Hybrid Power Grid Research Articles

Enhanced Hybrid Power Grid System Using Adaptive Fuzzy Logic Controller by Supraharmonics Reduction

Hybrid Systems meet the growing needs of electrical energy in the countries. The mismatching of hybrid systems leads to the phase shift in the three-phase signals, producing more harmonics in the band of 2 to 150kHz.However, due to various factors, harmonics have arisen from the RITHAPF and TCR which act as the phase shift controller in hybrid systems. Therefore, the Adaptive Fuzzy controller is employed with RITHAPF and TCR to maintain the phase shift and attenuate the harmonics produced. which outperforms the Hysteresis controller by 17.5% approx. in harmonic suppression and the simulation carried out for various phase angles.

Research Methods for Transient Stability Analysis of Power Systems under Large Disturbances

Transient stability analysis is critical for maintaining the reliability and security of power systems. This paper provides a comprehensive review of research methods for transient stability analysis under large disturbances, detailing the modeling concepts and implementation approaches. The research methods for large disturbance transient stability analysis are categorized into five main types: simulation methods, direct methods, data-driven methods, analytical methods, and other methods. Within the analytical method category, several common analytical strategies are introduced, including the asymptotic expansion method, intrusive approximation method, and other analytical methods. The fundamental principles, characteristics, and recent research advancements of these methods are detailed, with particular attention to their performance in various aspects such as computational efficiency, accuracy, applicability to different system models, and stability region estimation. The advantages and disadvantages of each method are compared, offering insights to support further research into transient stability analysis for hybrid power grids under large disturbances.

Machine Learning Approaches for Short-Term Photovoltaic Power Forecasting

A photovoltaic (PV) power forecasting prediction is a crucial stage to utilize the stability, quality, and management of a hybrid power grid due to its dependency on weather conditions. In this paper, a short-term PV forecasting prediction model based on actual operational data collected from the PV experimental prototype installed at the engineering college of Misan University in Iraq is designed using various machine learning techniques. The collected data are initially classified into three diverse groups of atmosphere conditions—sunny, cloudy, and rainy meteorological cases—for various seasons. The data are taken for 3 min intervals to monitor the swift variations in PV power generation caused by atmospheric changes such as cloud movement or sudden changes in sunlight intensity. Then, an artificial neural network (ANN) technique is used based on the gray wolf optimization (GWO) and genetic algorithm (GA) as learning methods to enhance the prediction of PV energy by optimizing the number of hidden layers and neurons of the ANN model. The Python approach is used to design the forecasting prediction models based on four fitness functions: R2, MAE, RMSE, and MSE. The results suggest that the ANN model based on the GA algorithm accommodates the most accurate PV generation pattern in three different climatic condition tests, outperforming the conventional ANN and GWO-ANN forecasting models, as evidenced by the highest Pearson correlation coefficient values of 0.9574, 0.9347, and 0.8965 under sunny, cloudy, and rainy conditions, respectively.

Power Flow Control Strategy of Wind Power Hybrid Power Grid Based on Digital Simulation Cloud Platform Architecture

Wind power hybrid is a comprehensive utilization method of new energy, which can greatly reduce energy pollution, but there is also the problem of tidal flow difference, so the power flow regulation of wind power energy is to be solved at present. In this paper, the digital simulation platform is used to comprehensively judge the grid-connected demand, collect data such as wind speed, power generation and energy storage, and regulate the power flow of the wind power hybrid grid in combination with the problem of wind speed randomness. Secondly, the intelligent control function is used to judge the wind turbine transmission power hybrid grid and the power flow of the distributed power grid to balance the stability of the overall power flow, voltage and current of the wind power hybrid power grid. The results show that the digital simulation cloud platform collects the power flow data of the wind power hybrid power grid, generates abnormal power flow points, and supplements the power flow through alternative methods, and its regulation and control effectiveness is greater than 90%, and the amplitude of maintaining the power flow is between 10~20%. The wind power grid's grid-connected power flow regulation time is within 10s, and there is no damage to the wind turbine and energy storage battery. Therefore, the digital simulation cloud platform can realize the power flow control of the wind power hybrid power grid, maintain its overall stability, and meet the needs of new energy grid expansion.

