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Real-time simulation is a well-established approach employed across various domains, predominantly through Hardware-In-the-Loop (HIL) simulation. HIL technology enables more realistic simulations of complex systems, usually achieved by a closed-loop scheme between the hardware under test and the real-time simulator. In the field of power systems, it is also progressively deployed not only for academic aspects but also for industrial applications. A HIL model takes advantage of such merits as alleviating the risk of damage to the major real objects and reducing the cost as well as tedious efforts during the test. Besides, the evolution and increasing computing power of real-time simulators promise the capability to reach more accurate models that closely represent reality. Accordingly, this manuscript aims to investigate some applications of HIL grid-integrated technologies in transmission systems and discuss some future trends and scopes correlating to this context.

Power hardware-in-the-loop (PHIL) testing has become indispensable for the rapid, modular, and cost-saving development of automotive components. This article focuses on PHIL tests composed of entire powertrains that exchange speed and torque signals with vehicle simulations. Previous studies pointed out the importance of promptly following the references from the virtual simulation environment to replicate realistic driving conditions and introduced control strategies to cope with the challenges associated with this setup. However, a comprehensive comparison of the different control strategies has not yet been carried out. To fill this gap, the concepts are first investigated in-depth in simulations and are then, rigorously validated on a state-of-the-art powertrain test bed under highly dynamic driving scenarios, including full-braking. Furthermore, an improvement of existing shaft torque control approaches, which are mainly based on feedforward control, is proposed to better compete with the other methods. The proposed extension shows higher resilience to low accuracy of torque actuators, while the other concepts exhibit greater robustness against time delays. The results from the direct comparisons are summarized and allow the appropriate selection of control strategies for specific use cases.

Power-Hardware-in-the-Loop (PHIL) is a kind of real-time simulation, capable of exchanging not just low-voltage, low current signals, but the power required by the power device under test (PDuT). PHIL requires a PDuT to be connected to a real-time digital power network simulator via a power interface (PI). There have been quite a few PIs proposed in the past. Among them, the ideal transformer model (ITM) is the most commonly used due to its ease of implementation. Other PIs such as partial circuit duplication and damping impedance can be considered as an extended version of the ITM. These PIs need to follow a strict impedance ratio between PDuT and the rest of the system prior to the PHIL implementation, which could be a tedious and difficult task. This paper proposed a new PI for PHIL based on multi-dimensional golden section search algorithm, which can eliminate such a constraint. The proposed method has been shown to have wider stability regions when PDuT is a passive device or active one such as an inverter based resource. Moreover, dynamic responses of the proposed method are similar to those of the ITM under stable conditions. The validity of the proposed method has been justified with offline simulation and experimental PHIL setups.

While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drivers has prevented exploitation of the maximum potential of semiconductor chips from obtaining the desired device operations. Thus, a potent ongoing trend is to design a fast gate driver switching scheme to upgrade the performance of electronic equipment at the system level. To address this issue, this work proposed a novel intelligent scheme for the control of gate driver switching using the concept of quantum computation in machine learning. In particular, the quantum principle was incorporated into deep reinforcement learning (DRL) to address the hardware limitations of conventional computers and the growing amount of data sets. Taking potential benefit of the quantum theory, the DRL algorithm influenced by quantum specifications (referred to as QDRL) not only ameliorates the performance of the native algorithm on traditional computers but also enhances the progress of relevant research fields like quantum computing and machine learning. To test the practicability and usefulness of QDRL, a dc/dc parallel boost converter feeding constant power loads (CPLs) was chosen as the case study, and several power hardware-in-the-loop (PHiL) experiments and comparative analysis were performed. [ABSTRACT FROM AUTHOR]

