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Overview: This article explores various AC-DC topologies, control strategies, and technical specifications crucial for enhancing efficiency and performance in chargers. It also addresses current challenges and advancements in the field. To achieve a significant reduction in the volume and weight of electric vehicles, off-board chargers must be used for both fast and ultra-fast DC charging. The topologies and control strategies of AC-DC for off-board chargers as shown in Fig. 1 are covered in this article, focusing on technical specifications, current developments, and challenges. Fig. 1: Circuit topology of AC-DC power stage (a-f) Source: IEEE Access The topologies shown here work well with fast DC charging. The rated power of the rectifiers can be increased to satisfy the demand for fast DC charging with an adaptable and appropriate design. Three-Phase Buck-Type RectifierFor an AC-DC rectifier in an electric vehicle charging station, there are critical requirements, such asPower factor correction (PFC)Low THDHigh efficiencyHigh-power density MeritsBecause it can provide all of the above properties, the three-phase buck-type rectifier (TPBR) as shown in Fig. 1(a) is an appropriate option for the AC-DC power stage. Furthermore, when compared to boost-type three-phase rectifiers, TPBR offers anInherent inrush current free startingBroader output voltage control rangePhase-leg shoot-through protectionOvercurrent protection circuit during short circuit DemeritsDistributed parasitic capacitances between the ground and the DC link output are another problem for TPBR when it operates at high frequencies. These capacitances produce input current distortion, particularly under conditions of low load. High step-down voltage gain is generally recommended when comparing different EVs on the road, taking into account their differences in battery range. Because the standard TPBR modulation index is less than 0.5, which increases losses and affects power quality, matrix-based TPBR is a good option in this situation. Swiss RectifierThe Swiss rectifier (SR), a variant of TPBR, is illustrated in Fig. 1(b). MeritsTPRB, with eight switches compared to six switches, offersGreater efficiencyLower common-mode noiseLower conductionLower Switching loss Because of its circuit nature, SR allows for the implementation of DC-DC converter control techniques. Furthermore, space vector pulse width modulation (SVPWM) may be avoided for SR, making control simpler. Interleaving SRs provides advantageous features likeReduces current and voltage rippleReduces filter requirementsIncreases powerHigh bandwidthReliability DemeritsOne of its main drawbacks is that SR only permits unidirectional power flow. However, to enable vehicle-to-grid functioning, bidirectional SR can be constructed at the expense of additional electrical components and a complex structure. Vienna RectifierWhen compared to a three-phase boost PFC rectifier, the three-phase Vienna rectifier (VR) in Fig. 1(c) operates similarly, but the power flow is unidirectional. Three-phase VR is made up ofThree boost inductors at the inputSix fast rectifier diodesSix switches (two per leg)Two split capacitors at the output VR utilizes a bipolar DC bus design, which improves power flow capability. On the other hand, input current distortion must be avoided by correcting the voltage imbalance in the bipolar DC bus topology. The power losses of several VR topologies were analyzed, and the structure shown in Fig. 1(c) had the fewest losses. As seen in Fig. 1(d), the switches are used in place of the diodes to guarantee bidirectional power flow. Another name for this architecture is a three-phase, three-level T-type rectifier. MeritsVR is commonly employed in high-power applications because of itsStraightforward control mechanismHigh power densityHigh power efficiencyUnity power factorReduced-number switchesLow THDNeutral connection-free constructionThere is no need for a dead zone switching drive since the voltage stress on the switches is half that of the DC link voltage. DemeritsEven if it still retains the three-level converter’s advantages, VR shares many of the disadvantages, such as the need for DC-link capacitors. VR frequency is reduced to about 250 kHz for an improved balance between high-power density and efficiency utilizing standard PCB technology. If this limit is exceeded, input current distortion could result, which would lower the quality of grid power. Three-Phase Boost-Type RectifierA three-phase six-switch boost rectifier (TPSSBR) is shown in Fig. 1(e). It hasThree inductors connected in series with a three-phase input AC sourceSix switches on three legs. Inductors are used to increase the input current voltage and decrease its harmonic content. The top and bottom switches are switched in a complementary manner. MeritsThe three-phase boost rectifier is a good fit for the AC-DC power stage of the EV charger because of itsStraightforward designContinuous input currentBidirectional operationHigh-output DC voltageLow current stressFew switchesStraightforward control schemeLow THDHigh efficiency DemeritsThe reverse recovery loss that the antiparallel diodes experience in the TPSSBR makes the switching loss of the MOSFETs worse. To lessen the anti-parallel diodes' reverse recovery loss, an ultra-fast DC rail diode has been incorporated at the DC-link side. This topology also preserves gentle switching, prevents bridge short-through issues, and guarantees automated step-up operation. Zero-voltage transition (ZVT) and zero-current transition (ZCT) TPSSBRs can also be used to provide soft switching as shown in Fig. 1(f). Multilevel AC-DC ConverterResearchers frequently use the multilevel converter (MLC) architecture, which generates alternating voltage levels from many lower levels of direct current voltages. There are three main types of MLC:Neutral Point Clamped (NPC) MLCFlying Capacitor (FC)Cascaded H-Bridge (CHB) MeritsAn MLC converter's fundamental method of operation is to use switches, capacitors, and voltage sources to create a staircase waveform at the output. Because MLC can supply high power with higher efficiency and power density, it is a preferred option for the AC-DC power stage in EV fast and ultra-quick charging applications. Some of the distinctive features of an MLC areLess voltage stress on the switches in high-voltage applicationsLow EMIReduced voltage transition between levelsLow THDSmaller dv/dtMinimization of magnetic components to allow superior performance Summarizing the Key PointsThe article discusses advanced AC-DC power stage technologies tailored for electric vehicle chargers, emphasizing efficiency and performance improvements.It gains a thorough understanding of the crucial role that topologies, control strategies, and technical specifications play in optimizing on-board charging systems.It explores the dynamic evolution of fast and ultra-fast DC charging solutions, addresses current obstacles, and showcases technological advancements.It also showcases the latest developments in onboard chargers that contribute to reducing the volume and weight of electric vehicles, meeting the growing demand for efficient charging solutions. ReferenceSafayatullah, M., Elrais, M. T., Ghosh, S., Rezaii, R., & Batarseh, I. (2022). A Comprehensive Review of Power Converter Topologies and Control Methods for Electric Vehicle Fast Charging Applications. IEEE Access, 10, 40753–40793. https://doi.org/10.1109/access.2022.3166935