The Strategy of Continuous Commutation Failure Suppression by Combining Turn-off Angle Compensation and Dynamic Nonlinear VDCOL

In recent years, with the continuous growth in China’s economy, the continuous advancement of urbanization and industrialization, the contradiction between rapid economic development and the continuous reduction in traditional fossil energy reserves such as coal, oil, and natural gas, the continuous aggravation of environmental pollution has become increasingly prominent. In this era, clean energy power generation technologies such as hydropower, wind power, and solar power generation, which have the advantages of renewability, environmental protection, and economy, have developed rapidly. However, wind and photovoltaic power plants are often located in remote areas, which means significant losses in the transmission process. High-voltage direct current (HVDC) transmission technology becomes the best choice to solve this problem. The HVDC transmission system based on a grid commutator is widely used in China’s AC-DC hybrid power grid. When an AC fault occurs on the inverter side, the line-commutated converter high-voltage direct current (LCC-HVDC) system is more prone to continuous commutation failure, which brings serious harm to system operation. To better suppress the problem of continuous commutation failure on the contravariant side, this paper analyzes the mechanism of continuous commutation failure from multiple angles. The DC current command sensitivity of a voltage-dependent current order limiter (VDCOL) in the LCC-HVDC system is low, which will lead to different degrees of continuous commutation failure. In addition, the rapid rise in DC current and the drop in commutation voltage during the fault will cause the turn-off angle to drop, and the probability of continuous commutation failure of the system will increase significantly. Based on the above theoretical analysis, a new control strategy combining the dynamic compensation of the turn-off angle of a virtual inductor and the suppression of continuous commutation failure by dynamic nonlinear VDCOL is proposed. A dynamic nonlinear VDCOL control strategy is proposed for the low sensitivity of current command adjustment under conventional VDCOL control. Secondly, two concepts of virtual inductance and DC current change rate are introduced, and a control strategy based on virtual inductance is proposed to comprehensively ensure that the switching angle has sufficient commutation margin during fault recovery. Finally, based on the CIGRE standard test model in PSCAD/EMTDC, the accuracy of the correlation mechanism analysis and the effectiveness of the suppression method are verified.

Dynamic reactive power optimization strategy for AC/DC hybrid power grid considering different wind power penetration levels

Dynamic reactive power optimization strategy for AC/DC hybrid power grid considering different wind power penetration levels

First-of-Its-Kind Frequency Enhancement Methodology Based on an Optimized Combination of FLC and TFOIDFF Controllers Evaluated on EVs, SMES, and UPFC-Integrated Smart Grid

The most recent advancements in renewable energy resources, as well as their broad acceptance in power sectors, have created substantial operational, security, and management concerns. As a result of the continual decrease in power system inertia, it is critical to maintain the normal operating frequency and reduce tie-line power changes. The preceding issues sparked this research, which proposes the Fuzzy Tilted Fractional Order Integral Derivative with Fractional Filter (FTFOIDFF), a unique load frequency controller. The FTFOIDFF controller described here combines the benefits of tilt, fuzzy logic, FOPID, and fractional filter controllers. Furthermore, the prairie dog optimizer (PDO), a newly developed metaheuristic optimization approach, is shown to efficiently tune the suggested controller settings as well as the forms of the fuzzy logic membership functions in the two-area hybrid power grid investigated in this paper. When the PDO results are compared to those of the Seagull Optimization Algorithm, the Runge Kutta optimizer, and the Chaos Game Optimizer for the same hybrid power system, PDO prevails. The system model incorporates physical constraints such as communication time delays and generation rate constraints. In addition, a unified power flow controller (UPFC) is put in the tie-line, and SMES units have been planned in both regions. Furthermore, the contribution of electric vehicles (EVs) is considered in both sections. The proposed PDO-based FTFOIDFF controller outperformed many PDO-based traditional (such as proportional integral derivative (PID), proportional integral derivative acceleration (PIDA), and TFOIDFF) and intelligent (such as Fuzzy PID and Fuzzy PIDA) controllers from the literature. The suggested PDO-based FTFOIDFF controller has excellent performance due to the usage of various load patterns such as step load perturbation, multi-step load perturbation, random load perturbation, random sinusoidal load perturbation, and pulse load perturbation. Furthermore, a variety of scenarios have been implemented to demonstrate the advantageous effects that SMES, UPFC, and EV units have on the overall performance of the system. The sensitivity of a system is ascertained by modifying its parameters from their standard configurations. According to the simulation results, the suggested PDO-based FTFOIDFF controller can improve system stability despite the multiple difficult conditions indicated previously. According to the MATLAB/Simulink data, the proposed method decreased the total fitness function to 0.0875, representing a 97.35% improvement over PID, 95.84% improvement over PIDA, 92.45% improvement over TFOIDFF, 83.43% improvement over Fuzzy PID, and 37.9% improvement over Fuzzy PIDA.

