Power Support Research Articles

Research on Optimal Voltage Control of Distribution Network with the Participation of EVs and PVs

With the accelerating penetration of photovoltaics (PVs) and electric vehicles (EVs), distribution networks face the risks of voltage violations and fluctuations. On the one hand, conventional voltage regulation resources like OLTC transformers and capacitor banks feature slow response and limited lifetime duration, making them incapable of quickly responding to the temporary voltage issues created by PVs and EVs. On the other hand, EVs and PVs interact with the power grid via fully controllable power electronic converters capable of real-time adjusting their operating settings, making them ideal voltage support resources. To exploit the voltage support capability of PVs and EVs, this paper proposes a two-stage control scheme for the voltage regulation of distribution networks, consisting of the day-ahead and intraday control stages. The day-ahead control mitigates potential voltage violations via day-ahead scheduling of the operation settings for OLTC transformers and capacitor banks. The intraday control further alleviates voltage deviations and voltage fluctuations based on the reactive power support of PV systems and the rational EV charging/discharging scheduling. A rolling optimization-based control technique is proposed in the intraday control stage to achieve real-time control of EVs and PVs with the stochastic nature of EV charging behaviors inherently considered. The proposed two-stage voltage regulation scheme is validated via case studies performed on the IEEE 123-node test feeder integrated with PVs and EVs.

An MPC based active and reactive power coordinated control strategy of PMSG wind turbines to enhance the support capability

As wind turbines are constantly replacing traditional units, it is becoming a consensus that wind turbines should participate in the grid support that was only responsible by traditional units in the past. In order to enhance the grid support capabilities (including active power support and reactive power support) of permanent magnet synchronous generator (PMSG) based wind turbines, this paper constructs an active and reactive power coordinated control strategy. Compared with the current active and reactive power coordinated control strategy of PMSG wind turbines, the method of the proposed one innovatively considers the climbing coordinated restriction between active and reactive power, flexible prioritization arrangement between active and reactive power, the accurate amplitude and climbing constraints of grid-side converters’ output voltage, and the model predictive control (MPC) technique. The simulation results verify that the proposed power control strategy can make PMSG wind turbines achieve excellent power output performance and thus better meet the requirements of power grid support.

Continuous Production of Monodisperse Silver Nanoparticles Suitable for Catalysis in a Droplet-Based Microreactor System

Silver nanoparticles (Ag NPs) with sizes below 50 nm have high value in catalysis, especially in electrocatalysis. However, due to the low efficiency of mass and heat transfer, conventional batch synthesis is unable to produce high-quality Ag NPs repeatedly at a large scale. To tackle this obstacle, a droplet-based microreactor system was designed in this work. Continuous and controllable synthesis of Ag NPs with sizes ranging from 7 to 30 nm, polydispersity indexes less than 10%, and high stability which could be stored at room temperature for 2.5 months were achieved by regulating residence time and introducing seed-mediated growth. Based on the Lifshitz–Slyozov–Wagner model and experimental data, growth kinetics were analyzed and revealed it as a diffusion-limited reaction, providing more powerful theoretical support for the synthesis of metal nanomaterials by the microreactor system.

Fuzzy Active Disturbance Rejection-Based Virtual Inertia Control Strategy for Wind Farms

This paper presents an advanced virtual inertia control strategy for wind farms to provide transient power support in the presence of frequency events, where a fuzzy active disturbance rejection controller is developed to enable the operation of an energy storage system (ESS) so as to provide support for frequency regulation of the power grid. To effectively estimate the system frequency under uncertain noises, fuzzy rules are presented to adaptively tune the parameters of the extended state observer and to realize the power-sharing, to improve the anti-interference ability of the wind power system. Finally, simulation analysis in MATLAB/Simulink is provided to validate the effectiveness of the proposed control strategy. Simulation results show that the developed virtual inertia control strategy based on fuzzy active disturbance rejection control has a good inertia support capability. In addition, the proposed method is able to improve the anti-noise capability of the wind power system.