Introduction Power electronics are pivotal in efficiently converting, controlling, and conserving electric power across residential, commercial, and industrial applications. Employing solid-state electronics helps adjust motor speeds, maintain uninterrupted power flow, enable high-frequency power supplies, integrate renewable energy, and positively impact energy usage from electric vehicles to data centers and spacecraft systems to high-speed rail; power electronics touch every arena. At the epicenter of this technology are semiconductor-switching devices like diodes, MOSFETs, IGBTs, and thyristors that shape and regulate power flow. Two stalwarts dominate for medium to high power needs - the metal-oxide-semiconductor field effect transistor (MOSFET) and the insulated gate bipolar transistor (IGBT). Selecting a suitable device is crucial to optimize overall system performance. This article provides a comparative analysis of these two technologies to help design engineers make an informed choice. Understanding Power MOSFETsPower MOSFETs are specialized transistors designed to switch on/off rapidly, allowing precise and speedy power transfer control. They can transition between cut-off and saturation modes in nanoseconds. This swift switching capability stems from their unique insulated gate structure, requiring minimal gate current to trigger state changes. Built-in body diodes facilitate the continuous conduction of load currents in either direction. Silicon has traditionally been the mainstream material, but new comprehensive bandgap materials like silicon carbide and gallium nitride promise significantly higher efficiency. With high breakdown strength, lower losses, and higher junction temperature capacity, these advanced materials drive a significant shift in power electronics. Exploring IGBT DevicesInsulated gate bipolar transistors (IGBTs) aim to combine the best attributes of power MOSFETs and bipolar junction transistors. They integrate the simple gate control of MOSFETs with the superior high current handling capacity of BJTs. A key feature enabling high collector current density is conductivity modulation, where electron and hole injection sustains current flow. However, this also slows down switching transients. The insulating layer blocks high voltages but leads to larger chip sizes. Modern IGBTs lower losses through innovations like trench gates, carrier lifetime control, and field stop layers. Advanced packaging technologies also boost power density and thermal performance. But slower switching speeds and conduction losses at low currents remain innate drawbacks. Comparing Key Application DomainsMOSFETs' ultrafast and controllable switching ability makes them perfect for switch mode power supplies (SMPS), Class D audio amplifiers, DC-DC converters, and lighting controls needing precise regulation. These applications demand fast dynamic response and low losses at moderate voltage and current levels.IGBTs, on the other hand, are extensively used in motor drives, uninterruptible power supplies (UPS), electric traction systems, wind turbines, HVDC transmission, and high power factor correction equipment. These applications require ruggedness to withstand network voltage fluctuations, high DC link voltages, and surge currents during motor commutation or load changes. IGBTs can reliably handle hundreds to thousands of amperes thanks to conductivity modulation but at the expense of switching speed. Analyzing Switching CharacteristicsMOSFETs can transition between on and off states extremely fast, within nanoseconds. This enables them to comfortably operate at frequencies in the MHz range for switch mode operations. However, their switching speeds are limited by charging and discharging intrinsic capacitances across drain, source, and gate terminals during the high di/dt and dv/dt transients.In contrast, IGBTs switch on and off much slower - in the range of microseconds to milliseconds, depending on load conditions. Their switching times are dictated by minority carrier injection and storage dynamics during turn-on and turn-off, respectively. The conductivity modulation mechanism in IGBTs that enables efficient high current operation also adds more delay during transients. Cost, complexity, and application-specific demands impact device selection, too. Analyzing Conduction LossesMOSFETs offer shallow conduction losses at nominal currents, enabling high efficiency. This stems from majority carrier transport through the drain-to-source channel unimpeded by minority charge storage effects. However, the drift component of on-state resistance limits efficiency at high currents due to velocity saturation.In contrast, IGBTs showcase deteriorating conduction losses at low currents but start outperforming MOSFETs above a few amperes current. This reversal occurs due to conductivity modulation wherein electron and hole injections sustain rising collector current density. IGBTs skip past velocity limits at high currents to achieve significantly higher efficiency. Rating on Voltage and Current MetricsLatest generation SiC MOSFETs boast blocking capabilities exceeding 1.7 kV, while GaN variants enable 1.2 kV switch-mode supplies. Commercial IGBT voltage ratings range from 1.2 kV to 1.7 kV presently. However, IGBT packages reliably exceed 1000 A without secondary breakdown concerns for conducting hundreds of amperes. MOSFETs lag on current density metrics presently. Sensitivity to High-TemperaturesIGBT performance depends significantly on temperature swings and self-heating, needing careful thermal management. MOSFETs show lower sensitivity thanks to the absence of conductivity modulation effects. But hotspots can still accelerate aging and degrade long-term MOSFET reliability over time. Cost Considerations Thanks to process maturity, MOSFET design and production costs have been considerably