A novel method of restoration path optimization for the alternating current–direct current bulk power grid after a major blackout

AbstractThe restoration control of the modern alternating current–direct current (AC–DC) hybrid power grid after a major blackout is difficult and complex. Taking into account the interaction between the line‐commutated converter high‐voltage direct current (LCC‐HVDC) and the AC power grid, this paper proposes a novel optimization method of restoration path to reconfigure the skeleton network for the blackout power grid. Based on the system strength, the supporting capability of the AC power grid for the LCC‐HVDC is first analysed from the aspects of start‐up and operation of LCC‐HVDCs. Subsequently, the quantitative relationship between the restoration path and the restoration characteristic of LCC‐HVDC is derived in detail based on the system strength indices of the short‐circuit capacity and the frequency regulation capability. Then, an optimization model of restoration path considering non‐tree paths is formulated and a feasible optimization algorithm is proposed to achieve the optimal path restoration scheme. A modified IEEE 39‐bus system and a partial power grid of Southwest China are simulated to show that the proposed method is suitable for the restoration of AC–DC power grids and can improve restoration efficiency. This research can be an important guidance for operators to rapidly restore the AC–DC power grid.

A Novel Hybrid Power-Grid Investment Optimization Model with Collaborative Consideration of Risk and Benefit

Power-grid investment (PGI) optimization is crucial for boosting investment performance, lowering investment risks, and assuring the sustainable development of power-grid businesses. However, existing studies, which primarily concentrate on financial aspects, have not adequately considered the risk and benefit factors in the process of PGI. In this context, this research suggests a novel hybrid PGI optimization model that collaboratively accounts for the risks and benefits. In the first step, risk and benefit indicator systems for PGI are built, and a comprehensive evaluation model based on the Bayesian best–worst method and TOPSIS is suggested. In the second stage, a PGI optimization model considering the investment amount, power demand, and low-carbon restrictions is further developed based on the evaluation results. Furthermore, the incomprehensible but intelligible-in-time logic algorithm is adopted to solve the problem. By conducting an empirical analysis of ten projects within a power-grid company, the optimal investment plan and a differentiated investment portfolio strategy are obtained by adjusting the key elements.

Identifying and assessing risk of cascading failure sequence in AC/DC hybrid power grid based on non-cooperative game theory

Identifying and assessing risk of cascading failure sequence in AC/DC hybrid power grid based on non-cooperative game theory

Joint Planning Method of Virtual Power Plant for Distributed Generation and Grid in AC-DC Medium and Low Voltage Distribution Network

The high proportion of virtual power plants (VPPs) used for distributed generation may cause problems such as power fluctuations and voltage distribution. In contrast, AC/DC hybrid power grid has strong transmission capacity due to its power information transmission. However, Its power grid structure and the location and capacity of VPP have an impact on the consumption capacity of the system, and the relationship between them are closely coupled. In addition, Under different operation modes, power grids of different voltage levels also have great differences. Therefore, the cooperative planning of medium and low voltage AC and DC distribution networks can improve the transmission capacity of the power grid Further improve the ability of distribution network to consume distributed power, A method is proposed in this paper about siting and capacity determination and AC-DC distribution grid frame transformation planning for medium and low voltage systems. The upper-layer model mainly focuses on AC-DC transformation scheduling in the power grid, distributed node location in the access grid and transmission line transmission capacity, while the lower-layer model effectively communicates with the low-voltage system through information flow and changes the operation of the power grid to a certain extent.The results show that the distributed generation system can reduce the operation cost and improve the overall operation efficiency of the power grid.