Novel Harmonic Distortion Prediction Methods for Meshed Transmission Grids with Large Amount of Underground Cables

The tremendous and fast green transition in Denmark has initiated the large-scale grid-integration of renewable energy sources, electrification of energy consumption, and establishment of PtX and Energy Islands, setting goals for transmission grid development—such as the establishment of new connections—and for grid reconstruction—such as the extensive substitution of overhead lines (OHLs) with underground cables (UGCs). The share of UGCs in the Danish transmission grid is increasing. Presence of UGC has resulted in that resonances of the harmonic impedance characteristics of the transmission grid are brought within the harmonic order range coinciding with the harmonic emission sources and causing systemwide increase of the harmonic voltage distortion in the 400 kV transmission grid. The transformation of the 400 kV transmission grid has given rise to the need to predict harmonic voltage distortion using simulation models to secure an adequate power quality and support investment decisions and harmonic mitigation for the grid stage, which has not yet been established and which differs from the present grid. This paper presents the experiences of Energinet, the Transmission System Operator (TSO) in Denmark, with harmonic distortion in the Danish transmission grid due to the establishment of 400 kV UGCs, and the development of measurement-validated methods for harmonic distortion simulation and prediction. The paper also presents ongoing developments within, and research addressing, the prediction of harmonic distortion in meshed grids; for example, it explores where and how an analytical approach can replace observational studies with many numerical simulations. The methods shall make it possible to predict whether, where in the transmission grid, and for which harmonic orders connections that have not yet been commissioned may cause the violation of the planning levels, and which mitigations are necessary for bringing the harmonic distortion below the planning levels with respect to a given margin.

A Water Cycle Approach for Maximum Power Point Tracking through an Interleaved Boost Converter

In this work, an Interleaved Boost Converter (IBC) is developed for Sun Powered E-vehicles (SPEVs) to reduce input/output filters, improve dynamic characteristics, and minimize device stress compared to conventional designs. The IBC achieves these goals by utilizing current control loops and lowering the size of passive components, resulting in excellent efficiency and reduced input/output voltage variation. To ensure an uninterrupted power supply (UPS) and support vehicle movement under erratic conditions, an MPPT (Maximum Power Point Tracking) controller is essential in the PV battery system. However, under non-ideal conditions such as shading, irradiance, temperature, and inclination angle variations, PV systems may experience multiple power peaks, making it challenging to identify the global peak. To address this issue, a unique Water Cycle Optimized Perturb and Observe (WCO-PO) method is proposed in this work. The proposed technique demonstrates shorter computation time, rapid convergence rate, and minimal variations after reaching the MPP (Maximum PowerPoint) in various weather scenarios, as demonstrated using MATLAB/Simulink software. The test results are presented with a comparison of the proposed approach against other methods, showcasing the advantages of the Water Cycle approach in MPPT through an Interleaved Boost Converter.

Education for Democracy in the Social Media Century

Social media has provided challenges and opportunities for education for democracy. There have always been structural elements of communication that are hidden and perpetuate inequalities. Social media has accelerated and empowered these hidden structures through algorithms. In this argumentative essay, we examine how critical media literacy can uncover hidden power structures and support education for democracy. Critical media literacy can help students identify exclusionary, inaccurate, missing, and polarizing elements of social media while examining and discussing issues and events. Seen through this lens, social media provides opportunities for education for democracy. Critical media literacy and education for democracy provide opportunities for increasing civic engagement and renewal.

Variable weight coefficient MPC control strategy for qZSI‐VSG wind power grid‐connected system

AbstractQuasi‐Z source inverters (qZSI) can overcome the disadvantages of conventional wind power systems, because of achieving the balanced DC‐link voltage by using its boost ability. The majority of currently used control methods for conventional inverters are susceptible to parameter changes, and the qZSI are controlled by finite switching sequence model predictive control (FSS‐MPC). In this paper, a Variable weight coefficient Model Predictive Control (V‐MPC) strategy is proposed. First, based on the optimal scheduling algorithm, according to the priority of the controlled object. The proportioning weights of the global feasible solution and the local optimal solution in the algorithm are coordinated. Then, using the equality‐constraints quadratic programming method, according to the relationship between the system frequency and the reference value, increase the weight of the qZSI algorithm or increase the proportion of VSG control to improve the ability to suppress frequency fluctuations. It can give full play to the short‐term power support role of the virtual synchronous wind turbine. The modeling and testing findings validate the suggested control strategy. When compared to the conventional finite control set model predictive control (FCS‐MPC), the V‐MPC can minimize the big store inductance current ripple and have lower THD in the load currents waveform.