reduced, making them economical for low- and medium-power applications. However, large-area silicon IGBTs can be fabricated at lower costs to score over MOSFETs in high-voltage, high-current areas. Emerging devices like SiC MOSFETs and GaN transistors promise tremendous performance gains but remain expensive. Gazing into the FutureWith continual advances in device structure, doping profiles, and material quality, MOSFET and IGBT technologies are poised to realize higher efficiency, power density, and reliability metrics. Novel cooling techniques leveraging direct liquid immersion or integrated microchannel heat sinks are being explored to dissipate heat from smaller footprints. Clever gate driver techniques and modern packaging methods will help extract the full potential from both devices. Another active area is developing hybrid modules that combine IGBTs and SiC MOSFETs to leverage their complementary strengths for optimal overall performance. The future looks brighter with the increasing maturity of wide bandgap devices and greater systems-level integration! Making the Optimal ChoiceMOSFETs excel for applications demanding nimble and accurate load control, typically up to a few kilowatts. IGBTs are the bedrock where large voltage blocks and high surge current capacity warrant extra ruggedness. However, cost budget, cooling challenges, reliability requirements, and desired switching frequencies also guide decision-making. Designers must weigh tradeoffs between conduction losses, switching frequencies, thermal management complexity, and hardware overheads while selecting the optimal power semiconductor switch. Conclusion In the vast power electronics landscape, MOSFETs and IGBTs remain the primary switching devices for most applications. MOSFETs stand out in environments needing nimble and accurate switching control up to a few kilowatts. IGBTs are the bedrock for systems where large voltages and surge currents demand extra ruggedness. Device selection requires carefully weighing metrics like losses, operating frequency, cooling needs, and costs. With continual technological upgrades, these devices will continue transforming future power management solutions.

Overview: The article discusses the importance of maintenance in ensuring the reliability and safety of power electronic systems. It outlines the steps involved in maintenance, including condition observation, anomaly identification, defect diagnosis, and remaining useful life prediction. Power electronic systems are subject to a variety of risks, including catastrophic failures, despite the careful consideration of dependability characteristics during design and control. This is because of the complex and demanding operating settings of power electronic systems. For field applications, power electronic components, converters, and systems must be extremely reliable and safe. What are the steps in maintenance to make the power electronic system more reliable?Preventive maintenance systems are useful ways to guarantee that planned functions are carried out as intended. The steps in maintenance of power electronic system includesCondition observationIdentification of anomaliesDiagnosing defectsRemaining Use Life (RUL) predictionThe above actions coincide with the IEEE standard framework of prognostics and health management for electronic systems. Condition ObservationPower electronics condition observation consists ofIdentification of system parametersPreprocessing dataMining featuresThe data from the condition observation is used to discover informative and hidden patterns that form the foundation for the prognostic and health management applications that follow. Identification of System ParametersIdentification of system parameters involves the gathering of data for important components.Characteristics of power electronic systems includesExtremely small space inside a power moduleExtremely fast switching frequencyRelatively insignificant parameter changes in terms of aging, etc.Because of these characteristics, developing specific hardware for parameter identification is quite a challenging task.A noninvasive approach that uses existing physical signals to indirectly get information or estimate relevant information without the need for additional hardware implementation is one of the more promising methods.Therefore, a sensorless and cost-effective option can be used for condition monitoring, which is good for people who work in industry. In general, there are two types of methods for identifying system parameters:Model-freeModel-based. Preprocessing data and Mining featuresThe goal of data preprocessing and feature mining is to improve the quality of the raw data so that it can be used for applications like problem diagnostics.Improving the quality of data involves the following steps to make it more organized. The steps are as followsData cleaning to minimize noiseData clustering is used to find groups of related data pointsDensity estimation is used to determine the distribution of the dataData compression to reduce the number of features by projecting large-sized data to small-sized dataData fusion to combine various information sources, and moreWhen data preparation and feature mining are done correctly, the performance of the ensuing prognostics and health management applications—such as diagnostic accuracy—can usually be greatly enhanced. Identification of Anomalies and Diagnosing DefectsThe anomaly detection process focuses on identifying unusual patterns and making a binary decision. When the nominal parameters or rated system characteristics exceed the predetermined safety range, it gives an indication.The fault diagnosis finds and identifies the specific failure modes after the unusual changes happen.The classification, regression, or clustering tasks are essentially anomaly detection and fault diagnosis. When a new fault signature arrives, it identifies the fault label based on the learned relationship from the training stage.Anomaly detection and fault diagnosis techniques fall into two categories:Supervised learningUnsupervised learning Remaining Useful Life (RUL) PredictionIn the design phase, lifetime prediction serves to support the characteristics of a population of units known as the ‘Design for Reliability’. It is one of the crucial components of prognostics and health management.The purpose of the estimation of RUL is not to accurately predict the lifespan of a population of units. Based on condition monitoring data, it predicts the remaining lifespan of each single unit in operation. For applications where availability, safety, or reliability are crucial, RUL prediction is used as an extra tool to lower uncertainty.The lifetime estimate is subject to several challenges, such asInaccuracies in model calibrationManufacturing tolerancesDifferences in operational environments and workloadWhen a particular unit is operated in the field, these uncertainties lead to inaccurate reliability estimations. The following areas require greater attention in order to improve the practicality of AI-based RUL prediction techniques for field applications. Quantification of uncertaintyFor RUL prediction, being able to measure uncertainty is more important than for other regression-related tasks, like control functions. Since the RUL is a random variable, quantifying the confidence interval is crucial for making the best decisions.All of these uncertainties—due to population heterogeneity, measurement noise, various operating settings, etc.