Over the past decade, the world's electrical grid infrastructure has experienced rapid growth in the integration of grid-edge inverter-based distributed energy resources (DERs). This has led to operating concerns associated with reduced system inertia, stability and intermittent renewable power generation. However, advanced or "smart" inverters can provide grid services such as volt-VAR, frequency-Watt, and constant power factor capabilities to help sustain reliable grid and microgrid operations. To address the challenges and accelerate the benefits of smart inverter integration, new approaches are needed to test both the impacts of inverter-based resources (IBRs) on the grid as well as the impacts of changing grid conditions on the operation of IBRs. Power hardware-in-the-loop (PHIL) stands out as a strong testing solution, enabling a real-time simulated power system to be interfaced to hardware devices such as inverters which can be implemented to determine interactions between multiple inverters at multiple points of common coupling on the grid and microgrids. This paper presents a review of PHIL for grid and microgrid applications including recent advancements and requirements such as real-time simulators, hardware interfaces and communication and stability considerations. An illuminating case study is summarized followed by exemplary PHIL testbed developments around the world, concluding with a proposed research paradigm to advance the integration of smart grid-following and grid-forming inverters. [ABSTRACT FROM AUTHOR]

The application of electric motor emulators (EME) has been prosperous in recent years along with the advancement in power hardware-in-the-loop technology. However, EME design methods based on a typical modeling approach and control structure tend to be invalid in promising a clear, dynamic accuracy objective and a robust dynamic accuracy performance over wide working points, especially at high operating speed. Hence, a new EME design method based on multi-input multioutput (MIMO) modeling and a MIMO closed-loop current control (MCLCC) structure is proposed in this article. Singular values of the MIMO motor model are analyzed to clarify the influence of the rotor speed on the dynamic accuracy objective of EME for the first time, based on which an unknown input observer is designed in the MCLCC structure to compensate for disturbance voltages caused by modeling errors. The transient tracking errors of both current and torque responses can thus be remarkably reduced at 300-Hz electrical speed in the experiment even if 35% modeling errors exist, verifying the superiority of the proposed EME design method in dynamic accuracy. [ABSTRACT FROM AUTHOR]

The design of modern industrial products is further improved through the hardware-in-the-loop (HIL) simulation. Realistic simulation is enabled by the closed loop between the hardware under test (HUT) and real-time simulation. Such a system involves a field programmable gate array (FPGA) and digital signal processor (DSP). An HIL model can bypass serious damage to the real object, reduce debugging cost, and, finally, reduce the comprehensive effort during the testing. This paper provides a historical overview of HIL simulations through different engineering challenges, i.e., within automotive, power electronics systems, and different industrial drives. Various platforms, such as National Instruments, dSPACE, Typhoon HIL, or MATLAB Simulink Real-Time toolboxes and Speedgoat hardware systems, offer a powerful tool for efficient and successful investigations in different fields. Therefore, HIL simulation practice must begin already during the university's education process to prepare the students for professional engagements in the industry, which was also verified experimentally at the end of the paper. [ABSTRACT FROM AUTHOR]

While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drivers has prevented exploitation of the maximum potential of semiconductor chips from obtaining the desired device operations. Thus, a potent ongoing trend is to design a fast gate driver switching scheme to upgrade the performance of electronic equipment at the system level. To address this issue, this work proposed a novel intelligent scheme for the control of gate driver switching using the concept of quantum computation in machine learning. In particular, the quantum principle was incorporated into deep reinforcement learning (DRL) to address the hardware limitations of conventional computers and the growing amount of data sets. Taking potential benefit of the quantum theory, the DRL algorithm influenced by quantum specifications (referred to as QDRL) not only ameliorates the performance of the native algorithm on traditional computers but also enhances the progress of relevant research fields like quantum computing and machine learning. To test the practicability and usefulness of QDRL, a dc/dc parallel boost converter feeding constant power loads (CPLs) was chosen as the case study, and several power hardware-in-the-loop (PHiL) experiments and comparative analysis were performed.