Response characteristics of flax retting liquid addition during chicken manure composting: Focusing on core bacteria in organic carbon mineralization and humification

To explore the applicability of flax retting liquid (FRL) addition, the physicochemical properties, microbial community structure and function, carbon conversion and humus (HS) formation were assessed during chicken manure (CM) aerobic composting. Compared with the control group, the addition of FRL increased the temperature at thermophilic phase, while the microbial mass carbon content (MBC) in SCF and FRH groups raised to 96.1 ± 0.25 g/Kg and 93.33 ± 0.27 g/Kg, respectively. Similarly, FRL also improved the concent of humic acid (HA) to 38.44 ± 0.85 g/Kg, 33.06 ± 0.8 g/Kg, respcetively. However, fulvic acid (FA) decreased to 30.02 ± 0.55 g/Kg, 31.4 ± 0.43 g/Kg, respectively and further reduced CO2 emissions. FRL influenced the relative abundance of Firmicutes at thermophilic phase and Ornithinimicrobium at maturity phase. Additionally, FRL strengthen the association among flora and reduce the number of bacteria, which was negative correlated with HA and positive with CO2 during composting. These findings offer powerful technological support for improving agricultural waste recycling.

Data-Driven Combined Central and Distributed Volt/Var Control in Active Distribution Networks

This paper proposes a two-stage combined central and distributed Volt/Var control (VVC) strategy to coordinate both utility-scale and customer-owned photovoltaics (PVs) for voltage regulation in active distribution networks (ADN). In the first stage, with day-ahead PV and load predictions, the central controller (CC) performs optimal power flow (OPF) to determine the hourly dispatch of on-load tap changers (OLTC) and capacitor banks (CBs). In the second stage, the ADN is partitioned into different zones only based on PV and load types. The zone controllers (ZC), which is formulated by deep neural networks (DNN), then communicate with their neighbors and track the optimal total reactive power support of PVs in each zone. In the offline training process, an analytical derivation to minimize power losses is also provided that can help the input and output selection of DNN. To online dispatch reactive power for individual utility-scale and customer-owned PVs in corresponding zones, a multi-mode reactive power allocation strategy is proposed. Three different modes namely loss reduction mode (LRM), fair power sharing mode (FPM) and voltage security mode (VSM) are designed to meet varying operation requirements, which can mitigate voltage violations with fair participation for customers and reduced power losses for system operators. Numerical simulations are performed on the IEEE 33-bus distribution system to demonstrate the effectiveness of the proposed method in finding a trade-off between voltage security and loss minimization with fairness.

Design of The Power Supply and Distribution Monitoring System for NNBI

The power supply and distribution system provides powerful support for the efficient operation of the negative ion source neutral beam injector (NNBI) experiment. To centrally manage the power supply equipment of each subsystem of NNBI, a power supply, and distribution monitoring system based on WinCC software and SQL Server database is developed. The system has an excellent man-machine interaction interface and realizes the monitoring and management of energy consumption in the power supply and distribution system. It has circuit process monitoring, fault alarm, operation log, historical data query, and other functions. After testing, the system can run stably and reliably control each device. At the same time, the system has good compatibility and expansibility and meets the needs of intelligent management and monitoring of the power supply and distribution system.

Integrated reactive power optimization for distribution systems considering electric vehicle dis-/charging support

Electric vehicle (EV) charging, and discharging have an important reactive power support capability for the distribution network, for which a reactive power optimization method considering EV dis-/charging is proposed. Firstly, the principle of charger’s reactive power regulation is analysed,​ and a charger state constraint model is established to satisfy the constraints on the power factor angle by modifying the charger state for the battery capacity and the target power of the users. Secondly, a quantification method for user reactive power optimization subsidies is proposed to establish network-side and user-side demand indicators respectively, and to integrate reactive power optimization target function for the distribution system. Then, bi-directional charger’s PF is taken as the optimization variable, and the charger power factor angle optimization method is proposed based on the Particle Swarm Optimization (PSO) algorithm, so as to establish a reactive power optimization model considered the orderly dis-/charging, in order to realize the active/reactive power regulation between the distribution network and Owners of the EV. Finally, simulations are carried out using the IEEE-33 model as an example. Results proved that presented orderly dis-/charging method can increase voltage profile and decrease loss rate of the network to 40%, but also significantly decrease customer’s expenditure to 13%, while satisfying the temporary travel demand of customers.