—should be considered in a workable practical solution. Quantifying the uncertainty using AI algorithms is quite difficult.A few practical options areThe use of particle filters in neural networks (NNs)Bayesian-based artificial intelligence techniques (e.g., Gaussian process, RVM)Monte Carlo methodsStochastic data-drivenStochastic, data-driven approaches are an interesting option to explore. These approaches can naturally yield the probability density function of the RUL for the purpose of computing the confidence interval. Adaptive capabilityThis is the crucial stage for real-world applications and is related to the model parameter tuning layer in Fig. 1 that connects the offline and online models. If an AI approach lacks adaptive flexibility, its use is limited.Power electronics have difficulties because the operational conditions of the training dataset, which is often acquired through accelerated testing trials, differ significantly from those of the in-situ system (i.e., the test data). Most of the research makes the assumption that the in-situ system's operational parameters are the same as those of the training dataset, which could not be the case in real-world applications.Therefore, the AI-based RUL prediction method's adaptability is essential for bridging the gap between research in academia and practical implementations in industry.Detailed mapping relationship derivations and transfer learning of degradation characteristics under different operating settings (temperature, voltage, humidity, etc.) are also interesting ways to tune model parameters. This means that system models need to be studied in great detail.Fig. 1 shows a methodical flowchart of power electronic system maintenance tasks. It typically comprises the three elements listed below.             Summarizing the Key PointsMaintenance of power electronic systems involves condition observation, anomaly identification, defect diagnosis, and remaining useful life prediction to ensure reliability and safety.The IEEE standard framework for prognostics and health management is applicable to power electronic systems, emphasizing the importance of a comprehensive maintenance approach.Data preprocessing and feature mining are crucial for improving the quality of raw data, enhancing the performance of prognostics and health management applications.AI-based remaining use life prediction techniques face challenges in real-world applications, requiring quantification of uncertainty and adaptability.Power electronic systems require an adaptive maintenance strategy to bridge the gap between research and practical implementation in industry, addressing operational parameter variations. ReferenceZhao, Shuai, Frede Blaabjerg, and Huai Wang. “An Overview of Artificial Intelligence Applications for Power Electronics.” IEEE Transactions on Power Electronics 36, no. 4 (April 2021): 4633–58. https://doi.org/10.1109/tpel.2020.3024914.

Overview: This article proposes a wind-solar hybrid power system that combines solar and a wind turbine power dispatching system that uses a battery and supercapacitor hybrid energy storage subsystem in the process of cost minimization.The proposed wind solar hybrid power system (WSHPS) architecture, which combines a wind energy system (WES) and a photovoltaic energy system (PVES), is shown in Fig. 1.Architecture of Wind Solar Hybrid Power SystemThe PVES has a 1 MW PV array, a maximum power point tracking (MPPT) controller, and a unidirectional DC/DC boost converter. An AC/DC rectifier, a pitch angle controller, and a 1.5 MW direct-drive three-phase permanent magnet synchronous generator (PMSG) linked to a wind turbine make up the WES.Fig. 1. A wind-solar hybrid power system with HESS Source: IEEE AccessPhotovoltaic Energy SystemThe output of the PV array is very sensitive to two environmental factors: PV irradiation and PV cell temperature. MPPT with incremental conductance (IC) controls the duty ratio of the unidirectional boost converter to draw the maximum amount of power from the PV array. In contrast to the more traditional methods used to extract maximum power from PV systems, an IC MPPT is easy to implement and very effective. As a result, IC MPPT has seen widespread application despite the fact that it can cause slight fluctuations in the maximum power point. One nonlinear device that can be modeled as a current source is a photovoltaic cell. The PV output power and capacity factor are both negatively affected when the PV cell temperature is higher than the ambient temperature.Wind Energy SystemThe WES consists of a wind turbine (WT), permanent magnet synchronous generator (PMSG), pitch angle control, drivetrain, and power converter. Without a gearbox, the WES-based PMSG can connect to the WT. PMSG, based on WES, utilizes a two-step process for energy conversion. The WT blades first convert the kinetic energy into mechanical energy. The second step is for the shaft to transmit the mechanical energy to the PMSG, which then uses the energy to generate electricity.LCL FilterTo satisfy smart grid regulations, an inverter's interaction with the grid additionally necessitates a small output harmonic filter. Because of its superior efficiency and ability to dampen harmonics, an LCL filter has been developed.Calculating the Dispatched PowerFurthermore, the WT's output is proportional to the wind speed passing through the rotor. The real solar irradiance, temperature, and wind speed data recorded at NREL to forecast the dispatched power hour by hour for a full day is expressed as PGrid,ref. Therefore, the WSHPS and HESS will continue to contribute the required amount of power to the utility grid throughout each hourly dispatching period. The WSHPS relies on both the PV array and the WT system to generate an average output power throughout each dispatching period.Dispatchable Power from Photovoltaic Energy SystemThe average