Multivalued Coefficient Prestorage and Block Parallel Method for Real-Time Simulation of Microgrid on FRTDS

Modelling, simulation and experimental verification for renewable agents connected to a distorted utility grid using a Real-Time Digital Simulation Platform

A control strategy has been proposed based on five terminals voltage source converter (VSC)–HVDC typical topological structure of large grid‐connected offshore wind power system, which means that VSCs on the wind farm side are controlled with AC voltage control method and VSCs on the grid side are controlled with DC voltage droop control method. A simulation model has been built on power systems computer aided design (PSCAD)/electromagnetic transients including DC (EMTDC) platform, and with it, several simulations have been conducted such as start‐stop of wind farm, power fluctuation and suspension of converter station. In the end, the control strategy is proved out to have coordination control capability and flexibility.

A conventional dynamic voltage restorer with fault current limiting capability

In this paper, a comparison of simulation between Power Systems Computer Aided Design (PSCAD) and Real Time Digital Power System Simulator (RTDS) Hardware In-the-Loop (HIL) is presented under the same conditions to express their corresponding results for other researchers reference the differences and choice the suitable testing system. Both RTDS and PSCAD are applied widely and trusted in power electronics researching field. However, RTDS provides a real time simulation process to get close to real experimental results. Further, RTDS support HIL and permit Digital Signal Processor (DSP) control inside simulation components. Therefore, the results differences produced by RTDS and PSCAD becomes one important reference for a system or algorithm. In this study, one power compensator simulation system is built in both PSCAD and RSCAD. The set-up process is introduced, and their simulation results are analyzed.

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.

Recent developments in power systems to build a smart grid depend critically on communication networks which provide unprecedented advantages for comprehensive system visibility, monitoring, protection, and control. However, it increases the system complexity and vulnerability to cyberattacks that could jeopardize the seamless system operation. The attack must be detected effectively, and then proper measures to mitigate the effect quickly to restore normality. This work implements a reduced-order <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> filter to simultaneously estimate the state variable and unknown inputs such as noise or attack signals in the automatic generation control (AGC) system. Further, the knowledge of the disturbances is utilized to mitigate the attack by appropriately compensating the sensor readings, such that the control decisions are based on the correct states, not the corrupted signals generated in the attack scenario. The stability criterion is provided based on Lyapunov functions to check the estimation error in the presence of the exogenous disturbance. Further, the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> estimator performance is evaluated by comparing it with the Kalman filter to verify its effectiveness. The estimator’s performance is validated by developing a cosimulation platform using the server–client architecture of data exchange. Further, the performance is validated in a real-time digital simulator (RTDS) platform used as the power system interacting with an estimator deployed on Raspberry Pi board sensing the attacks.

For the power system with a large number of power electronic equipment, the traditional electromagnetic transient real-time simulator is difficult to achieve small step simulation. To solve this problem, a power system transient real-time simulator is built by adopting a power system multi-rate real-time simulation method based on field programmable gate array (FPGA) and CPU. Taking the photovoltaic power generation system as an example, the system is divided into a large step part and a small step part by adopting a model partition method, and the asynchronous communication between FPGA and CPU is realized through Ethernet to form a large step-small step multi-rate co-simulation platform. For the error problem caused by the system data interaction after model partition, a PWM equivalent averaging method is proposed to equalize the output voltage at the AC side of the inverter, so as to reduce the error and compare the consumption of the equalized hardware resource. Finally, by comparing with the simulation results of the Simulink offline model, the experimental results have verified the effectiveness and accuracy of the method in real-time simulation of the power system.