Stolen Dreams: The 1955 Cannon Street All-Stars and Little League Baseball’s Civil War by Chris Lamb

Reviewed by: Stolen Dreams: The 1955 Cannon Street All-Stars and Little League Baseball’s Civil War by Chris Lamb Robert Greene II Stolen Dreams: The 1955 Cannon Street All-Stars and Little League Baseball’s Civil War. By Chris Lamb. (Lincoln: University of Nebraska Press, 2022. Pp. xxii, 344. $34.95, ISBN 978-1-4962-1945-9.) The history of sport in American life has long been an important place to explore how race, sectionalism, and politics collide. While books such as Jules Tygiel’s Baseball’s Great Experiment: Jackie Robinson and His Legacy (New York, 1983) and Adrian Burgos Jr.’s Playing America’s Game: Baseball, Latinos, and the Color Line (Berkeley, 2007) showcase the interplay of sport, cultural, and political histories, Stolen Dreams: The 1955 Cannon Street All-Stars and Little League Baseball’s Civil War offers another excellent example of this approach. For Chris Lamb, the story of the Cannon Street All-Stars is a stand-in for the larger story of the civil rights struggle in South Carolina. Describing this story of young Black boys who were not allowed to compete in South Carolina’s Little League tournament due to Jim Crow segregation as “inextricably linked to postwar Charleston,” Lamb has written an important history of a Little League ball club and a narrative of Charleston’s long and vexed history of racism (p. 3). The civil rights movement’s history was partially shaped by Jackie Robinson’s 1947 desegregation of Major League Baseball. Whether one argues for a “long civil rights movement” thesis or posits that the civil rights movement as we know it began in the mid-1950s, it is clear that Robinson’s symbolism was a crucial marker for Black American activists and their white liberal allies. The story of the Cannon Street All-Stars, like the slow desegregation of the majors after Robinson’s arrival, illustrates the halting pace of desegregation across American society in the 1950s and 1960s. As Lamb points out, the Cannon Street All-Stars were denied the right to play against white teams in South Carolina just a year after the Brown v. Board of Education (1954) decision. In another historical irony, the team traveled to Williamsport, Pennsylvania, to accept an invitation to watch the Little League World Series—after being denied a chance to play for it—the same week that Emmett Till was murdered in Mississippi. One of the strengths of Lamb’s work is his ability to tie the earlier history of Charleston as a slave port and a flashpoint during Reconstruction to the plight of the Cannon Street All-Stars. For instance, Lamb highlights the Charleston Baseball Riot of 1869. Sparked by a confrontation on a baseball diamond between Black baseball fans and Charleston police, it became both a moment when the Reconstruction-era dreams of Black Americans were confronted with the reality of powerful support for white supremacy and an example of how much baseball was intertwined with American political struggles during the nineteenth and twentieth centuries. Lamb does an exemplary job of showing how the Cannon Street All-Stars served as a nexus of both change and continuity in South Carolina’s history of racism. For example, he reminds the reader that the white teams’ refusal to play the Cannon Street All-Stars led to the creation of Dixie Youth Baseball, a segregated youth league that “didn’t become integrated” until after its founder’s death, and that continues to play tournaments today (p. 197). He also points out that the Cannon Street All-Stars became an example of how the public [End Page 382] memory of the past is actively shaped by the public. Lamb tells the story of researcher Augustus Holt, whose investigation into why Dixie Youth players (including his son) wore Confederate flags on their uniforms in the early 1990s led to his becoming a prominent voice for greater recognition of the All-Stars in Charleston. Stolen Dreams works as a history told at the intersection of sports, civil rights, and southern memory, reminding readers of how often those fields are closely woven together. Robert Greene II Claflin University Copyright © 2023 Southern Historical Association

A novel modeling and emergency control method of transient energy of DFIG-based wind turbine under grid fault