output power of the PV array is calculated for each dispatching period using the average irradiance and temperature from the NREL solar statistics inputs. Input factors, including solar cell type, number of parallel cells, and number of series cells, as well as environmental circumstances, are used by the PV array module in Matlab/Simulink to generate power-voltage characteristic curves. NREL's solar data has a resolution of one sample per minute. To generate solar data with a resolution of 120 samples/minute, the cubic spline interpolation method is used. After that, the mean operation method is used to get the average irradiance and temperature for each dispatching time. PPVES,est is the estimated power of the PVES derived from the average irradiation, whereas ηPVES,est is the estimated efficiency of the PVES derived from the average temperature. The ultimate estimated power dispatchable by PVES (PPVES) can be written as follows: PPVES = PPVES,est * ηPVES,est    (1)Dispatchable Power from Wind Energy SystemSimilarly, the estimated WES dispatchable power (PWES) is determined. Based on user input parameters such as base wind speed, base rotational speed, blade pitch angle, and maximum power at base wind speed, the WT model in MATLAB/Simulink gives the WT power characteristic curve. Then, the average wind speed is obtained using the mean operation and cubic spline interpolation methods. The PWES is an estimated power output based on the average wind speed. Finally, Equation (2) is used to determine the typical power output of the wind solar hybrid power system, which is expressed as PWSHPS. PWSHPS = PPVES + PWES    (2)Hybrid Energy Storage SystemEach ESS is connected to a bidirectional DC/DC converter, and the HESS is paired in parallel with the WSHPS. Parallel connections between the WSHPS and HESS and the DC-link capacitor bank that functions as the DC bus lead to a three-level T-type inverter that provides clean, stable DC power. By regulating the current through the power converters, it is possible to regulate the output power from the WSHPS and HESS in this architecture. Because of its great efficiency, low total harmonic distortion (THD), and lower common-mode voltage, a three-level T-type inverter is used. Controlling the system power that is fed into the utility grid is the responsibility of the HESS. Calculating the HESS reference power (PHESS,ref) is as simple as subtracting the PGrid,ref from the PWSHPS: PHESS,ref =  PGrid,ref - PWSHPS   (3) Rapidly fluctuating power components can severely shorten a battery's service life. To assign high-frequency power reference components for the supercapacitor energy storage system SESS (PSESS,ref) and low-frequency power reference components for the battery energy storage system BESS (PBESS,ref), the PHESS,ref is supplied through the LPF. In addition, when the ideal value of depth of discharge (DOD) is determined, a rule-based state of charge (SOC) control algorithm is used to keep the BESS SOC within the optimal range (DOD optimum). As with the SESS, after the best value of DOD has been determined, a rule-based SOC control algorithm is put into place to govern the SESS SOC.HESS DOD OptimisationThe DOD and the rate of change of the charging-discharging power are the two most important factors in determining the ESS's useful life. There is an almost exponential link between cycle life and DOD consumption. There are two primary determinants of ESS costs: (i) the ESS's expected service life and (ii) the ESS's minimum capacity. The minimal capacity of the BESS increases as the DOD decreases in use. However, the BESS's service life decreases with increasing discharge depth. Thus, the simulations are run with all possible values of the BESS DOD to find the optimal value of DOD that results in the cheapest BESS for dispatching the WSHPS electricity. Similarly, research into the ideal DOD for the SESS has been conducted. Unlike Li-ion batteries, supercapacitors can be charged and drained indefinitely. Therefore, the total number of charging-discharging cycles for the SESS is taken to be constant.HESS Cost MinimizationThe BESS and SESS use the LPF as their power reference. Minimum SESS capacity is proportional to the LPF time constant, while minimum BESS capacity is inversely related to the LPF time constant. The total cost of the HESS can be reduced by selecting an appropriate value for the filter time constant. The PSO strategy is used to determine the optimal LPF time constant once the suitable cost formula of the HESS as a function of the LPF time constant has been acquired via the curve fitting method. Because of its many benefits, including easy implementation, increased credibility in locating global optimums, the need for the adjustment of only a small number of parameters, and rapid convergence, the PSO method is used. Although genetic algorithms are also commonly used as an optimization approach in renewable energy systems, the PSO typically provides faster evaluation times and higher-quality solutions.Estimation BESS and SESS LifespanThe charging-discharging characteristics of the BESS over a period of time are utilized to evaluate its service life due to the fluctuating nature of the WSHPS output power. Because of calendar aging, the BESS's predicted lifetime decreases. Calendar aging and cycling are both taken into account by the SESS aging model.Estimating the Cost of HESSThe ESS cost is examined while taking into account the costs associated with both cycle and calendar aging. The capital cost, power conversion system cost, and operation and maintenance (O&M) cost of the ESS make up its total expense. Thus, it is possible to estimate the overall cost related to the BESS (CBat,overall) using equation (4): CBat,overall = CCap + Cconv + CO&M     (4)Summarizing the Key PointsThe article proposes a wind-solar hybrid power system that combines solar and wind turbine power dispatching systems.The system uses a battery and supercapacitor hybrid energy storage subsystem to minimize costs.The wind energy system consists of a wind turbine, permanent magnet synchronous generator, pitch angle control, drivetrain, and power converter.The photovoltaic energy system has a 1 MW PV array, a maximum power point tracking controller, and a unidirectional DC/DC boost converter.The article aims to optimize energy storage and power dispatching in wind-solar hybrid systems for cost-effective and reliable electricity supply.ReferenceRoy, Pranoy, Jiangbiao He, and Yuan Liao. “Cost Minimization of Battery-Supercapacitor Hybrid Energy Storage for Hourly Dispatching Wind-Solar Hybrid Power System.” IEEE Access 8 (2020): 210099–115. https://doi.org/10.1109/access.2020.3037149.