The literature review explores the evolution and advancements in the implementation of latency-based solvers for real-time simulation of power electronic systems using field-programmable gate arrays (FPGAs).The journey begins with Dr. Johnson, who highlights the exceptional capability of FPGAs to outperform traditional general-purpose processors in floating-point throughput for power flow computations.[1] This foundational work sets the stage for subsequent research that delves deeper into the acceleration of various computational tasks using FPGA technology.As the field continues to mature, new methodologies and algorithms are developed to harness the full potential of FPGAs.These innovations aim to not only improve the performance of power electronic simulations, but also to enhance the flexibility and reconfigurability of the systems.Researchers are exploring novel approaches such as adaptive solvers, where the latency of the system dynamically adjusts based on the complexity of the simulation.[2] This adaptive nature allows for efficient resource allocation and utilization in real-time applications, leading to improved overall system performance.Furthermore, advancements in FPGA architecture and design techniques enable the integration of multiple solvers on a single chip, catering to the increasing demand for multi-domain simulations.This integration paves the way for seamless co-simulation of diverse power electronic systems, including converters, inverters, and motor drives.Additionally, the emergence of high-level synthesis tools simplifies the development process, making it more accessible to researchers and practitioners alike.[3] These tools enable the conversion of high-level hardware description languages into FPGA-specific designs, alleviating the need for manual low-level coding.Moreover, the availability of FPGA development boards and development kits provides a testing ground for prototype implementations, allowing researchers to evaluate their designs in a real-world scenario.[1] In conclusion, the literature review highlights the evolutionary journey of latency-based solvers for real-time power electronic simulations using FPGAs.From the initial groundbreaking work to the current state-of-the-art advancements, researchers have continuously pushed the boundaries to achieve higher performance and accuracy.With ongoing research and innovation, the field is poised for further growth and development, promising even more efficient and versatile solutions for real-time power electronic simulations.[4] [5] build on this foundation by addressing the parallelization of the sparse Matrix-Solve phase in SPICE applications.Their findings indicate that reduced-precision floating-point datapaths can significantly enhance performance, achieving speedups of 2-18 times over single-core microprocessor implementations.This article emphasizes the importance of exploiting parallelism and optimizing resource usage in FPGA designs.The authors present an FPGA-based framework that effectively tackles and addresses the inherent challenges associated with simulating intricate physical phenomena utilizing unstructured spatial discretization.This innovative and pioneering approach significantly enhances data locality and memory access patterns, thereby showcasing a remarkable and astonishing 90 times speedup as compared to high-performance microprocessors.[1] The demonstrated outcomes and results of this work serve to underscore and emphasize the critical significance of efficient and effective memory management when harnessing and leveraging the immense computational power offered by FPGAs.This research proves to be a groundbreaking and pivotal advancement in the field, with far-reaching implications and potential for further exploration and application in diverse areas of study.[6] Introduce FPGA-SPICE, which is a state-of-the-art simulation-based power estimation framework that perfectly integrates seamlessly with cutting-edge architecture exploration tools.

A new hardware platform for digital real-time simulation and control applications is introduced which is highly expandable and customizable due to its modular design and flexible, open interfaces. The system is based on digital signal processors (DSPs) and field programmable gate arrays (FPGAs). A detailed description of the processor and interface boards as core components of the system is given. A small-scale desktop system for hardware-in-the-loop real-time simulations is shown. Furthermore, modeling methodologies and commonly used integration techniques with regard to usual problems and practical implementation are presented. An actual implementation is presented as an example simulation which is used to verify the functionality and evaluate the performance of the real-time simulation platform. A real-time simulation of a buck converter with a time-step of 1 µs without FPGA co-processing is shown and the simulation results are compared to real hardware measurements. To address the common problem of inter time-step switching, solutions are discussed and two approaches are implemented and compared. In total, this paper presents a short overview of digital real-time simulation including modeling and integration, software implementation, hardware platform for code execution and hardware-in-the-loop testing.

Background/Objectives: The stability of High-Voltage Direct Current (HVDC) system is improved by optimization of system's control parameters. The simulation model of HVDC network is designed in Power Systems Computer Aided Design (PSCAD) and the Proportional Integral (PI) parameters optimization are achieved by using simplex algorithm. Simulation based evaluation of Integral Time Absolute Error-Objective function (ITAE-OF) is implemented in this paper. Methods/Statistical Analysis: Simulation calculation results are iterated to determine the new values of objective function. The model of three parallel HVDC lines connecting Power system of Central-East China is used as a test network. PI control parameters of San-Chang ±500KV HVDC system line are optimized. Findings: Optimized results have been achieved by evaluating ITAE-OF using transient simulation and converged via Simplex algorithm in PSCAD. The performance of system in steady state behavior as well as in fault condition is improved through optimized control parameters as compared to the initial control parameters, which are presented by plotting graphs. Application/Improvements: The derived equation can be further optimized using the hybrid system.

Superconducting Generator (SCG) has many advantages such as small size, high generation efficiency, low impedance, and so on. An improved power system with many potential good properties may be obtained by introduction of SCG. In order to study the behaviors of SCG in power systems, a digital type SCG model for an existing analog type real-time power system simulator is developed in this work, which is suitable for real-time simulations when the generator constants and control systems are changed frequently. By use of the above-mentioned equipments, real-time simulation in cases of SCG with different generator constants and in case of SCG in multi-machine power system has been conducted. The real-time simulation results verify the effects of SCG on power system stability enhancement and show the influence of generator constants on its stability-improving effects.

