Flexible Grid Research Articles

Real Time Micro Gas Turbines Performance Assessment Tool: Comprehensive Transient Behavior Prediction With Computationally Effective Techniques

Abstract Conventional centralized power generation is increasingly transforming into a more distributed structure. The periodic power production that is created by the renewable production unit generates the need for small-scale heat and power units. One of the promising technologies which can assist flexible power grid is micro gas turbines (mGTs). Such engines are competent candidates for small-scale combined heat and power (CHP). mGTs, as compensators for demand fluctuations, are required to work on transient and part-load conditions, creating new research challenges. A complete characterization of their dynamic behavior through a real-time simulation tool is necessary to establish effective control systems. Moreover, the energy transition requires the conversion of conventional mGTs to more sophisticated high-efficient cycles with the addition of extra components (saturation unit, aftercooler, etc.). Consequently, a modular and computationally fast real-time tool offers an asset in the development of future cycles based on the mGT concept. This paper presents the development of a numerical in-house tool implemented in Python programing language for the performance prediction of the mGT. The fundamental target of our work is to achieve high fidelity of the simulated dynamic responses. The key benefit of this tool is the low complexity component modules. The model is validated with experimental results from the VUB T100 test rig. The code reproduces the experimental data well during steady-state and transient operations as the key cycle parameters present a deviation from the measurements within the range of 1.5%.

Convolutional neural network based on fast Fourier transform and gramian angle field for fault identification of HVDC transmission line

Flexible DC grid puts forward high-speed dynamic, and high-reliability requirements for DC transmission line protection. How to identify DC line faults ultra-fast and reliably is one of the critical technologies for the further development of the flexible DC grid. To solve this problem, a new DC transmission line fault identification scheme based on the convolutional neural network (CNN) based on fast Fourier transform (FFT) and gramian angular field (GAF) is proposed. The proposed scheme aims to further reduce the identification time of DC transmission line fault types under the requirements of rapidity and accuracy of DC transmission line protection. In this scheme, the obtained feature data are processed by FFT and GAF to obtain the feature images of different fault types corresponding to DC transmission lines. Then the CNN is used to classify the feature images to realize the fault identification of DC transmission lines. Compared with previous methods, this method can apply the mature image classification algorithm in artificial intelligence algorithm to DC transmission line fault identification and realize the rapid identification of DC transmission line fault types. The simulation results show that this method can only use the fault data within 1.5 ms after the fault to achieve 100% accuracy of fault recognition. When the fault data acquisition window is reduced to 1 ms it still has 99.88% classification accuracy, which has certain advantages in the speed and accuracy of DC transmission line fault recognition.

Research on source-load coordinated dispatching of flexible DC distribution network based on big data

In this new round of power network development, the concept of coordinated and optimized operation of power network interconnection and smart grid “source network load” has gradually attracted attention. Based on the analysis of the impact of the flexible DC distribution network on the complex energy system with multiple data sources and large data volume under the big data platform, the coordinated dispatching of the source and load of the big data flexible DC distribution network is studied. Therefore, a source-load matching index that can evaluate the impact of different types of loads on the stability of the flexible DC grid is constructed and incorporated into the load recovery optimization model. First, use the scene reduction method to process all generated scenes; next, take the reduction technology and the scene generation method into account of the uncertainty caused by the prediction error and incorporate them into the multi-objective function optimization model; finally, the membership function of fuzzy numbers is used to model uncertainty. So as to construct a load recovery model that can coordinate the load recovery amount, importance and system dynamic response. The actual meaning of the matching index is explained through model solving and actual case analysis.

A novel cycle counting perspective for energy management of grid integrated battery energy storage systems

Battery energy storage systems (BESS) are essential for flexible and reliable grid performance as the number of renewable energy sources in grids rises. The operational life of the batteries in BESS should be taken into account for maximum cost savings, despite the fact that they are beneficial for economical grid operation. In this context, this paper present a new battery cycle counting perspective for energy management of grid-connected BESS. For this purpose battery’s one full charge–discharge cycle characteristic is compared with the operating battery charge–discharge cycle every time step. This comparison was explained mathematically and graphically in detail. The results are compared with the rain flow counting method which is the most popular cycle counting algorithm. Consequently, this cycle counting approach successfully counts the battery charge/discharge cycles and it has shown that has an advantage for BESSs due to being specifically developed just for batteries.