Power grids are becoming more decentralized as renewable energy sources take over as the dominant factor. These cutting-edge technological advancements, while providing opportunities for greater productivity.Why is a new reliability framework necessary?The new components of today's power systems bring up novel difficulties that necessitate a new reliability framework, which has recently been implemented. Assessing the reliability of modern power systems necessitates not only assessing various electro-magnetic and mechanical stability difficulties but also introducing new ideas related to local reliability.New Reliability ConceptA new methodology for reliability analysis in contemporary power systems should be established in order to address the issues brought on by new power system technology. It could keep the main ideas of adequacy and security while also taking into account the effects of grid modernization.Modern Power System Adequacy AssessmentThe cyber-physical structure of the current power system, which consists of three layers—power, communication, coupling, and decision—explains the adequate nature of this system. The proposed adequacy assessment framework is depicted in Fig. 1 in order to address all the drawbacks of reliability evaluation methodologies.Fig. 1. Framework for modern power system adequacy assessment. Source: IEEE Open Journal of Power Electronics As illustrated in Fig. 1, the suggested framework allows for the evaluation of the cyber-physical power system's suitability at three hierarchical levels: generation, generation-transmission, and distribution.GenerationFirst and foremost, sufficient generation system capacity is needed to meet system demand as a whole. As a result, the generating sufficiency in HL I can be assessed similarly to the sufficiency of the traditional power system, as illustrated in Fig. 2(a).Fig. 2. Conventional framework for adequacy assessment. Source: IEEE Open Journal of Power ElectronicsCyber-Physical Generation-Transmission SystemTo make sure that the cyber-physical generation-transmission system in HL II is good enough, the effects of the cyber-layers and the effects of distribution generation must be modeled. Large-scale generation units and distribution networks based on microgrids are shown in simplified form in Fig. 3(a). The microgrids are modeled as a specific node at a Point of Common Coupling (PCC), which is depicted in Fig. 3(b), in order to assess the adequacy of these systems. Fig. 3. Scalable framework for modern power system adequacy: a) main structure as a simplified grid; b) equivalent model of microgrids from distribution systems; c) local adequacy for each microgrid. Source: IEEE Open Journal of Power Electronics Depending on the topology and accompanying power management technique inside each microgrid, this special PCC node may be a load or a generation unit for each microgrid in a distribution network. For example, in the substation microgrid comprising medium-scale generators to provide its load, the equivalent load (which is equal to the generation minus the load) can be taken into account at the PCC in Fig. 3(b). Additionally, the equivalent generation can be assumed at the PCC in Fig. 3(b) if the substation microgrid's generation is greater than its load. The substation's internal generation unit availability, load power, and upstream switch reliability all have an impact on this equivalent generation unit's availability. The MV distribution networks can therefore be characterized for transmission system analysis as equivalent loads or generations. The cyber-physical availability model, as shown in Fig. 2(b), can therefore be used for modeling the reliability of the cyber-physical transmission system.Cyber-Physical Distribution SystemThe reliability of cyber-physical distribution networks can be modeled in HL III for each microgrid based on its structure in HL III-A and for the distribution network in HL III-B, as illustrated in Fig. 1. In distribution networks, there are four different types of microgrid structures: single-customer, partial feeder, full feeder, and substation microgrid. The single customer microgrid's adequacy can be modeled by simplifying its structure, as seen in Fig. 3(c). The distribution network outside of the single-customer microgrid is represented in this form as an equivalent generation unit. The local adequacy of the microgrid must be met depending on the application of the single-customer microgrid, such as household load, hospital load, etc. The partial or full feeder microgrid's adequacy can be evaluated similarly to the single-customer microgrid by treating the single-customer microgrids inside it as a specific equivalent node at PCC, which can be a load or generator. Additionally, by modeling the feeder microgrids as special nodes at PCC, the substation microgrid's adequacy is assessed. The distribution network adequacy assessment's primary focus is on the accessibility as well as the availability of energy sources in each sub-grid. This may necessitate restrictions across sub-grids, particularly for single customers who may wish to be islanded during grid outages in order to retain their adequate supply despite the upstream microgrid's declining adequacy. A distribution network consists of numerous substations, which are connected to the high-voltage grid and to one another by MVAC or MVDC transmission systems. Thus, by modeling each substation microgrid as a particular node at their PCC, be it a load or a generator, which is connected to the main grid, it is possible to assess the adequateness of the cyber-physical distribution systems. Due to the presence of DGs and DESS, distribution system reliability, unlike traditional power systems, necessitates local adequacy assessment. The suggested scalable reliability modeling for distribution networks' microgrids ensures each microgrid's adequate suitability.Modern Power System Security AssessmentIn addition to being adequate, modern power systems also need to be secure due to the various sources of uncertainty they include. Similar to conventional power systems, security can be characterized as a system's capacity to tolerate unforeseen events. As indicated in Fig. 4, the security of modern power systems can be examined in three domains: static, dynamic, and cyber. Fig. 4. Framework for security assessment in modern power systems. Source: IEEE Open Journal of Power ElectronicsStatic SecurityThe steady-state operation of the system following any unforeseen event is referred to as static security. The system frequency, bus voltages, and temperature limits of the equipment must therefore remain within a reasonable range. In contrast to traditional power systems, converters specifically for HV and MV transmission lines require appropriate analysis of their thermal limits due to their restricted overloading capacity. Therefore, corrective measures must be taken to maintain system security