Power hardware-in-the-loop (PHIL) simulation combines the advantages of digital simulation and physical experiment, which provides great convenience for research and verification of a complex electric system, such as the high-voltage direct current (HVdc) system. The digital interface algorithm realizes interconnection of the digital and physical system, but it is also the main factor to affect stability and accuracy of the PHIL results. In this article, the damping impedance interface algorithm is adopted to test the performance of a modular multilevel converter (MMC) connected into an HVdc system. Instead of online acquiring the exact MMC dc impedance, a simple RLC damping impedance is proposed to ensure stability and particularly, low-frequency accuracy for the PHIL system. Moreover, as testing in the laboratory does not allow hundreds of MVA-rated physical MMC, suitable scaling factors are proposed to design a scaled-down MMC prototype which presents identical dynamic characteristic with a full-scale MMC. A PHIL setup including RT-LAB real-time simulator, power amplifier, and a scaled-down MMC prototype is built and the experiments confirm the effectiveness of the proposed interface algorithm. [ABSTRACT FROM AUTHOR]

Over the past decade, the world’s electrical grid infrastructure has experienced rapid growth in the integration of grid-edge inverter-based distributed energy resources (DERs). This has led to operating concerns associated with reduced system inertia, stability and intermittent renewable power generation. However, advanced or “smart” inverters can provide grid services such as volt-VAR, frequency-Watt, and constant power factor capabilities to help sustain reliable grid and microgrid operations. To address the challenges and accelerate the benefits of smart inverter integration, new approaches are needed to test both the impacts of inverter-based resources (IBRs) on the grid as well as the impacts of changing grid conditions on the operation of IBRs. Power hardware-in-the-loop (PHIL) stands out as a strong testing solution, enabling a real-time simulated power system to be interfaced to hardware devices such as inverters which can be implemented to determine interactions between multiple inverters at multiple points of common coupling on the grid and microgrids. This paper presents a review of PHIL for grid and microgrid applications including recent advancements and requirements such as real-time simulators, hardware interfaces and communication and stability considerations. An illuminating case study is summarized followed by exemplary PHIL testbed developments around the world, concluding with a proposed research paradigm to advance the integration of smart grid-following and grid-forming inverters.

Nowadays, the stationary energy storage systems (ESSs) are widely introduced to recover the regenerative braking energy in urban rail systems. And the multiple ESSs along the line, substations, traction, and braking trains in the traction power system make up a multienergy coupling system, whose energy efficiency is expected to be improved. With the aim of power flow optimization, a cooperative control strategy for multiple ESSs based on multiagent deep reinforcement learning is proposed in this article. Under the distributed control structure, the decision process of multiple ESS agents is formulated as a fully cooperative Markov game, in which each ESS makes independent decision and cooperates to improve the overall energy saving effect. And the value decomposition network, which decomposes the joint state-action value into value functions across agents, is adopted to stabilize the multiagent learning process. Three train operation scenarios are presented in simulation, and the power flow distributions are analyzed quantitatively to better evaluate the performance of the proposed cooperative strategy. A power hardware-in-the-loop (PHIL) experimental platform, which integrates the RT-LAB simulator and physical supercapacitor-based energy storage system (SCESS) is developed in this article to emulate the dc traction power system with multitrain operation. Based on the PHIL platform, the proposed cooperative control strategy is implemented experimentally. Both simulation and experimental results show that in comparison with genetic algorithm (GA), the proposed strategy optimizes the energy distribution between different SCESSs and trains, and improves the overall energy saving effect of the multi-SCESSs. [ABSTRACT FROM AUTHOR]

Power hardware-in-the-loop (PHiL) simulations provide a powerful environment in the critical process of testing new components and controllers. In this work, we aim to explain the impact of time delays in a PHiL setup and recommend how to consider them in different investigations. The general concept of PHiL, with its necessary components, is explained and the benefits compared to pure simulation and implemented field tests are presented. An example for a flexible PHiL environment is shown in form of the Power Hardware-in-the-Loop Simulation Laboratory (PHiLsLab) at TU Hamburg. In the PHiLsLab, different hardware components are used as the simulator to provide a grid interface via an amplifier system, a real-time simulator by OPAL-RT, a programmable logic controller by Bachmann, and an M-DUINO microcontroller. Benefits and limitations of the different simulators are shown using case examples of conducted investigations. Essentially, all platforms prove to be appropriate and sufficiently powerful simulators, if the time constants and complexity of the investigated case fit the simulator performance. The communication interfaces used between simulator and amplifier system differ in communication speed and delay; therefore, they have to be considered to determine the level of dynamic interactions between the simulated rest of system and the hardware under test.

