditional field operation mode and achieved good results, but the application of virtual simulation technology in the field of news and communication is very little. This paper takes the construction of virtual simulation news system as an example. Based on the support of 3D modeling technology of Multigen Creator, the functional requirements of virtual simulation news interview system are analyzed, the overall system objectives and architecture are set up, virtual scene database, 3D entity modeling, model optimization, and real-time rendering are established. A virtual simulation system for emergency news interviews is designed and developed, including real-time simulation environment and online operational feedback. This paper discusses the application effect of the system. By means of the questionnaire survey, SPSS23.0 is used to further analyze the feedback data of users. The data show that the expected functions of 3D modeling and real-time simulation of system modules have been realized. The research shows that virtual simulation technology can be successfully applied in the field of news and communication, and can successfully penetrate into the practical dimension of news and communication, change the existing single information interaction mode, and create a new era of real-time simulation.

Geometric Mapping Evaluation for Real-Time Local Sensor Simulation.

Medical augmented reality and simulated test environments struggle in accurately simulating local sensor measurements across large spatial domains while maintaining the proper resolution of information required and real time capability. Here, a simple method for real-time simulation of intraoperative sensors is presented to aid with medical sensor development and professional training. During a surgical intervention, the interaction between medical sensor systems and tissue leads to mechanical deformation of the tissue. Through the inclusion of detailed finite element simulations in a real-time augmented reality system the method presented will allow for more accurate simulation of intraoperative sensor measurements that are independent of the mechanical state of the tissue. This concept uses a coarse, macro-level deformation mesh to maintain both computational speed and the illusion of reality and a simple geometric point mapping method to include detailed fine mesh information. The resulting system allows for flexible simulation of different types of localized sensor measurement techniques. Preliminary simulation results are provided using a real-time capable simulation environment and prove the feasibility of the method.

Performance Comparison of PID and NARX Neural Network for Attitude Control of a Quadcopter UAV

ABSTRACT: In this study, two different types of controllers have been designed and tested for altitude and motion control of an autonomous quadrotor to compare the control performance under the influence of parametric uncertainty and disturbances. The first controller is a proportional-integral-derivative (PID) controller which is a conventional linear controller. The closed-loop PID algorithms calculate the results of the system by using the error values that consist of the difference between the sensor values measured by the closed-loop feedback method and the reference inputs. The second method that has been used is artificial neural network (ANN) algorithms, which provide both advantages and convenience in defining and controlling linear systems and non-linear systems with the closed-loop feedback method used in PID. The most important feature of the ANN algorithms is their high performance as a result of training with different input values. Therefore, the ANN control system has been trained with the input data used with Gaussian noise and the desired target data. A dynamic time series non-linear autoregressive with Exogenous input (NARX) neural network has been chosen as an ANN controller because of the time-delayed backpropagation learning performance. In this study, PID, and NARX NN control algorithms to control the maneuvers and altitude of the quadcopter and the mathematical model have been designed on Matlab Simulink. Motion control performances of the PID and NARX controllers are tested on the model. The design was tested on a real-time simulation environment with a one-millisecond fixed-step size. This paper proposes an alternative approach to control attitude and altitude on a quadcopter with the NARX NN algorithm.