Utilizing controlled plug-in electric vehicles to improve hybrid power grid frequency regulation considering high renewable energy penetration

This study proposes an incorporated strategy based on energy storage systems (ESSs) like plug-in electric vehicles (PEVs) with load frequency control (LFC) to enhance the frequency stability during high penetration of renewable energy sources (RESs). Furthermore, an innovative-cascaded controller is used in the LFC loop, and PEVs are considered in the two identical areas' multi-source power grids. The proposed control structure is based on using two terms, the first term is the fractional-order-proportional-derivative (FOPD), and the second cascaded term is a fractional-order-proportional-integral (FOPI) to form the cascaded (FO-(PD-PI)) controller. Additionally, the gains of the proposed controller are well designed, utilizing an improved version of the manta ray foraging optimization algorithm (MRFO) labeled as leader MRFO (LMRFO). The effectiveness of the proposed FO-(PD-PI) controller based on the LMFRO algorithm is validated by comparing its performance with that of other control approaches such as (i.e., the proportional-integral-derivative (PID) controller, the tilt-integral-derivative (TID) controller, and the fractional-order-PID (FOPID) controller) based on different optimizers. Different load perturbation patterns, a high penetration level of RESs, and the communication delay time are broadly implemented for ensuring the superiority of the proposed controller in penalizing the power grid perturbations. Furthermore, for validating the efficiency of the proposed controller, an IEEE 39 bus is used. As a result, the proposed integrated strategy is a viable and effective control scheme for modern power grids with high-RESs penetration.

Optimal defense strategy for AC/DC hybrid power grid cascading failures based on game theory and deep reinforcement learning

This paper proposes a two-person multi-stage zero-sum game model considering the confrontation between cascading failures and control strategies in an AC/DC hybrid system to solve the blocking problem of DC systems caused by successive failures at the receiving end of an AC/DC system. A game model is established between an attacker (power grid failure) and a defender (dispatch side). From the attacker’s perspective, this study mainly investigates the problem of system line failures caused by AC or DC blockages. From the perspective of dispatch-side defense, the multiple-feed short-circuit ratio constraint method, output adjustment measures of the energy storage system, sensitivity control, and distance third-segment protection adjustment are used as strategies to reduce system losses. Using as many line return data as possible as samples, the deep Q-network (DQN), a deep reinforcement learning algorithm, is used to obtain the Nash equilibrium of the game model. The corresponding optimal dispatch and defense strategies are also obtained while obtaining the optimal sequence of tripping failures for AC/DC hybrid system cascading failures. Using the improved IEEE 39-node system as an example, the simulation results verify the appropriateness of the two-stage dynamic zero-sum game model to schedule online defense strategies and the effectiveness and superiority of the energy storage system participating in defense adjustment.

Voltage source control strategy of three-port modular multilevel converter

AC & DC hybrid power grid is an important trend of the future renewable energy based new-type power system. Power electronic transformer with multi AC and DC ports is the key device for renewable energy conversion and transmission. Global concerns are growing about the power electronic transformer and its control in the academic and industry communities. The existing topologies have disadvantages such as large volume, too many power conversion stages, difficult power balancing among submodule units, and complicated circulating control. On the other side, the lack of inertial of common power converter control strategies brings potential instability for renewable energies. TP-MMC has a compact structure and provides two independent AC ports and one DC port. It is suitable for the interconnection among AC & DC power grids. A voltage source control strategy is proposed in this paper for one of the AC ports in TP-MMC. The inertial link is added in the phase lock loop and the inner impedance is added in the dual loop control strategy. Thus, the proposed control strategy provides virtual inertial and brings self-synchronous ability. The AC port works as a voltage source with flexible virtual impedance. Active and reactive power can be controlled by frequency and voltage respectively. The proposed voltage source control strategy is validated by simulation results.

