Real-time Digital Simulator Platform Research Articles

DC fault current clearance coordinated control strategy for DC grid with hybrid MMC

For DC grid based on the hybrid modular multilevel converter (MMC), the traditional DC fault current clearance scheme takes a long time and greatly affects the active power transmission. A novel DC fault current clearance coordinated control strategy is proposed, which can quickly interrupt the fault current and reduce the impact of DC fault on the DC grid and AC system. For fault-line connected MMC (FLMMC), a negative DC voltage control is employed, which can improve the current attenuation speed and ensure reliable fault isolation. For non-fault-line connected MMC (NFLMMC), the active current-limiting control (ACLC) based on the virtual reactor is adopted, which can reduce the current flow to the fault location and further shorten fault isolation time. To reduce the impact on the AC system during the DC fault, a short-time active power support control is designed. Finally, a four-terminal DC grid simulation model is built based on the RT-LAB OP5600 real-time digital simulation platform. The simulation results show that the proposed coordinated control strategy for the DC grid can quickly clear DC fault current, shorten DC fault isolation time, and strengthen active power support capability.

Error analysis and improved method of time-domain distance protection for wind power transmission lines

Time-domain distance protection has a good transient performance and operation speed when applied to wind power transmission lines. In this paper, the error analysis and improved method of phase-to-phase time-domain distance protection are investigated. Firstly, based on the time-domain mathematical model, the location error caused by fault resistance is analyzed, and then the algorithmic convergence and accuracy of conventional phase-to-phase distance relay are evaluated. To solve the computational non-convergence problem, an improved phase-to-phase distance relay is proposed, in which the instantaneous negative-sequence current is used to improve the location accuracy, especially during the fault transient stage of wind farms. In order to avoid the protection overreach problem, the threshold selection method is designed based on the maximum allowable error of the calculated distance. According to the proposed method, the corresponding protection device is developed. And the hardware-in-the-loop (HIL) test system is built based on the real-time digital simulation (RTDS) platform. Extensive experimental tests are carried out, to verify the feasibility and superiority of the proposed time-domain distance protection.

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 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.

Theoretical Development and Experimental Evaluation of a Nonlinear Observer for sensorless WECS

This research paper introduces a novel sensorless wind energy conversion system (WECS) with a Vienna rectifiers-based high-gain observer. The main emphasis is on crafting a high-gain observer capable of providing real-time estimates for challenging-to-measure signals like rotor speed and load torque. Addressing the complexities arising from system nonlinearity and high dimensionality, the paper showcases the effectiveness of the proposed observer through simulations and theoretical analysis. Furthermore, an experimental validation on the RealTime Digital Simulator (RTDS) platform validates the observer’s performance and reliability, highlighting its potential for enhancing sensorless WECS technology.

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.

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.

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.

A non-unit line protection method for MMC-HVDC grids based on the curvatures of backward traveling waves

The existing protection techniques for high-voltage direct-current (HVDC) grids suffer from several shortcomings such as high sampling frequency, poor robustness, and reliance on simulation for threshold setting. To solve these problems, this paper proposes a non-unit protection method for modular multilevel converter (MMC)-based HVDC grids using the curvatures of backward traveling waves. To this end, the propagation characteristics of traveling waves and the boundary characteristics of DC lines are first studied, then the analytical expressions of backward traveling waves are derived. Moreover, the curvatures of backward traveling waves are analyzed. On this basis, a non-unit protection method is proposed, including zone selection, disturbance identification, and pole selection. At last, with a protection platform and a real-time digital simulator (RTDS) platform of the MMC-HVDC grid, the accuracy and the robustness of the proposed protection method are verified. The results show that the protection method can correctly identify faults with different distances and resistance in 1 ms and has strong robustness against transition resistance, sampling frequency, boundary value, noise, system topology, and line parameters.

The Fault Ride-Through Characteristics of a Double-Fed Induction Generator Using a Dynamic Voltage Restorer with Superconducting Magnetic Energy Storage

With the prevalence of renewable energy sources such as wind power in the power system, analyzing the fault characteristics of systems composed of DFIGs is becoming increasingly important. Therefore, this article analyzes, at first theoretically, the fault characteristics of a doubly fed induction generator (DFIG) during fault periods. It was found that the fault current of the DFIG exhibited the frequency offset phenomenon, which is affected by the depth of voltage dips and can negatively impact traditional distance protection. Furthermore, a method using a dynamic voltage restorer (DVR) based on superconducting magnetic energy storage (SMES) was adopted to compensate for the fault voltage of DFIG, which can mitigate the voltage dips of the DFIG. This method can not only achieve the fault ride through for DFIG but also significantly improve the frequency offset of the fault current during fault periods. Finally, a model composed of a 2.5 MW DFIG-based wind turbine and a 2.5 MW DVR-based SMES was built using a real-time digital simulator (RTDS) platform, and the simulation results showed that the fault stator voltage of DFIG can be compensated at a rated value of 0.69 kV, and the frequency of fault current can be maintained at 50 Hz These results validate the excellent performance of the method in achieving the fault ride through of DFIG and improving the frequency offset of the fault current by comparing multiple type faults while employing different protection methods.