Individual finger movement decoding using a novel ultra-high-density electroencephalography-based brain-computer interface system.

Brain-Computer Interface (BCI) technology enables users to operate external devices without physical movement. Electroencephalography (EEG) based BCI systems are being actively studied due to their high temporal resolution, convenient usage, and portability. However, fewer studies have been conducted to investigate the impact of high spatial resolution of EEG on decoding precise body motions, such as finger movements, which are essential in activities of daily living. Low spatial sensor resolution, as found in common EEG systems, can be improved by omitting the conventional standard of EEG electrode distribution (the international 10-20 system) and ordinary mounting structures (e.g., flexible caps). In this study, we used newly proposed flexible electrode grids attached directly to the scalp, which provided ultra-high-density EEG (uHD EEG). We explored the performance of the novel system by decoding individual finger movements using a total of 256 channels distributed over the contralateral sensorimotor cortex. Dense distribution and small-sized electrodes result in an inter-electrode distance of 8.6 mm (uHD EEG), while that of conventional EEG is 60 to 65 mm on average. Five healthy subjects participated in the experiment, performed single finger extensions according to a visual cue, and received avatar feedback. This study exploits mu (8-12 Hz) and beta (13-25 Hz) band power features for classification and topography plots. 3D ERD/S activation plots for each frequency band were generated using the MNI-152 template head. A linear support vector machine (SVM) was used for pairwise finger classification. The topography plots showed regular and focal post-cue activation, especially in subjects with optimal signal quality. The average classification accuracy over subjects was 64.8 (6.3)%, with the middle versus ring finger resulting in the highest average accuracy of 70.6 (9.4)%. Further studies are required using the uHD EEG system with real-time feedback and motor imagery tasks to enhance classification performance and establish the basis for BCI finger movement control of external devices.

Optimal operation strategies of pumped storage hydropower plant considering the integrated AC grids and new energy utilization

The large-scale development and utilization of new energy resource extremely promotes the construction and application of the flexible DC power grid especially in China. This paper focuses on the operation stability and new energy transmission of an actual regional power grid in North China, including new energy plants, the flexible DC power grid, a pumped storage hydropower plant (PSHP) with variable speed pumped storage unit (VSPSU) and regional AC power grids. According to the operation rules and goals, the economic operation model of the flexible DC-PSHP system is established by the mixed-integer second-order cone programming. Considering the transmission and consumption of the new energy generation, two operation strategies and three simulation scenarios are proposed. The day-ahead optimal operation schemes of PSHP in different scenarios are given by the case simulation. The results show that the proposed strategies can satisfy the operation demands of the regional power grid both in new energy generation transmission and operation economic benefits.

Research on dual-mode fault suppression strategy of AC isolation and current limiting based on hybrid MMC

Abstract The DC side fault of the high voltage DC transmission system based on modular multilevel converters high voltage DC (MMC-HVDC) is easily affected by the double influence of AC transient electrical quantity infeed and overvoltage and overcurrent, seriously threatening the safe operation of the power grid. Aiming at the problem above, a fault suppression strategy in dual mode of isolation and current limiting is proposed. Based on the half-bridge-full-bridge hybrid MMC, the fault transient mathematical model considering AC feed and sub-module switching feed is analyzed. AC isolation module with double conduction self-resistance structure and current-limiting control module is constructed, which can be adaptively adjusted to the system’s direct current parameters. The ±500 kV double-ended hybrid MMC system model is established to verify the scheme’s effectiveness. In addition, the influence of high AC modulation parameters on the suppression effect is investigated. PSCAD/EMTDC simulation results show that AC active and reactive power feed-in peaks are reduced by 388.69 MW and 119.82 Mvar, respectively, under dual-mode control. The peak value of DC overvoltage and overcurrent is reduced by 1211.53 kV and 22.5 kA, respectively, the fault self-clearing time is shortened by 43 ms, and the fault suppression effect is remarkable. In the high AC modulation ratio operating state, the modulation parameters are positively correlated with the AC power feed and negatively correlated with the overvoltage and overcurrent of the DC system. The research results provide support for the fault protection scheme of the hybrid MMC flexible and direct power grid.

