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When electric vehicles (EVs) encounter an emergency, the voltage of the dc-bus capacitor in the surface-mounted permanent magnet synchronous motor (SPMSM)-based powertrain requires to be reduced as fast as possible. In order to eliminate the disadvantages and synthesize the advantages of the traditional machine-winding-based and external bleeder-based discharge techniques, this article proposes a hybrid discharge strategy that can achieve 5-s discharge in the minimum sacrifice of the bleeder size and weight for any EV drives. For the purpose of evaluating the size reduction of the new method, the individual bleeder-based scheme is modeled and analyzed at first. Then, the combined discharge method is developed, which contains two sequential procedures: bleeding resistor (BR) design and discharge control algorithm design. The BR design process has to be implemented under extreme condition. But concerning that the emergency might occur at the moment when the machine operates below the maximum speed, three different discharge modes including full-power, partial-power, and bleeder-based discharge modes are developed. The proposed discharge techniques are verified by experiments that are conducted on a three-phase SPMSM drive system used for EVs. [ABSTRACT FROM AUTHOR]

When the permanent magnet synchronous machine (PMSM) based electric vehicles (EV) are in the postcrash situations, the dc-bus capacitor voltage requires to be reduced quickly for the sake of electric shock risk prevention. Currently, due to the advantages of low cost, compact structure, and high reliability, the pure-winding-based discharge strategies are attracting increasing attentions. However, there are no theoretical criteria for judging whether a pure-winding-based method is suitable for bleeding a particular PMSM-based EV drive, not to mention the rules for opting for an effective discharge strategy among the instant nonzero d-axis, zero q-axis (NDZQ), long-cycle NDZQ, and the nonzero d-axis, nonzero q-axis (NDNQ) current control techniques. This article discusses the applicable occasions of the instant NDZQ, long-cycle NDZQ, and NDNQ discharge methods based on parametric analysis. On this ground the principles for determining whether an EV drive can adopt a pure-winding-based method for discharge are given. Meanwhile, the implementation procedures of the proposed criteria are detailed clearly. Finally, the proposed selection criteria are used for evaluating five different EV drives so as to select the corresponding winding-based discharge strategy for each system, and the effectiveness is verified by simulation or experiments. [ABSTRACT FROM AUTHOR]

The intermittent and stochastic nature of solar resource hinders the integration of solar energy into modern power system. Solar forecasting has become an important tool for better photovoltaic (PV) power integration, effective market design, and reliable grid operation. Nevertheless, most existing solar forecasting methods are dedicated to improving forecasting accuracy at site-level (e.g. for individual PV power plants) regardless of the impacts caused by the accumulated penetration of distributed PV systems. To tackle with this issue, this article proposes a novel generative approach for regional solar forecasting considering an entire geographical region of a flexible spatial scale. Specifically, we create solar irradiance maps (SIMs) for solar forecasting for the first time by using spatial Kriging interpolation with satellite-derived solar irradiance data. The sequential SIMs provide a comprehensive view of how solar intensity varies over time and are further used as the inputs for a multi-scale generative adversarial network (GAN) to predict the next-step SIMs. The generated SIM frames can be further transformed into PV power output through a irradiance-to-power model. A case study is conducted in a 24 × 24 km area of Brisbane to validate the proposed method by predicting of both solar irradiance and the output of behind-the-meter (BTM) PV systems at unobserved locations. The approach demonstrates comparable accuracy in terms of solar irradiance forecasting and better predictions in PV power generation compared to the conventional forecasting models with a highest average forecasting skill of 10. 93 ± 2. 35 % for all BTM PV systems. Thus, it can be potentially used to assist solar energy assessment and power system control in a highly-penetrated region. • A regional solar forecasting approach using solar irradiance maps (SIMs). • Using generative model to produce image-based forecasts for an entire region. • Extending forecasts to the regional level with flexible geographical scales. • Potential applications for distributed photovoltaic power estimation. [ABSTRACT FROM AUTHOR]

Under partial shading conditions (PSC), the power-voltage (P–V) characteristic curve of a photovoltaic string exhibits multiple peaks, posing a big challenge to the problem of global maximum power point tracking (GMPPT). The traditional 0.8 VOC-model-based GMPPT method locates the global maximum power point (GMPP) locus by comparing the power at each local power peak. However, a considerable amount of time is required for iteratively scanning each 0.8 VOC vicinity. To address this problem, an improved 0.8 VOC-model-based GMPPT method is proposed in this article. A shading vector is introduced to characterize the PSC. The proposed GMPPT method estimates the 0.8 VOC region with the GMPP directly from the measured shading vector by the k-nearest neighbors approach and saves the time consumed in the comparison process used in the conventional method. Simulation and experimental results demonstrate that the proposed method is capable of tracking the GMPP efficiently and accurately under various shading patterns. [ABSTRACT FROM AUTHOR]