A Cooperative P2P Trading Framework: Developed and Validated Through Hardware-in-Loop

In the past five years, the importance of peer-to-peer (P2P) trading for promoting the use of renewable energy has been demonstrated in many scientific literature and pilot projects. However, a large-scale demonstration of P2P trading in today’s electricity market is yet to be implemented. The reason for this can be partially attributed to two factors. First, most existing pilot projects focus on the aspects of communications between different participants and settlements of energy trading parameters between them without giving considerable attention to the impact of such trading on the distribution network. Second, scientific studies that have rigorously investigated the impact on distribution networks mostly validated their frameworks using numerical simulations without substantiating the findings through hardware implementation. In this paper, this gap is addressed by proposing a ready-to-implement canonical coalition game-based P2P energy trading scheme for electricity customers within a local distribution network. It is shown that the proposed scheme not only guarantees stable and fair outcomes for all participants, but also satisfies all mandatory power network constraints during the trading process. Importantly, the proposed framework is implemented in an RSCAD-RTDS (real-time digital simulator) platform and the readiness of the scheme for a real-field trial is demonstrated through validation in software-in-loop and hardware-in-loop setups. The usefulness and suitability of the proposed scheme to be implemented in today’s electricity network are established via both software-in-loop and hardware-in-loop case studies.

An intelligent fault detection and classification technique based on variational mode decomposition-CNN for transmission lines installed with UPFC and wind farm

The output voltage and current signals of grid-connected doubly-fed induction generator (DFIG)-based wind turbine generators (WTGs) are significantly modulated during grid disturbances. Consequently, the performance of conventionally used distance relaying-based transmission line (TL) protection schemes are affected. The problem becomes further complicated when the interconnected TLs are compensated with unified power flow controller (UPFC). In this paper, an intelligent relaying scheme is proposed for efficient detection and classification of faults in such crucial TLs. In the proposed method, the suitable features are extracted from the locally measured current signals using variational mode decomposition (VMD). The main advantage of VMD is that it can extract the different frequency components of a faulted current signal adaptively with fast convergence. The extracted gray-scale images through VMD are utilized further by the deep convolution neural network (CNN) classifier for effective classification of faults. The efficacy of the proposed relaying algorithm is evaluated on 12000 fault and 120 non-fault cases generated on a system comprising of DFIG-wind farm and UPFC compensation using MATLAB/Simulink® and real time digital simulation platform (OP4510). The fast fault detection time (¡10 ms), high accuracies in the fault detection and classification (100% and 99.86%) justify the merits of the proposed relaying scheme.

An optimal frequency regulation in interconnected power system through differential evolution and firefly algorithm

Automatic generation control is extensively used to regulate power plants in a modern area of the power system network. In this paper, automatic generation and frequency control in interconnected power system is presented. A multisource such as thermal, hydro, and gas-based power plant is considered in this study, which is carried out by incorporating nonlinearity like generation rate constants, HVDC link, and the conventional PID controller design. Further, an optimal setting of the PID controller is performed by employing evolutionary, and metaheuristic algorithm-based approaches such as differential evolution and firefly algorithm, respectively. With these algorithms, the proposed model has been tested with their performance evaluation and comparison characteristics are discoursed. The robustness of the proposed controllers is assessed based on comparative analyses to regulate the interconnected power network’s frequency profile under different loading conditions. The stability analysis is performed using the Eigen and Nyquist plots to assess the proposed controllers’ efficacy. Besides, the frequency control study is summarized with comparative assessment through various performance indices such as settling time, peak overshoot and undershoots under different operating conditions. Finally, the proposed control scheme, in the interconnected power system, is validated through a real-time digital simulation platform, i.e., OPAL-RT 5142. The comparison of simulation and real-time results demonstrates the effectiveness of the FA-optimized PID controller in comparison with that of the DE-optimized PID controller.

Transfer learning-based fault location with small datasets in VSC-HVDC

Fault location plays a critical role in long-distance voltage source convertor based high-voltage direct current (VSC-HVDC) transmission systems. Although machine learning-based fault location methods were proved to be effective in some simulation scenarios, the small fault data sets from practical transmission lines are always a barrier for its application. Transfer learning can reach a fast convergence with a small data set when the model has learned knowledge with large data sets which have similar distributions. This paper proposed a transfer learning-based fault location method for VSC-HVDC transmission lines and discussed its performance under different conditions. The method uses stacked de-noising auto-encoder to model the relationship between current waveforms of travelling waves and fault locations, and fine-tunes the model with small data sets from the target transmission line through transfer learning. The proposed method is tested with a simulated VSC-HVDC transmission line on real time digital simulation platform. Results show the proposed method can locate faults with small training data sets and stand the influences from fault type, grounding resistance, and noise. The research results can provide technical support for the practical application of artificial intelligence in transmission grid.