ANN and SSO Algorithms for a Newly Developed Flexible Grid Trading Model

In the modern era, the trading methods and strategies used in the financial market have gradually changed from traditional on-site trading to electronic remote trading, and even online automatic trading performed by pre-programmed computer programs. This is due to the conduct of trading automatically and self-adjustment in financial markets becoming a competitive development trend in the entire financial market, with the continuous development of network and computer computing technology. Quantitative trading aims to automatically form a fixed and quantifiable operational logic from people’s investment decisions and apply it to the financial market, which has attracted the attention of the financial market. The development of self-adjustment programming algorithms for automatically trading in financial markets has transformed to being a top priority for academic research and financial practice. Thus, a new flexible grid trading model incorporating the Simplified Swarm Optimization (SSO) algorithm for optimizing parameters for various market situations as input values and the Fully Connected Neural Network (FNN) and Long Short-Term Memory (LSTM) model for training a quantitative trading model for automatically calculating and adjusting the optimal trading parameters for trading after inputting the existing market situation are developed and studied in this work. The proposed model provides a self-adjust model to reduce investors’ effort in the trading market, obtains outperformed Return of Investment (ROI) and model robustness, and can properly control the balance between risk and return.

Coordinated Optimization Scheduling of Data Center and Electricity Retailer Based on Cooperative Game Theory

As the number of internet data centers (IDC) increases, the energy consumption of modern data centers is growing rapidly, which takes an increasing part of the global electricity consumption. In implementation, to cover the electricity consumption and reduce the electricity bill, data centers are often deployed with renewable energy, energy storage system (ESS) and conventional generators, which has brought the characteristics of both flexible electricity load and micro grid to the data centers. Therefore, the data center micro grids can adjust its operations according to the real time electricity price and cut down the operational cost. However, the rising of electricity will force the data center to start up the conventional generators, which leads to the incensement of operational cost and carbon tax. In view of this, we propose a coordinated operation scheduling method of data centers and electricity retailers based on cooperative game theory. In this method, a cooperative game union comprised of the data center and the electricity retailer is established to minimize the total cost. And the extra income of the alliance is distributed using the Shapley value method. A simulation is launched on Gurobi software, and the results have illustrated that the proposed method can reduce the data center operational cost by 5%.

Simulative comparison of concepts for simultaneous control of heat flow and outlet temperature of heat exchangers for highly flexible use in the test facility “District LAB”

An important measure for decarbonising the heating sector is the transformation of existing district heating (DH) systems into low-emission heating grids based on renewable heat sources. The test facility for DH applications “District LAB (D-LAB)” is currently being set up in order to support the transition by enabling the experimental investigation of various transformation measures. It consists mainly of a Flexible Heating Grid (FHG), which connects several decentralised Hardware-in-the-Loop (HIL) and is fed by a central generation plant. The HIL units in the FHG should be able to map almost any heat producer or consumer, so that a wide range of investigation scenarios is possible. In order to fulfil this requirement, the Heat Exchanger (HEx) that connects the HIL units with the FHG must extract or feed a defined heat flow from the grid and at the same time ensure a defined secondary-side outlet temperature. In a literature research conducted to the best of our knowledge, it turned out that in all technical applications only one outlet temperature is controlled. Therefore a suitable control concept had to be developed. This has been done by extensive simulative investigations, which are presented in this paper. Two control concepts, (I) “decoupled PID controller”, (II) “Characteristic Field (CF)-Based Control”, were self-developed and compared with each other. In order to represent a large spectrum of possible operating conditions with regard to the transformation of DH systems, 48 investigation scenarios based on target value steps were defined and used for the comparison. Subsequently, the average performance using the Root Mean Square Error (RMSE) as well as the time dependant step responses were examined. It turned out that, the CF-based concept appears to be more suitable for use in the D-LAB. It is conceivable that these results can also be transferred to other test facilities in which both, the heat flow and one outlet temperature need to be controlled.

DC fault current-limiting method based on dual-loop active control for modular multilevel converters

PurposeIn the event of a DC short-circuit fault in a flexible DC power grid, the high peak value of the fault current puts forward more stringent requirements on the DC circuit breaker. The existing fault current cutoff mainly focuses on changing the topology structure. To suppress the development of fault current and reduce the investment cost of the DC grid, this paper aims to propose a dual-loop active current-limiting control based on energy difference.Design/methodology/approachFirstly, the equivalent circuit at fault is established, and the parameters related to the fault current are analyzed. Then, the relationship between the output voltage change of the bridge arm and the difference between the AC and DC energy is deduced. Finally, the experimental results are discussed on the real-time simulation platform Opal-RT.FindingsThe proposed current-limiting measures can greatly reduce the fault current, reduce the breaking current of the circuit breaker and increase the capacitor voltage during the fault period, which is beneficial to the stability of the AC system. It is verified that the proposed method is also applicable to a certain high-resistance fault.Originality/valueThis paper applies the method of AC fault to DC fault and deduces the relationship between energy difference and voltage variation corresponding to different step lengths based on digital simulation. In addition, two variables are used as control structure parameters to reduce the probability of system misoperation.