Dynamic Equivalent Software Design for AC/DC Hybrid Power System

This paper proposes a new software design method of dynamic equivalents for the AC/DC hybrid power system. First, some critical issues of dynamic equivalents for the AC/DC hybrid power grid have been intensively investigated. Then, in consideration of the function requirements, this paper builds a general framework for the dynamic equivalent software, which follows the design routine of the separateness of modules and data switching, and flexible extensibility. Finally, a new software tool for dynamic equivalents is developed with OOP technics and unified modelling, and a case has been studied to validate the performance of the newly developed software.

Relay Protection Method of High Voltage Transmission Line Based on Time-frequency Analysis

Since China entered the era of high-voltage AC and DC hybrid power grids, many high-voltage transmission lines have been successfully constructed. Due to the high voltage and long transmission distance of high-voltage transmission lines, once a fault occurs, it will cause serious losses. The research on the relay protection method of high-voltage transmission lines based on time-frequency analysis is proposed, which has important contribution value to ensure the stable development of the power grid. The fault signal of the high-voltage transmission line is extracted based on time-frequency analysis. The fault transient component of a high-voltage transmission line is detected by decomposing the fault signal characteristics. The phase correlation protection based on the fault transient component is realized to realize the relay protection of the high voltage power transmission line. The simulation results show that the accuracy of the proposed method is 100%, which verifies the reliability of this method.

A novel partitioning method for the power grid restoration considering the support of multiple LCC-HVDC systems

The restoration of the modern alternating current-direct current (AC–DC) hybrid power grid after a blackout is difficult and complex. By using the partitioning restoration strategy and the support of high voltage direct current (HVDC) system, the restoration speed of the blackout power grid can be greatly accelerated. Aiming at this problem, this paper proposes a partitioning method for the power grid restoration with multiple line commutated converter-based HVDC (LCC-HVDC) systems. Firstly, by introducing the system strength indices to quantify the interaction between AC and LCC-HVDC systems in the restoration process, a partitioning model considering multiple LCC-HVDCs is proposed. Wherein, the transmission power is optimized to make full use of LCC-HVDCs’ support capability. Then, by combining the system strength characteristic and community structure characteristic of the power grid, a partitioning method based on an improved Girvan Newman (GN) algorithm is proposed. Finally, the results are studied based on a modified IEEE 39-bus system and a realistic partial power grid of southwest China. Compared with two typical partitioning methods for the AC power grid restoration, the results show that the proposed method can effectively use the DC support power and speed up the restoration progress.

A Multipurpose Reference System Based on the Hybrid Power Grid of Cape Verde

Reference systems are key enabling platforms facilitating the evaluation and comparison of different methods and technologies prior to prototyping and field deployment. In the context of the energy transition, where the number and diversity of the grid-related research is ever expanding, we propose a reference system based on two islands of Cape Verde. These isolated power systems capture the behaviour of modern, mid & large size grids ranging from 20 to 100% renewable energy penetration, accommodating a very diverse technological mix. The topology is based on the real transmission system as of 2021, considers sector coupling and the role of power electronics-interfaced units. The Open-Access data was provided by the local system operator and the largest renewable utility of the country. The main objective is to enable off-the-shelf usage by minimizing the amount customization required for any possible study. In that way, it is suitable for a range of traditional and modern studies such as: power flow, energy management, control, stability, reliability, resiliency etc. We showcase the usefulness of this reference system with four short studies regarding grid strength, frequency stability, optimal sizing & placement of battery systems and synthetic inertia provision.

Predictive Commutation Failure Suppression Strategy for High Voltage Direct Current System Considering Harmonic Components of Commutation Voltage

The commutation failure of high voltage direct current (HVDC) systems could lead to unstable operation of the alternating current/direct current (AC/DC) hybrid power grid. The commutation voltage distortion caused by harmonics is a considerable but unclear factor of commutation failure. According to the control switching process of HVDC systems, the commutation voltage-time area method is employed to analyze and reveal the influence mechanism of harmonic components of commutation voltage on first and subsequent commutation failures. Considering the distortion characteristics of AC voltage, a predictive commutation failure suppression strategy considering multiple harmonics of commutation voltage is proposed. In this strategy, the new extinction angle and the zero-crossing offset angle after voltage distortion are calculated considering the harmonic components so as to obtain the compensation margin of the lag trigger angle by combining the correction margin with the voltage change rate. Moreover, the tuning method of parameters of extinction angle and voltage prediction variables are provided. Finally, a case study based on CIGRE standard HVDC system is performed and analyzed by using power systems computer-aided design (PSCAD) software. Compared with the International Council on Large Electric systems (CIGRE) standard test model and traditional commutation failure prevention (CFPREV) control model, the results verify that the proposed strategy can effectively reduce the risk of first and subsequent commutation failures and improve the sensitivity of CFPREV control.