The anti-interference ability of the power system continues to decline with the increase of wind power penetration. Due to the limitation of the reduction of the synchronous generators proportion and the response speed, the emergency power controllability of the power system with large-scale wind power is insufficient, and the stability problems of the power system continue to highlight under the grid fault. At the same time, wind turbines can hardly provide emergency support for the power system due to the maximum power point tracking mode. Therefore, the transient energy of doubly fed induction generator based wind turbine (DFWT) during the grid fault is depicted, which is accumulated by the imbalance between the input mechanical power and output electromagnetic power. And a new idea of utilizing the fault transient energy of DFWT to provide emergency power support for the power system is proposed in this paper. Firstly, the expression of stator short-circuit current of DFWT in the crowbar input and reactive power support stage is derived. The dynamic model of the rotor speed of DFWT is established further, and the calculation method of fault transient energy of DFWT is proposed. Next, in order to maximize the utilization of the transient energy, the calculation method of control duration time and control reference value is proposed, and the transient energy emergency control (TEEC) method of DFWT is proposed. The case studies and experimental results show that the TEEC method can not only provide stable power support for the power system, but also alleviate the short-term power impulse of DFWT after the grid fault removal, and accelerate the recovery of the rotor speed of DFWT, which is conducive to the safe and stable operation of DFWT and the power system.

A New Multistage Clustering Algorithm for Optimal VAr Planning For Dynamic Voltage Stability Analysis

Power systems need reactive power support to withstand voltage instability issues. The Volt Ampere reactive (VAr) resources are to be optimally determined for location and size. Generally, candidate locations are determined based on the ranking of buses according to sensitivity indices, and the Trajectory Sensitivity Index (TSI) is the most widely used sensitivity index. However, the locations identified by ranking the buses at the system level using the TSI method do not guarantee an optimal VAr solution. The recent methods based on dividing the power system into zones address the issue of optimality. The prevailing zoning methods are based on the computation of the electrical distance between buses and do not address the zoning scenario where the electrical distance between the buses is indeterminable. This paper introduces a new multistage algorithm for grouping the buses into zones even when the electrical distance is indeterminable. The new proposed strategy encompasses applying proposed analytical and parametric techniques after the standard clustering steps. A new index, namely the Bilateral Sensitivity Index (BSI), is introduced to quantify the proximity of buses. The TSI-based zonal level ranking of buses is introduced. The proposed strategy demonstrates that when TSI is employed to rank the buses at the zonal level rather than at the system level, it helps towards an optimal VAr solution. The new multistage clustering strategy is integrated into the generalized Dynamic Voltage Stability Analysis (DVSA) framework for optimal VAr determination and applied to study the voltage collapse phenomenon on a practical 24-bus system in the southern part of India. The results demonstrate the proposed approach’s efficacy in mitigating voltage instability issues through optimal VAr support.

A time‐scale adaptive a forecasting and dispatching integration strategy of the combined heat and power system considering thermal inertia

AbstractWith the integration of wind, electricity and heat, the combined heat and power system has the characteristic of multi‐time scales, in which the wind power has high uncertainty, the thermal system is difficult to synchronize with the power system for the large inertia and delay. Therefore, the fixed time‐scale dispatching is unable to guarantee the reliability of the system. Given the above problems, this paper proposes a time‐scale adaptive dispatching strategy of the combined heat and power system considering thermal inertia. This strategy analyzes the time characteristics of wind power forecasting error and the thermal inertia, while later establishing time‐scale adaptive dispatching sub‐main model of combined heat and power system. Specifically, in the time‐scale adaptive method, the system available reserve model is improved due to the power support of the thermal inertia. Based on the existing fixed time‐scale dispatching, this method dynamically adjusts the steps of forecasting and the time‐scales of dispatching when the system available reserve is inadequate to compensate for the wind power forecasting error. Taking the 4‐h fixed time‐scale dispatching as an example, the simulation results suggest that the proposed strategy achieves the dynamic dispatching of the combined heat and power system, while improving its reliability and stability.

A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management.

This study aimed to establish a risk prediction model for diabetic retinopathy (DR) in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators and to propose suggestions for chronic disease management. This multi-centered retrospective cross-sectional study was conducted among 2,385 patients with T2DM. The predictors of the training set were, respectively, screened by extreme gradient boosting (XGBoost), a random forest recursive feature elimination (RF-RFE) algorithm, a backpropagation neural network (BPNN), and a least absolute shrinkage selection operator (LASSO) model. Model I, a prediction model, was established through multivariable logistic regression analysis based on the predictors repeated ≥3 times in the four screening methods. Logistic regression Model II built on the predictive factors in the previously released DR risk study was introduced into our current study to evaluate the model's effectiveness. Nine evaluation indicators were used to compare the performance of the two prediction models, including the area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, F1 score, balanced accuracy, calibration curve, Hosmer-Lemeshow test, and Net Reclassification Index (NRI). When including predictors, such as glycosylated hemoglobin A1c, disease course, postprandial blood glucose, age, systolic blood pressure, and albumin/urine creatinine ratio, multivariable logistic regression Model I demonstrated a better prediction ability than Model II. Model I revealed the highest AUROC (0.703), accuracy (0.796), precision (0.571), recall (0.035), F1 score (0.066), Hosmer-Lemeshow test (0.887), NRI (0.004), and balanced accuracy (0.514). We have built an accurate DR risk prediction model with fewer indicators for patients with T2DM. It can be used to predict the individualized risk of DR in China effectively. In addition, the model can provide powerful auxiliary technical support for the clinical and health management of patients with diabetes comorbidities.