Self‐Encapsulated Cu Grid for Highly Transparent Conductive Electrode for Transparent Heater and Electrochemical Supercapacitor Applications

AbstractThe conducting metallic grid is a prominent viable candidate for an alternative to indium tin oxide for optoelectronic devices. This metallic grid tends to oxidize quickly, and to avoid oxidization, a passivation layer must be added, which drastically compromises the transmittance. The fabrication of a highly flexible, highly transparent, and conductive copper grid electrode with an outstanding sheet resistance of 0.11 Ω □−1, and excellent transparency of 93.13% is reported. This copper electrode resists oxidization with the help of poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), and even after exposing the electrode to the ambient atmosphere, it shows excellent sheet resistance of 0.12 Ω □−1. This is achieved by the in situ formation of an oxidization‐resistive light‐absorbing PEDOT:PSS layer that encapsulates the Cu microparticles during electrodeposition. The electrode shows excellent mechanical stability with good electromagnetic interference shielding of 19 dB. Moreover, the electrode is developed as a thin film heater, and subjects to electrochemical analysis, which shows a specific capacitance of 81.58 mF cm−2 for supercapacitor application.

Calculation method of short-circuit fault current in flexible DC grid

The flexible DC grid has the capability to transport and distribute electric energy in multiterminal power system, and avoid the adverse impact on AC power grid in reactive power consumption and current harmonic. Unfortunately, because of the discharge of submodule capacitor facing the short-circuit fault of the overhead line, The overcurrent problem caused by the fault restricts the further development of the DC grid. At present, the research on short-circuit fault of flexible DC grid is mainly based on computer software simulation without mathematical expression to describe failure process quantitatively. This paper proposes a short-circuit fault current calculation method describing flexible DC grid fault process. Firstly, the linearized equivalent model of the MMC converter station is obtained by considering the discharge characteristics of the submodule capacitors. Secondly, considering the DC grid space topology, the parsed expression of overcurrent in short circuit fault is derived. Finally, the analysis results of the paper are compared with the software simulation results of the PSCAD/EMTDC platform to verify the validity and accuracy of the overcurrent algorithm.

Partial Discharge Behavior of Typical Defects in Power Equipment Under Multilevel Staircase Voltage

With the widespread application of power electronic switching technology, power equipment is facing new electrical stresses brought about by multilevel staircase voltages during testing and operation. Therefore, the partial discharge (PD) behavior of five typical defects in power equipment under the staircase waveform needs to be investigated. This article mainly analyses the phase-resolved PD (PRPD) pattern and pulse repetition rate (PRR) of five typical defects under sinusoidal voltage and multilevel staircase voltage with different number of levels. Also, the PD behavior under staircase voltage with different step responses are investigated. By analyzing the reasons behind the PD behavior between different cases, the PD characteristics and the transformation of PRPD patterns under different staircase voltages are obtained. Moreover, this research finds that the sensitivity of different defects to the staircase voltage is different. These results provide experimental and theoretical support for the testing and diagnosis of PD under new electrical stress present in the future flexible electric grid.

Mechanisms Regulating Energy Homeostasis in Plant Cells and Their Potential to Inspire Electrical Microgrids Models.