because any contingency could lead to link overload. Additionally, after any contingency that results in the islanding of the microgrids, the distribution networks must guarantee that the power quality standards are met in addition to the voltage limitations. This is because the power quality requirements for various applications cannot be the same. Therefore, after islanding the microgrids, active and passive filters must be properly relocated in distribution networks to fulfill static security.Dynamic SecurityIn addition, the power system needs to be dynamically secure in case of an emergency. Modern power systems heavily rely on fluctuating energy sources with low inertia; hence, dynamic security is crucial. It could cause problems with voltage and frequency stability in the power systems. Without the proper voltage regulators, intermittent output power or renewable resources may degrade the grid voltage, which may impact the stability of the voltage. Furthermore, the absence of inertia in more or full renewable energy supplies may have an impact on the stability of the grid's frequency. Intercommuting to nearby grids with HVDC systems and using energy storage systems are required to resolve the frequency stability difficulties in the grid. The overall system security can control the size and placement of renewable energy sources, as well as the connection points, capacity, and ancillary services of HVDC networks. Proper system design can guarantee the entire security of the power system. As a result, just like traditional power systems, power system security evaluation calls for an analysis of voltage, frequency, and angular stability. Additionally, due to the widespread use of power electronic converters, the EMM stability difficulties in modern power systems must be taken into account in security evaluation. Power systems and microgrids may experience serious stability problems as a result of EMM interactions. Due to the quick dynamics of converter control systems, the EMM stability assessment within contingency analysis may be a challenging and time-consuming operation. Therefore, adequate models and tools for EMM stability analysis for security evaluation in modern power systems should be established.Cyber SecurityModern power systems are vulnerable to cyber-security vulnerabilities in addition to static and dynamic security problems. Cyber problems may be connected to either the decision layer or the communication and coupling layer. The physical malfunction of monitoring and measurement devices, as well as the lack of data availability, can have an impact on the system's performance at the communication and coupling layers. Additionally, cyberattacks affecting sensors and shift measurements, as well as physical failure of decision equipment that results in false data being injected into communication links, can lead to poor decisions and malfunctions in power systems. The security of the power system must be ensured against physical failure, data loss, and cyberattacks. These issues could have a number of detrimental effects on the system, including angular and frequency stability due to poor decision-making and a change in the demand-generation balance, issues with islanding detection and grid separation, as well as effects from equipment overloading, all of which could jeopardize the security of the entire system. Therefore, in security evaluation and management, it is necessary to consider the cyber-security of modern power systems.Summarizing the Key PointsThe decentralization of power grids due to renewable energy sources requires a new approach to assessing their reliability. The cyber-physical structure of the current power system consists of three layers: power, communication and coupling, and decision. The main ideas of adequacy and security are taken into account in new reliability framework. The new framework can address all the drawbacks of reliability evaluation methodologies. The cyber-security of modern power systems is a crucial consideration in security evaluation and management.ReferencePeyghami, Saeed, Peter Palensky, and Frede Blaabjerg. “An Overview on the Reliability of Modern Power Electronic-Based Power Systems.” IEEE Open Journal of Power Electronics 1 (2020): 34–50 https://doi.org/10.1109/ojpel.2020.2973926.

Overview: The article discusses the rapid growth of renewable energy resources, particularly photovoltaic and wind turbines, as the most attractive power generation options due to strong government incentives and encouragement to use green energy. Over the past ten years, the use of renewable energy resources has grown rapidly throughout the world. Renewable energy sources, especially photovoltaic (PV) and wind turbines (WT), have emerged as the most attractive power generation options.Challenges in Renewable Energy Based Power SystemsThe installed wind turbine capacity increased from 540 GW to 591 GW between 2017 and 2018, while the installed solar photovoltaic capacity increased from 405 GW to 505 GW. The output of the photovoltaic and wind turbines exhibits unstable characteristics because it is heavily dependent on weather factors such as wind and cloud movement. The utility grid faces significant technical challenges with regard to power quality, generation dispatch control, and grid reliability as a result of the substantial penetration of these types of intermittent renewable energy sources. As a result, operators of renewable energy plants will face pressure to deliver consistent power, much like conventional fossil fuel power plants have done. Overgeneration and restrictions are the grid operators' growing concerns as more photovoltaic and wind turbines are connected to the grid. There are primarily two reasons for the curtailment of renewable energy, namely regional supply excess and regional transmission constraints. Although higher levels of curtailment have also been reported, the typical range of curtailment levels for wind generation is between 1% and 4%. When rigid traditional generators, like nuclear and coal plants, are unable to be used to generate lower power, negative pricing and the curtailment of renewable energy generation occur. The duck curve, which is depicted in Fig. 1, can be used to show the enormous difficulty of incorporating solar and wind energy as well as the likelihood of overgeneration and curtailment. Fig. 1. Duck curve illustration. Source: IEEE AccessThe Idea of Hybrid Power SystemsIt is generally accepted that any individual wind or solar source cannot sustainably power a load. It should also be noted that the hours of maximum output for wind and solar systems vary throughout the day and the year. The weather and climate patterns actually make solar and wind energy resources mutually beneficial. Thus, on a seasonal or daily basis, the energy produced by wind-photovoltaic resources keeps reversing. Since photovoltaic and wind turbines have benefits that complement