Strain Analysis of High Energy Implanted 4H-SiC Epiwafer By Synchrotron X-Ray Plane Wave Topography

Silicon Carbide (SiC) is a promising wide bandgap semiconductor for power devices. Due to excellent properties of SiC, such as wide band gap, high break down voltage and thermal stability, SiC devices are able to be operated under harsh environment, such as high temperature, high voltage and high frequency environment [1]. 4H-SiC high voltage devices are highly sought for applications, such as hybrid vehicles, shipboard and power grid systems, and high-speed trains. Usually, such medium or high voltage devices are fabricated on 4H-SiC wafers with thick epilayers that will increase the resistance of the device specially at high temperatures. Deep implanted SiC superjunction devices have the potential to replace planar devices for medium voltage applications [2] However, forming deep implanted pillars into thick epilayers is quite challenging. An optimized solution of selective area doping is utilizing multi-steps high energy ion implantation system. Such a system has been developed at the Tandem Van de Graaff accelerator facility at Brookhaven National Laboratory with the capability of multi-steps high energy implantation at energies up to 150 MeV [3]. By employing such a system, medium voltage charge balance devices and 2 kV superjunction structure PIN diode have been demonstrated [4-5]. Implantation employing high energy ions can create lattice strain in the epilayer by displacing the host atoms. Therefore, characterization of strain in as-implanted epilayer is critical to understand the nature of damage introduced by the high energy implantation.Here, we employ synchrotron X-ray plane wave topography (SXPWT), where X-rays with energy of 8 keV is initially monochromatized by double crystal Si (111) monochromator followed by tuning with an asymmetric Si (331) beam conditioner. The effective width of the resultant X-ray beam is lowered to 0.5” due to the asymmetric factor of the beam conditioner [6]. Therefore, the angular resolution of SXPWT is vastly enhanced, enabling miniscule distortions in the lattice to be detected.The diffraction intensity profile from a 4H-SiC epiwafer implanted with Al ions to (concentration) using this effectively plane wave X-ray beam is shown in Fig. 1. Two high intensity peaks and weak intensity fringes in between, with an angular separation of only 2ʹʹ can be observed. This illustrates non-uniform strain in the implanted epilayer. Intensity profile of peaks and fringes is extracted from the topograph then fitted with commercial Rocking-curve Analysis by Dynamical Simulation (RADS) software developed by Bede to obtain the strain profile. The fitted curve and strain profile are shown in Fig.2. The strain profile will be analyzed and compared with doping profile obtained by Secondary Ion Mass Spectrometry (SIMS).[1] J. Guo, Y. Yang, B. Raghothamachar, T. Kim, M. Dudley, J. Kim, J. Cryst. Growth[2] L. C. Yu and K. Sheng, Solid State Electron., vol. 50, no. 6, pp. 1062-1072, 2006.[3] P. Thieberger, C. Carlson, D. Steski, R. Ghandi, A. Bolotnikov, D. Lilienfeld, P. Losee, Nucl. Instrum. Methods Phys. Res. B: Beam Interact. Mater. At.[4] R. Ghandi, C. Hitchcock, S. Kennerly, ECS Transactions 104, 67 (2021)[5] R. Ghandi, A. Bolotnikov, S. Kennerly, C. Hitchcock, P.-m. Tang, T.P. Chow, 2020 32nd International Symposium on Power Semiconductor Devices and ICs (ISPSD), IEEE, 2020, pp. 126-129.[6] H. Peng, Z. Chen, Y. Liu, B. Raghothamachar, X. Huang, L. Assoufid and M. Dudley, J. Appl. Crystallogr. (accepted) Figure 1