With the integration of distributed renewable energy to the distribution network and the development of multiterminal flexible DC transmission technology, multiterminal flexible DC distribution network has broad application prospects. At the same time, with the rapid development of new energy vehicles, the echelon utilization of power battery has become a research hotspot. By analyzing the characteristics of flexible DC distribution network and echelon utilization battery, the structure and control strategy of modular multilevel converter (MMC), DC solid‐state transformer, photovoltaic power generation, wind power generation, and echelon utilization battery energy storage system are established, respectively, in this paper. To achieve a DC network connection of various types of power supply and load, this paper proposes a starting method of multiterminal flexible DC distribution network and a cooperative control strategy of the wind‐solar‐storage system. A six‐terminal ring‐shape DC distribution network model is built in real‐time digital simulation (RTDS) platform. The simulation results show that the modeling methods and control strategies of each component in the real‐time simulation model meet the operation requirements of the multiterminal flexible DC distribution network, which provides a reference for the construction and research of the flexible DC distribution network.

A project titled “Establishing the advanced disaster reduction management system by fusion of real-time disaster simulation and big data assimilation,” was launched as Core Research for Evolutional Science and Technology (CREST) by the Japan Science and Technology Agency (JST). Intended to save as many lives as possible in future national crises involving earthquake and tsunami disasters, the project works on a disaster mitigation system of the big data era, based on cooperation of large-scale, high-resolution, real-time numerical simulations and assimilation of real-time observation data. The world’s most advanced specialists in disaster simulation, disaster management, mathematical science, and information science work together to create the world’s first analysis platform for real-time simulation and big data that effectively processes, analyzes, and assimilates data obtained through various observations. Based on quantitative data, the platform designs proactive measures and supports disaster operations immediately after disaster occurrence. The project was launched in 2014 and is working on the following issues at present.Sophistication and fusion of simulations and damage prediction models using observational big data: Development of a real-time simulation core system that predicts the time evolution of disaster effect by assimilating of location information, fire information, and building collapse information which are obtained from mobile terminals, satellite images, aerial images, and other new observation data in addition to sensing data obtained by the undersea high-density seismic observation network.Latent structure analysis and major disaster scenario creation based on a huge amount of simulation results: Development of an analysis and extraction method for the latent structure of a huge amount of disaster scenarios generated by simulation, and creation of severe scenarios with minimum “unexpectedness” by controlling disaster scenario explosion (an explosive increase in the number of predicted scenarios).Establishment of an earthquake and tsunami disaster mitigation big data analysis platform: Development of an earthquake and tsunami disaster mitigation big data analysis platform that realizes analyses of a huge number of disaster scenarios and increases in speed of data assimilation, and clarifies the requirements for operation of the platform as a disaster mitigation system.The project was launched in 2014 as a 5-year project. It consists of element technology development and system fusion, feasibility study as a next-generation disaster mitigation system (validation with/without introduction of the developed real-time simulation and big data analysis platform) in the affected areas of the Great East Japan Earthquake, and test operations in affected areas of the Tokyo metropolitan earthquake and the Nankai Trough earthquake.

This paper presents the implementation and experimental details of a real-time digital simulator designed for representing a Distribution Static Compensator (D-STATCOM) interfaced with a digital controller. Real-time simulation using conventional fixed time-step integration algorithms can lead to erroneous results due to the lack of synchronism between the simulator time-step and the discrete switching signals coming from the digital controller. The real-time simulation algorithm implemented in this paper overcomes the drawbacks of a fixed time-step algorithm. The real-time algorithm relies on precise registration of timing of the incoming discrete firing pulses and a subsequent correction procedure to calculate the system state. This approach has been implemented on a hybrid digital processing platform comprising of a Digital Signal Processor (DSP) and a Field Programmable Gate Array (FPGA). The platform represents both the power electronic system and the digital control system. Experimental results, for a 5 kV A D-STATCOM system, in verification of the real-time simulator results are also provided.

Presently, there are mainly two problems that prevent Electric Vehicles (EVs) from becoming popular against the Internal Combustion Engine Vehicles (ICEVs), namely: short range and too long to recharge the battery pack of the EV. Due to this, battery development is a crucial aspect to improve the performance of EVs. This progress requires dependable computer aided designs to model the characteristics of a battery accurately and reliably. This paper uses Power Systems Computer Aided Design (PSCAD) to create an equivalent runtime circuit model to observe the qualities of the Lithium Iron Phosphate battery cell under discharge at different temperatures. The model is a 3-R-C branch runtime equivalent circuit model. In order to find the fixed parameters of the circuit, MATLAB was used to implement basic current voltage characteristics. 3-D tables have been used in PSCAD to implement the State of Charge (SOC) and temperature dependent circuit parameters of the model. Once the simulations for all temperatures were completed, the average marginal error between measured and simulated terminal voltage came to be 2.1%, therefore making PSCAD an accurate simulation tool for modeling equivalent circuits of different batteries.