Power hardware-in-the-loop (PHIL) technology allows for the testing of physical equipment including power electronic converters in a simulation environment that closely mirrors the reality of the electric power grid. A challenge involved in PHIL systems is the design of the interface between the digital network model and physical equipment as this has a significant influence on stability of the real-time simulation. While a small time step supports stability and accuracy, its lower limit is given by the real-time constraint. The proposed multirate partitioning (MRP) interface addresses this issue by using a rather small time step at the hardware–software interconnection and then employing a staged adaptation of the time step within the digital model in accordance with the real-time constraint. Thus, multiple rates are used. The Nyquist stability criterion confirms enhanced stability and bandwidth by the MRP compared with single-rate (SR) counterparts. Moreover, a PHIL test of two parallel photovoltaic converters feeding a low-voltage network reveals different behaviors depending on the interface. Using the MRP, the waveforms more closely track the real-world curves of active and reactive power with the relative accuracy increasing with the speed of the transients. Informed decision making regarding the integration of renewables in the grid is so supported. [ABSTRACT FROM AUTHOR]

With increasing changes in the contemporary energy system, it becomes essential to test the autonomous control strategies for distributed energy resources in a controlled environment to investigate power grid stability. Power hardware-in-the-loop (PHIL) concept is an efficient approach for such evaluations in which a virtually simulated power grid is interfaced to a real hardware device. This strongly coupled software-hardware system introduces obstacles that need attention for smooth operation of the laboratory setup to validate robust control algorithms for decentralized grids. This paper presents a novel methodology and its implementation to develop a test-bench for a real-time PHIL simulation of a typical power distribution grid to study the dynamic behavior of the real power components in connection with the simulated grid. The application of hybrid simulation in a single software environment is realized to model the power grid which obviates the need to simulate the complete grid with a lower discretized sample-time. As an outcome, an environment is established interconnecting the virtual model to the real-world devices. The inaccuracies linked to the power components are examined at length and consequently a suitable compensation strategy is devised to improve the performance of the hardware under test (HUT). Finally, the compensation strategy is also validated through a simulation scenario.

This paper presents a converter-based permanent magnet synchronous generator (PMSG) emulator as a testbed for designing, analyzing, and testing of the generator's power electronic interface and its control system. The PMSG model is formulated in a real-time digital simulator. A voltage type ideal transformer model combined with a virtual impedance is presented as an interface algorithm. The design procedure and implementation of the virtual impedance in a simulation platform is discussed. A six-switch voltage source converter is used as a power amplifier to mimic the behavior of the PMSG supplying linear and nonlinear loads. A proportional–integral plus resonant controller is proposed as a voltage loop controller for tracking a distorted output voltage reference signal. The accuracy of the proposed emulator is investigated for the fundamental and low-order voltage harmonics. Technical challenges of the PMSG emulator are considered and proper solutions are suggested. The performance of the proposed emulator is compared with an actual PMSG. [ABSTRACT FROM AUTHOR]

Variable-speed heat pumps (VSHPs) and battery energy storage systems (BESSs) have been considered as promising energy storage resources (ESRs) that can be used for grid frequency regulation (GFR) through direct load control (DLC). In this paper, a power hardware-in-the-loop (PHIL) simulation setup has been developed to analyze the effects of real DLC-enabled VSHP and BESS units (not simulation models) on real-time GFR. Using the PHIL application, the dynamic response characteristics of the complicated hardware units have been comprehensively incorporated into the GFR analysis. In addition, a new real-time GFR scheme has been proposed to reduce the frequency deviation and the required reserve capacity of generators in a laboratory-scale islanded microgrid. In the proposed GFR method, the fast-response BESS compensates for the high-frequency components of load demand variations, while the rotary VSHP and the conventional generators are controlled to mitigate the low-frequency variations. PHIL simulation studies have been performed to compare the conventional and proposed GFR schemes under various conditions. The simulation results show that the VSHP and BESS can be effectively exploited as DLC-enabled ESRs to improve frequency stability. [ABSTRACT FROM AUTHOR]