In this paper, the main features of systems that are required to flexibly modulate energy states of plant cells in response to environmental fluctuations are surveyed and summarized. Plant cells possess multiple sources (chloroplasts and mitochondria) to produce energy that is consumed to drive many processes, as well as mechanisms that adequately provide energy to the processes with high priority depending on the conditions. Such energy-providing systems are tightly linked to sensors that monitor the status of the environment and inside the cell. In addition, plants possess the ability to efficiently store and transport energy both at the cell level and at a higher level. Furthermore, these systems can finely tune the various mechanisms of energy homeostasis in plant cells in response to the changes in environment, also assuring the plant survival under adverse environmental conditions. Electrical power systems are prone to the effects of environmental changes as well; furthermore, they are required to be increasingly resilient to the threats of extreme natural events caused, for example, by climate changes, outages, and/or external deliberate attacks. Starting from this consideration, similarities between energy-related processes in plant cells and electrical power grids are identified, and the potential of mechanisms regulating energy homeostasis in plant cells to inspire the definition of new models of flexible and resilient electrical power grids, particularly microgrids, is delineated. The main contribution of this review is surveying energy regulatory mechanisms in detail as a reference and helping readers to find useful information for their work in this research field.

Measurement of Power Grid Resilience Based on a Dynamic Inoperability Input–Output Model

The increase in global natural disasters, emergencies, and terrorist attacks brings great challenges to the flexible operation of power grids. The research on the flexibility of power grids becomes more and more important. At the same time, the rapid development of renewable energy and smart grids also provides new opportunities for research of flexible power grids. Based on the dynamic inoperability input–output model (DIIM), this study creatively uses the node transmission power to represent the relationship between nodes in the power grid and then studies the resilience measurement of the power grid. First, the significance of studying power grid resilience is discussed, and the absorption and recovery capacity of power grid resilience is described. Second, the power grid resilience measurement model based on the DIIM is established, and a theoretical analysis is carried out. Using the characteristics of inoperability, the power grid resilience is measured from the time aspect, and the characteristics of the model are analyzed at the same time. On the basis of theoretical analysis, this study also provides a control strategy to improve the grid resilience, which has good convenience and applicability. Finally, the theoretical analysis method is applied to a power grid example, and the correctness and effectiveness are verified. The measurement model can intuitively display the resilience characteristics of power grids and provide theoretical support for management and emergency response.

Analysis and Prospect of the Application of Wireless Sensor Networks in Ubiquitous Power Internet of Things.

With the rapid development of the economy and society, the low efficiency and high loss of the traditional power grid can no longer meet the growing social demand, and the power grid market is facing a reform. Smart grid, as a next-generation power system, it can effectively improve the performance of traditional power grids. The ubiquitous power Internet of Things (UPIOT) replaces the traditional grids with efficient, safe, reliable, and flexible new grids, improves the utilization efficiency of the grid, reduces the loss of the power grid in the transmission process, and can meet the needs of different types of markets and users. As an advanced information acquisition and processing technology, wireless sensor networks have been widely used in medical, industrial, agricultural, commercial, and public management fields. It is an important means to promote future economic development and build a harmonious society. In the power system, wireless sensor network technology can be widely used in many fields such as line fault location, real-time monitoring, smart meter reading, and relay protection. In this paper, the basic concepts and overall architecture of ubiquitous power Internet of Things are summarized. Then, we summarize the research status of the wireless sensor network in smart grid, including power equipment, line monitoring, smart grid wireless automatic meter reading, distribution network relay protection, power assets life-cycle management, power grid fault location, and power grid fault diagnosis. In view of the technical characteristics of wireless sensor networks, combined with the production links of power systems, the application framework of wireless sensor network technology in the power systems is constructed. The application of wireless sensor networks is prospected from the aspects of network development of relay protection, application research of smart substation, application research of power grid catastrophe, security protection of power system, and deep-seated ubiquitous power Internet of Things.

Scanning Inductive Thermographic Surface Defect Inspection of Long Flat or Curved Work-Pieces Using Rectification Targets

Inductive thermography is an NDT method, which can be excellently used to inspect long metallic specimens (such as railway tracks) to detect surface defects. Aiming at the inspection of railway tracks in service with a movable setup, the method had to be advanced from a stationary application to a scanning setup. This work presents methods for using calibration targets for rectification, in order to improve the quality of the resulting images. Two scanning techniques are presented for detecting different types of rolling contact fatigue (RCF) defects on rail pieces. In the case of the first method, separate stationary inductive pulsed measurements are carried out for the segments of a long sample and the results are stitched together to one panoramic image of the whole specimen (“stop-and-go”). Since the surface of the rail piece is curved, rectification of the surface with a flexible grid is necessary to generate seamless panoramic images. In the case of the second method, a specimen is moved with constant speed underneath the induction coil. For the detection of shallow surface cracks, the infrared camera has to have a view of the surface during the heating; therefore, the camera is placed behind the coil but tilted towards a position below the induction coil. In order to be able to evaluate phase images from the temporal temperature change, a checkerboard grid as a rectification target is used. It is also analyzed how the chosen IR camera frame rate and the motion speed affect the scanning result.