Adaptive power system frequency support from distributed photovoltaic systems

The integration of converter-based renewable energy resources in a power system leads to reduced inertia, creating a multitude of challenges relating to stability and reliability. On the positive side, the faster response of converter-based renewable energy resources to frequency disturbances, compared to the conventional synchronous-based generators, reduces the required minimum level of inertia in future low-inertia power systems. Accordingly, grid support from distributed photovoltaic (DPV) systems is one of the emerging solutions to overcome the challenges of these systems. This paper demonstrates how adaptive power system frequency support, which modifies the dynamic of frequency support in DPV systems according to the available level of power system inertia, improves overall system operation. In this way, for lower values of power system inertia, a higher amount of power reserve is maintained across DPV systems. Additionally, a faster frequency–Watt response is implemented to provide a larger amount of grid support under frequency disturbances. Simulation results on a composite load model of distribution feeder show that applying for adaptive frequency support from DPV systems improves the frequency nadir during under-frequency events. Experimental results show the effectiveness of the proposed approach in providing a faster dynamic response and higher amount of power support from DPV systems under low inertia conditions.

Transient voltage stability emergency control strategy for HVDC receiving end power grid based on global orthogonal collocation

When asynchronous motors, especially double-fed asynchronous motors in large capacity pump storage are the main loads in the high voltage direct current (HVDC) receiving end power grid, the increase of the equivalent slip of asynchronous motor load may cause transient voltage instability. In order to recover the voltage rapidly in the grid, the emergency reactive power support needs to be quick and accurate. A method for transient voltage stability emergency control by temporarily reducing DC current is proposed, the inverter station is used as emergency reactive power source for the HVDC receiving end power grid. In detail, firstly, aiming at the quantitative calculation of DC current, a nonlinear optimization model with the optimization variable of DC current and the objective of minimizing energy transmission reduction of HVDC is established. Further, in order to achieve fast solution and meet the accuracy requirements, global orthogonal collocation (GOC) is incorporated into the optimization model to transform the differential equations of both objective function and constraints into algebraic equations, thus the optimization is transformed into a nonlinear programming (NLP) problem, by which the emergency control strategy, in specific, the optimal DC current control scheme is obtained. Finally, the modified IEEE 14 benchmark is used to verify the effectiveness and superiority of the proposed strategy.

Fault current analysis and active current limiting strategy for hybrid cascaded LCC/MMC HVDC system

The hybrid cascaded LCC/MMC high voltage direct current (HC-HVDC) system is a prospective topology that can avoid the commutation failure problem of LCC-HVDC while ensuring bulk power transmission capability. However, the complex topology results in different DC fault characteristics at the receiving end, which brings challenges to fault detection and current limiting technology. As a result, it is of great theoretical importance to investigate the fault characteristics of the HC-HVDC system and propose the corresponding fault current limiting strategy. Firstly, this paper simplifies the equivalent discharging circuit of the hybrid cascaded LCC/MMC inverter into a first-order RL circuit by assuming the firing-advance angle is constant after fault, and proposes the fault current expressions by Laplace transform. Secondly, by changing the insertion sequence of submodules, an active fault current limiting strategy based on the submodule sorting algorithm (SMS-FCL) is proposed, which can accomplish fault current suppression, reactive power and DC voltage support, and energy loss reduction simultaneously. Moreover, the proposed SMS-FCL can cooperate with other FCLs to further suppress the fault current, and the cooperation prerequisites are analyzed. Finally, an LCC-LCC/MMC HVDC system is built in PSCAD/EMTDC to validate the accuracy of the proposed fault current expressions and the effectiveness of the current limiting strategy.