Power system simulation is an important means to study the dynamic behavior, to ensure the safety and stability, and to optimize the operation of a power grid. Pure physical simulation and digital simulation have their own advantages and disadvantages. A three-phase four-wire hybrid simulation platform integrating the advantages of both the digital simulation and physical simulation is developed by combining the physical simulation system and real-time digital simulator. The platform is rated at 400 V and 50 kVA with the short-circuit capacity of 500 kVA and can supply ten times the rated current to support the simulation of various short-circuit faults. An improved interface algorithm based on an ideal transformer model is proposed to extend the stability region of a hybrid simulation. Hybrid simulation experiments are conducted under two cases, and the comparison with the digital simulation demonstrates the performance of this platform and the potential applied to a modern power system. This platform has been equipped in a key laboratory of smart power grid technology. [ABSTRACT FROM PUBLISHER]

The importance of Power Hardware-in-the-Loop (PHIL) experiments is rising more and more over the last decade in the field of power system and components testing. Due to the bidirectional exchange between virtual and physical systems, a true-to-reality interface is essential; however, linking several dynamic systems, stability issues can challenge the experiments, the components under test, and the individuals performing the experiments. Over the time, several interface algorithms (IA) have been developed and analyzed, each having different advantages and disadvantages in view of combining virtual simulations with physical power systems. Finally, IA are very specific to the kind of PHIL experiment. This paper investigates the operational range of several IA for specific PHIL setups by calculations, simulations, and measurements. Therefore, a selection of the mainly used respectively optimized IA is mathematically described. The operational range is verified in a PHIL system testing environment. Furthermore, in order to study the influence of different PHIL setups, according to software and hardware impedance, different tests using linear and switching amplifiers are performed. [ABSTRACT FROM AUTHOR]

This paper presents the wideband system identification (WSI) technique, i.e., an online method to identify power impedances over a wide frequency range from which the corresponding parametric impedance can be calculated online as well. The WSI technique exploits an existing custom 25-kW power electronic converter on the top of its power conversion function, which serves as power amplifier of an existing power hardware-in-the-loop (PHiL) simulation setup. The PHiL simulation technique allows connecting a real device under test (DUT) with the real-time simulated rest of system (ROS) at power level. An interface algorithm (IA) on simulation side and a power amplifier (the 25-kW power electronic converter) connect ROS and DUT. This paper shows the impact of the uncertainties in the WSI chain on the accuracy of the impedance identification and highlights how the WSI technique can be combined with the damping impedance method IA to improve both accuracy and stability of the PHiL test bench. The application of the method is illustrated for the scenario of a PHiL test of a dc microgrid with a passive load. [ABSTRACT FROM PUBLISHER]

Digital-physical hybrid real-time simulation (hybrid simulation) platform integrates the advantages of both digital simulation and physical simulation by combining the physical simulation laboratory and the real-time digital simulator. Based on a 400 V/50 kVA hybrid simulation platform with 500 kVA short-circuit capacity, the hybrid simulation methodology and a Hausdorff distance based accuracy evaluation method are proposed. The case validation of power system fault recurrence is performed through this platform, and the stability and accuracy are further validated by comparing the hybrid simulation waveform and field-recorded waveform and by evaluating the accuracy with the proposed error index. Two typical application scenarios in power systems are studied subsequently. The static var generator testing shows the hybrid simulation platform can provide system-level testing conditions for power electronics equipment conveniently. The low-voltage ride through standard testing of a photovoltaic inverter indicates that the hybrid simulation platform can be also used for voltage standard testing for various power system apparatus with low cost. With this hybrid simulation platform, the power system simulation and equipment testing can be implemented with many advantages, such as short period of modelling, flexible modification of parameter and network, low cost, and low risk. Based on this powerful tool platform, there will be more application scenarios in future power systems.