one another in terms of power profiles, the hybrid utilization of the two should receive more attention. It is possible to develop hybridization techniques to deal with the intermittent nature of solar and wind power.Wind-Solar Hybrid Power SystemsThe wind-solar hybrid power system (WSHPS) combines photovoltaic and wind turbine subsystems to boost overall system efficiency, reduce energy storage capacity needs, and make the power grid more reliable. Wind-solar hybrid power systems are better than single photovoltaic or wind turbine systems in deficient utilities because they can compensate for unwanted intermittent variations with a single renewable energy source. In addition, the wind-solar hybrid power system can help the points of generation and consumption be adjacent to each other, which reduces infrastructure costs, particularly for rural electrification projects. As a result, wind-solar hybrid power system schemes at a single location are becoming a prominent trend in the worldwide transition to renewable energy. Voltage and frequency regulation, the mismatch between generated power and load demand, grid operation economics, and the scheduling of generation units are just some of the difficulties associated with the incorporation of large amounts of intermittent renewable energy into the utility. Therefore, grid operators must take extra measures to guarantee the reliability of the system. Because of the addition of solar and wind energy to the grids, fossil fuel generators, for example, need to be switched on and off or have their outputs adjusted more frequently to account for power fluctuations. In addition to raising maintenance costs, frequent cycling of fossil fuel generators also reduces efficiency. With high solar penetration, the cost of cycling ranges from $0.47/MWh to $1.28/MWh per fossil-fueled generator. Therefore, the aforementioned economic challenges necessitate a constant power dispatch commitment from the wind-solar hybrid power system framework at an acceptable interval.Energy Storage SystemsAdding the energy storage system (ESS) to the wind-solar hybrid power system framework will further mitigate the risks associated with renewable energy sources. In particular, the energy storage system makes it possible to provide supplementary services like voltage regulation, frequency regulation, harmonic reduction, transient stability, and load leveling. There are a variety of energy storage systems on the market, but two of the most popular are batteries and supercapacitors (SC). The characteristics of the battery and supercapacitors are compared in Table 1. There are many similarities between the supercapacitors and the conventional capacitors, with the main differences being the supercapacitors' smaller size and longer lifespan. Table 1: Battery and SC Performance Comparison Source : IEEE Access The battery energy storage system (BESS) has a low-power ramp rate, which indicates that the BESS charging-discharging rates are insufficient to meet peak or pulse load demand despite its high energy density property. The energy density is low, but the power ramp rate is high in the supercapacitor energy storage system (SESS). So, the supercapacitors can't keep up with the load for as long as it's needed. It's obvious that neither of these energy storage systems has both a high power density and a high energy density. Therefore, if only one kind of energy storage system is deployed to meet both the power and energy capacity specifications, a high installation cost may be needed to meet both the energy and power capacity needs.Hybrid Energy Storage SystemTherefore, a cost-effective energy storage system can be developed through the use of a hybrid energy storage system (HESS) consisting of a battery energy storage system and a supercapacitor energy storage system, with the supercapacitor facilitating the fast-changing power components passing through the battery, which increases the service life of the battery.Hybrid Energy Storage for Wind-Solar Hybrid Power SystemsThe main goal is to improve the way that renewable energy is used so that the wind-solar hybrid power system output power can be sent to the power grid every hour for a whole day, as desired. For this, the wind-solar hybrid power system architecture incorporates a hybrid energy storage system made up of lithium-ion batteries and supercapacitors, which can store the collected wind-solar hybrid power system energy and transform the intermittent energy into a reliable supply that can be dispatched when needed.Dispatching SchemeTo provide the wind-solar hybrid power system's output power to the utility grid, a dispatching scheme has been employed rather than the conventional peak shaving or smoothing approach. The wind-solar hybrid power system can be regulated like other conventional generators, such as thermal and hydropower plants, because of the utility's dispatching scheme. When combined with the dispatched scheme by which wind-solar hybrid power system output power is supplied to the grid, this flexibility extends to the utility grid in many ways, including the scheduling of generation units, the economics of grid operation, and the provision of grid ancillary services.Low Pass FilterA low pass filter (LPF) is used to split the energy produced by the hybrid energy storage system into two groups: the SC group receives power with a fast-dynamic response, while the battery group receives power with a slow-dynamic response. The battery's lifespan is increased by using this method because it helps the battery avoid rapid charging and discharging cycles and a large discharge current. In addition, the most cost-effective hybrid energy storage system for hourly dispatching of the wind-solar hybrid power system power scheme is sought by using curve fitting and Particle Swarm Optimization (PSO) techniques. The goal is to minimize the cost of the hybrid energy storage system while keeping the energy storage system's state-of-charge (SOC) within a certain range and meeting the power demand during each dispatching period.Summarizing the Key PointsRenewable energy resources, particularly solar and wind, have grown rapidly due to strong government incentives. The output of these energy sources exhibits unstable characteristics due to weather factors such as wind and cloud movement. Hybrid power systems that integrate wind and solar energy can maximize the potential of renewable energy. Technical challenges in photovoltaic and wind turbine power systems need to be addressed to overcome the unstable characteristics of renewable energy. The integration of energy storage systems can help mitigate the variability of renewable energy sources.ReferenceRoy, Pranoy, Jiangbiao He, and Yuan Liao. “Cost Minimization of Battery-Supercapacitor Hybrid Energy Storage for Hourly Dispatching Wind-Solar Hybrid Power System.” IEEE Access 8 (2020): 210099–115. https://doi.org/10.1109/access.2020.3037149.