ICARUS, a new inner heliospheric model with a flexible grid

Context. Simulating the propagation and predicting the arrival time of coronal mass ejections (CMEs) in the inner heliosphere with a full three-dimensional (3D) magnetohydrodynamic (MHD) propagation model requires a significant amount of computational time. For CME forecasting purposes, multiple runs may be required for different reasons such as ensemble modeling (uncertainty on input parameters) and error propagation. Moreover, higher resolution runs may be necessary, which also requires more CPU time, for example for the prediction of solar energetic particle acceleration and transport or in the framework of more in-depth studies about CME erosion and/or deformation during its evolution. Aims. In this paper we present ICARUS, a new inner heliospheric model for the simulation of a steady background solar wind and the propagation and evolution of superposed CMEs. This novel model has been implemented within the MPI-AMRVAC framework which enables the use of stretched grids and solution adaptive mesh refinement (AMR). The usefulness and efficiency (speed-up) of these advanced features are explored. In particular, we model a typical solar wind with ICARUS and then launch a simple cone CME and follow its evolution. We focus on the effect of radial grid stretching and two specific methods or criteria to trigger solution AMR on this typical simulation run. Methods. For the solar background wind simulation run, we limited the mesh refinement to the area(s) of interest, in this case a co-rotating interaction region (CIR). For the CME evolution run, on the other hand, we apply AMR where the CME is located by the use of a tracing function. As such, the grid is coarsened again after the CME has passed. Results. The implemented AMR is flexible and only refines the mesh in a particular sector of the computational domain, for example around the Earth or a single CIR, and/or for a particular feature such as CIR or CME shocks. Radial grid stretching alone yields speed-ups of up to 4 and more, depending on the resolution. Combined with solution adaptive mesh refinement, the speed-ups can be much larger depending on the complexity of the simulation (e.g., number of CIRs in the background wind, number of CMEs) and on the chosen AMR criteria, thresholds and the number of refinement levels. Conclusions. The ICARUS model implemented in the MPI-AMRVAC framework is a new inner heliospheric 3D MHD model that uses grid stretching as well as AMR techniques. The flexibility in the grid and its resolution allows an optimization of the computational time required for CME propagation simulations for both scientific and forecasting purposes.

SiC Mass Commercialization: Present Status and Barriers to Overcome

In an increasingly electrified technology driven world, power electronics is central to the entire clean energy manufacturing economy. Silicon (Si) power devices have dominated power electronics due to their low cost volume production, excellent starting material quality, ease of fabrication, and proven reliability. Although Si power devices continue to improve, they are approaching their operational limits primarily due to their relatively low bandgap, critical electric field, and thermal conductivity that result in high conduction and switching losses, and poor high temperature performance. Silicon Carbide’s (SiC) compelling efficiency and system benefits have led to significant development efforts over the last two decades and today planar and trench MOSFETs, and JFETs are commercially available from several vendors as discrete components or in high power modules in the of 650 V to 1700 V voltage range. High impact application opportunities, where SiC devices are displacing their incumbent Si counterparts, have emerged and include automotive and rail power electronics with reduced losses and reduced cooling requirements; novel data center topologies with reduced cooling loads and higher efficiencies; variable frequency drives for efficient high power electric motors at reduced overall system cost; more efficient, flexible, and reliable grid applications with reduced system footprint; and “more electric aerospace” with weight, volume, and cooling system reductions contributing to energy savings. In particular, SiC insertion in electric vehicles brings major competitive advantages and is a volume application opportunity that can spur manufacturing economies of scale and lower system costs. As SiC continues to grow, the industry is lifting the last barriers to mass commercialization that include higher than Si device cost, relative lack of wafer planarity, the presence of basal plane dislocations, reliability and ruggedness concerns, and the need for a workforce skilled in SiC power technology to keep up with the rising demand. It should be noted that in many applications, insertion of SiC reduces overall system cost compared to Si even though SiC devices can cost 2-3 more than their Si counterparts. This is due to the passive component and cooling system simplifications enabled by the efficient high frequency SiC operation. In this paper, we will review key aspects of SiC technology and discuss overcoming barriers to mass commercialization.