The importance of Power Hardware-in-the-Loop (PHIL) experiments is rising more and more over the last decade in the field of power system and components testing. Due to the bidirectional exchange between virtual and physical systems, a true-to-reality interface is essential; however, linking several dynamic systems, stability issues can challenge the experiments, the components under test, and the individuals performing the experiments. Over the time, several interface algorithms (IA) have been developed and analyzed, each having different advantages and disadvantages in view of combining virtual simulations with physical power systems. Finally, IA are very specific to the kind of PHIL experiment. This paper investigates the operational range of several IA for specific PHIL setups by calculations, simulations, and measurements. Therefore, a selection of the mainly used respectively optimized IA is mathematically described. The operational range is verified in a PHIL system testing environment. Furthermore, in order to study the influence of different PHIL setups, according to software and hardware impedance, different tests using linear and switching amplifiers are performed.

This paper demonstrates a novel cosimulation architecture that integrates hardware testing using power hardware-in-the-loop (PHIL) techniques with larger-scale electric grid models using off-the-shelf non-PHIL software tools. This test bed for distributed integration enables utilities to study the impacts of emerging energy technologies on their system and manufacturers to explore the interactions of new devices with existing and emerging devices on the power system, both without the need to convert existing grid models to a new platform or to conduct in-field trials. This paper describes an implementation of this architecture for testing two residential-scale advanced solar inverters at separate points of common coupling (PCCs). The same hardware setup is tested with two different distribution feeders (IEEE 123 and 8500 node test systems) modeled using GridLAB-D. In addition to simplifying testing with multiple feeders, the architecture demonstrates additional flexibility with hardware testing in one location linked via the Internet to software modeling in a remote location. In testing, the inverter current, real and reactive power, and PCC voltage are well captured by the cosimulation platform. Testing of the inverter advanced control features is currently somewhat limited by the software model time step (1 s) and tested communication latency (24 ms). These limitations could be overcome using faster modeling and communication within the same cosimulation architecture. [ABSTRACT FROM PUBLISHER]

This paper proposes a coordinated control of distributed energy storage system (ESS) with traditional voltage regulators including the on-load tap changer transformers (OLTC) and step voltage regulators (SVR) to solve the voltage rise problem caused by the high photovoltaic (PV) penetration in the low-voltage distribution network. The main objective of this coordinated control is to relieve the tap changer transformer operation stress, shave the distribution network peak load and decrease the transmission and distribution resistive power losses under high solar power penetration. The proposed control method limits the energy storage depth of discharge in order to meet a more than ten-year cycle life. A benchmark distribution network model was developed in the Real Time Digital Simulator (RTDS) and the simulation results from the studied cases verified the proposed coordinated control strategy. The experimental implementation of proposed control algorithms were developed based on a power hardware-in-the-loop (PHIL) test bed with a 22 kWh ESS, a smart meter, Labview controller, and RTDS. The experimental results were consistent with those obtained from simulation study. [ABSTRACT FROM PUBLISHER]

In this paper, a method is presented for removing the risk associated with the testing and development of novel drive system topologies, prototype electrical machines, advanced control system strategies, or a combination of the aforementioned without using any real motors/generators. The test platforms for low-power machines are relatively inexpensive and accessible; however, as power levels increase into the upper kilowatt and megawatt range, validation of prototype machines and drives becomes costly. The proposed induction machine emulator (IME) platform utilizes the power hardware-in-the-loop concept in conjunction with a high-fidelity machine model and load dynamics. The electrical machine and its load dynamics are simulated with a real-time digital simulator, which generates appropriate control commands to a power electronics-based voltage amplifier that interfaces to a variable speed drive (VSD). Specifically, the current draw is recreated by altering the phase and magnitude of a voltage amplifier connected to a VSD under test via a unique transformer-based LCL-type coupling network. Based on the proposed concept, the use of a multiwinding, tap-changing transformer establishes a truly versatile and universal test platform for a wide range of power levels. In addition, this paper presents a control strategy in the synchronously rotating reference frame in dq coordinates for the power electronic converters in IME operation. Experimental results at the 25-kVA power level validate the feasibility and highly dynamic performance of the proposed test platform. [ABSTRACT FROM AUTHOR]