An intelligent protection scheme for series-compensated transmission lines connecting large-scale wind farms

Series-compensated transmission lines (SCTLs) are increasingly preferred for transmitting bulk amounts of electricity generated from the present-day large-scale wind farm to the utility grid due to several technical and economic benefits. However, when a fault occurs in such a wind farm-integrated SCTL, the impedance across the metal oxide varistor (MOV)-protected series capacitor varies non-linearly. Also, the fault current contributed from the wind farm side is quite different compared to the grid side. Consequently, the widely used fixed impedance-based distance relaying schemes showed limitations when used for protecting such crucial TLs. In this paper, the impacts of series compensation and wind farm integration on distance relay are investigated, and this paper proposes an intelligent relaying scheme using only the current measurements. In the proposed scheme, the fault detection task is performed using the signs of the half-cycle magnitude differences of the line end positive-sequence currents, and the fault classification task is performed using only the local current measurements processed through the Fourier–Bessel series expansion (FBSE) bagging ensemble (BE) classifier. The non-stationary components present in the current signal at the initiation of a fault are captured by calculating FBSE coefficients, and the singular value decomposition is applied for dimensionality reduction of the feature set. Finally, the extracted features are used by the BE classifier for fault classification. The method is evaluated in MATLAB/Simulink® on numerous fault and non-fault data simulated in two-bus systems and also validated through the OPAL-RT (OP4510) manufactured real-time digital simulation platform. The obtained results (response time for fault detection and classification &lt;10 ms), including the comparative assessment results (fault detection accuracy =100% and fault classification accuracy =99.37%), justify the effectiveness of the proposed relaying scheme in protecting the wind farm-integrated SCTLs.

Analysis and Countermeasures of Harmonic Instability in a Practical HVDC System With Fixed Series Compensation and STATCOM

In a practical ±500 kV/3000 MW line commutated converter-based high-voltage DC (LCC-HVDC) transmission system, a sustained 5.5/105.5 Hz harmonic is observed in the inverter station bus voltage, which results in a power limit because of AC filter resistance harmonic overload protection action. To study this phenomenon and find a solution, a real-time digital and physical closed-loop simulation platform based on RTDS is established and the harmonic instability phenomenon is reproduced. Then, the harmonic instability phenomenon mechanism and impact factors are analyzed based on real-time simulation results. The simulation results show that series resonance and core saturation are the main reasons for the observed harmonic. Unstable harmonic interactions between AC and DC networks result in sustained harmonics. A temporary countermeasure of bypassing the series capacitor is proposed and verified by the field test. To solve the problem thoroughly, a supplementary harmonic damping controller (SHDC) based on a static synchronous compensator (STATCOM) is designed and verified by simulation tests

Characterizing Current THD’s Dependency on Solar Irradiance and Supraharmonics Profiling for a Grid-Tied Photovoltaic Power Plant

The rapidly increasing distributed energy resources (DERs) in power systems are now getting interconnected to set community grid structures, where power quality will be a major concern. The grid-to-grid (G2G) bidirectional power transfer among the distribution microgrid will not be considered commercially feasible unless the upstream harmonics are under the limits. The aggregation of such harmonics, measured as total harmonic distortion (THD), is feared to be beyond tolerable limits with the progression of rooftop grid-tied PV-like installations. Hence, this THD needs to be characterized with DER generation end variables. In this work, the photovoltaic (PV) DERs’ dependency on environment variables such as irradiance was profiled in the context of generating and injecting harmonics into the grid. A mathematical model of a grid-tied three-phase PV DER was developed as part of this correlation characterization, matching the fundamental unit structure of a 1.4 MW solar canopy located on the Florida International University (FIU) Miami campus. To determine the qualitative association with produced THD patterns, the model was evaluated with various irradiance settings. A real-time digital simulation (RTDS) platform was used to verify it. Following this confirmation, sets of data from power quality meters at the point of common coupling and FIU field sensors were utilized to validate further the correlation model. The results showed that the grid current’s THD exhibited a high correlation with the irradiance profile and its variation over time. The early morning and late afternoon periods of the day, associated with a low irradiance, constantly had higher harmonics generated from the PV DER. The midday THD was rather rational with partial shadings, hence a geolocation-dependent factor. These findings were verified by an RTDS and validated by real field data. In quantifying the THD injected by a single DER at a high-frequency (2–150 kHz) supraharmonics (SH) level, a 3% peak increment in magnitude was observed from the high-fixed to the low-fixed irradiance profile. The correlation characteristics depicted that the hybrid microgrid suffered from a daytime-dependent harmonic insertion from the grid-tied DER. This is a global problem unless specific measures are taken to mitigate the harmonics. The electrically notorious higher-frequency SH was found to increase proportionally. The G2G power transfer can be limited because of the higher THD in the early morning and late afternoon, which will also worsen because the numbers of grid-tied PV DERs (i.e., rooftop solar and industrial solar) are likely to increase rapidly soon. The community grid structure can thus have a controlled harmonics filtration setup purposefully designed to address the findings of this work, which also fall within the scope of our future research.

Implementation of Novel Reduced-Order H∞ Filter for Simultaneous Detection and Mitigation of FDI-Attacks in AGC Systems

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.