We report on the application of a 5-MW variable voltage source (VVS) amplifier converter for utilization in power hardware-in-the-loop (PHIL) experiments with megawatt-scale motor drives. In particular, a commercial 2.5-MW variable speed motor drive (VSD) with active front end was connected to a virtual power system using the VVS for integrating the drive with a simulated power system. An illustrative example is given, whereby a 4-MW gas turbine generator system, including various loads, is simulated and interfaced with the VSD hardware in the lab through the VVS using current feedback to the simulation. Mechanical loading is applied to the motor via an identical 2.5-MW dynamometer connected to the same shaft. This paper first describes the PHIL facility, illustrates the challenges of powering a motor drive from a controlled voltage source converter at the multimegawatt scale, and provides experimental results from dynamic simulations. While certain challenges remain with the accuracy of the interface, it is concluded that PHIL simulations at the megawatt power level are possible and may prove useful for validating models of drive systems in the future. [ABSTRACT FROM AUTHOR]

With increasing changes in the contemporary energy system, it becomes essential to test the autonomous control strategies for distributed energy resources in a controlled environment to investigate power grid stability. Power hardware-in-the-loop (PHIL) concept is an efficient approach for such evaluations in which a virtually simulated power grid is interfaced to a real hardware device. This strongly coupled software-hardware system introduces obstacles that need attention for smooth operation of the laboratory setup to validate robust control algorithms for decentralized grids. This paper presents a novel methodology and its implementation to develop a test-bench for a real-time PHIL simulation of a typical power distribution grid to study the dynamic behavior of the real power components in connection with the simulated grid. The application of hybrid simulation in a single software environment is realized to model the power grid which obviates the need to simulate the complete grid with a lower discretized sample-time. As an outcome, an environment is established interconnecting the virtual model to the real-world devices. The inaccuracies linked to the power components are examined at length and consequently a suitable compensation strategy is devised to improve the performance of the hardware under test (HUT). Finally, the compensation strategy is also validated through a simulation scenario. [ABSTRACT FROM AUTHOR]

The Smart Grid is one of the most important solutions to boost electricity sharing from renewable energy sources. Its implementation adds new functionalities to power systems, which increases the electric grid complexity. To ensure grid stability and security, systems need flexible methods in order to be tested in a safe and economical way. A promising test technique is Power Hardware-In-the-Loop (PHIL), which combines the flexibility of Hardware-In-the-Loop (HIL) technique with power exchange. However, the acquisition of PHIL components usually represents a great expense for laboratories and, therefore, the setting up of the experiment involves making hard decisions. This paper provides a complete guideline and useful new tools for laboratories in order to set PHIL facilities up efficiently. First, a PHIL system selection guide is presented, which describes the selection process steps and the main system characteristics needed to perform a PHIL test. Furthermore, a classification proposal containing the desirable information to be obtained from a PHIL test paper for reproducibility purposes is given. Finally, this classification was used to develop a PHIL test online database, which was analysed, and the main gathered information with some use cases and conclusions are shown. [ABSTRACT FROM AUTHOR]

Digital-physical hybrid real-time simulation (hybrid simulation) platform integrates the advantages of both digital simulation and physical simulation by combining the physical simulation laboratory and the real-time digital simulator. Based on a 400 V/50 kVA hybrid simulation platform with 500 kVA short-circuit capacity, the hybrid simulation methodology and a Hausdorff distance based accuracy evaluation method are proposed. The case validation of power system fault recurrence is performed through this platform, and the stability and accuracy are further validated by comparing the hybrid simulation waveform and field-recorded waveform and by evaluating the accuracy with the proposed error index. Two typical application scenarios in power systems are studied subsequently. The static var generator testing shows the hybrid simulation platform can provide system-level testing conditions for power electronics equipment conveniently. The low-voltage ride through standard testing of a photovoltaic inverter indicates that the hybrid simulation platform can be also used for voltage standard testing for various power system apparatus with low cost. With this hybrid simulation platform, the power system simulation and equipment testing can be implemented with many advantages, such as short period of modelling, flexible modification of parameter and network, low cost, and low risk. Based on this powerful tool platform, there will be more application scenarios in future power systems. [ABSTRACT FROM AUTHOR]