This article proposes a new finite control set model predictive control (FCS-MPC) strategy that simultaneously evaluates two targeting control objectives including speed and currents in a single cost function, achieving high-performance single-closed-loop control structure. Besides, aiming at the calculation delay problem of the model predictive control controllers, a novel calculation delay compensation method by predicting the current variation within the delay time is proposed. In this article, an improved machine model that is especially designed for the multiobjective FCS-MPC operation is illustrated at first. Then, a new cost function that can evaluate the tracking performance of speed and d-axis current and the steady-state performance of the q-axis current is developed. Compared with the conventional FCS-MPC approaches, extra speed controllers are not needed so that the proposed control topology becomes simpler. Then, in order to tune the weighting factors for the speed and currents in the cost function, an efficient handling strategy containing two implementation procedures, state variable normalization and balance of state sensitivity to voltage alteration, is developed. Finally, a brand-new computation delay estimation and compensation technique based on the dual sampling within a control period is proposed to reduce the current and torque ripples during the control process. Comparative simulation and experiments conducted on a three-phase 1.5-kW permanent magnet synchronous machine drive system are employed to verify the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

The precision of position estimation is highly dependent on the accuracy of multiple current sensors, whereas the conventional error calibration strategies for current sensor accuracy uncertainty (SAU) problem have limitations regarding the position sensorless controlled drives. In order to solve this thorny problem, this article proposes a mutual calibration strategy for the multiple current sensors in an interior permanent magnet synchronous motor (IPMSM) drive. The proposed current sensor error calibration strategy takes full advantage of the correlation among the multiple current sensors themselves without using any complicated observers. Moreover, the traditional seven-segment space vector pulsewidth modulation technology is applied without modification. The only change is reflected in several sets of the artificially added current sampling points. The effectiveness of the proposed strategy is verified by experimental results on a 5-kW IPMSM motor prototype, which shows that the calibrated current sensors exhibit improved accuracy, and the position estimation accuracy is also guaranteed. [ABSTRACT FROM AUTHOR]

In order to enhance the control performance of the surface-mounted permanent magnet synchronous machines (PMSM) working under the low frequency situations, this letter innovatively proposes an accurate finite control set (FCS) model predictive current control (MPCC) method. First, a novel predicting plant model in the continuous-time domain based on the numerical solutions of the PMSM state-space model (differential equations) is developed. Without using the linear discretization implementation, the influence of the low control frequency can be eliminated completely. Besides, a brand-new calculation delay compensation method based on delay time prediction and current precompensation is designed for the proposed FCS–MPCC strategy. Finally, experiments are conducted on a PMSM test bench with the control frequencies of 2 and 1 kHz to comprehensively verify the proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes a perturbation estimation based nonlinear adaptive power decoupling controller for doubly fed induction generator based wind turbines (DFIG-WTs). Perturbation states are defined to include the nonlinearities, uncertainties of the system model, the cross-coupling between control loops, and external disturbances. Perturbation observers are designed to estimate the fast time-varying perturbation states. With perturbation estimation, the DFIG-WT system is fully decoupled, and an output feedback control can be designed for the control of rotor currents. Rotor current references are calculated based on the steady-state relation between active/reactive power and rotor current, and stator dynamic is ignored. The performance of the proposed controller is evaluated and verified via both simulation and experimental tests. [ABSTRACT FROM AUTHOR]

Aging affects different photovoltaic (PV) modules in a PV array in a non-uniform way, thereby leading to non-uniform working conditions of the PV modules and resulting in variations in the power outputs of the PV array. In this paper, an algorithm is developed for optimising the electrical configuration of a PV array during the non-uniform aging processes amongst the PV modules. A new PV array reconfiguration method is proposed to maximize the power generation from non-uniformly aged PV arrays through rearrangements of the positions of the PV modules without having to replace the aged PV modules with new ones, thereby saving on maintenance costs. This reconfiguration strategy requires information about the electrical parameters of the PV modules in an array, so as to choose the optimal reconfiguration topology. In this algorithm, the PV modules are sorted iteratively in a hierarchy pattern to reduce the effect of mismatch due to the non-uniform aging processes amongst PV modules. Computer simulation and analysis have been carried out to evaluate the effectiveness of the proposed method for different sizes of non-uniform aged PV arrays (4 × 4, 10 × 10, and 100 × 10 arrays) with MATLAB. The results show an improvement in the power generation from a non-uniformly aged PV array and can be applied to any size of PV array. [ABSTRACT FROM AUTHOR]

There has been growing interest in using photovoltaic (PV) energy harvesting technology to reduce reliance on mineral-based energy. Partial shading scenarios (PSS) significantly affect the electrical characteristics of a PV generator. However, a few studies have devoted to the detection and assessment of the PSS. In this paper, shading rate and shading strength are used to characterize the PSS. A shading pattern detection algorithm is proposed to estimate the number of shaded modules in a PV string and distinguish the PSS from uniform irradiation scenarios. A multiple-output support vector regression is applied to estimate the shading strength. In addition, the maximum power point voltage of the applied PV generation system can be predicted from measured data. Simulation and experimental validation show the feasibility of the proposed method in the face of various environmental conditions. It could be used as a preliminary step toward automatic supervision and monitoring PV generation system. [ABSTRACT FROM AUTHOR]

Plug-in hybrid electrical trucks (PHETs) are a kind of emerging transport solution to reduce greenhouse gas emissions. Switched reluctance motors (SRMs) are one of the popular choices for PHETs applications due to characteristics of rear-earth free, high starting torque, wide-speed range, and good fault tolerance. Usually, more than two converters are needed to achieve flexible energy conversion among multiple electrical energy components on board, i.e., generator, battery bank, and motor. High-power converters should be used to drive the trucks that occupy the limited on-board space. Furthermore, an extra converter is also needed to achieve ac grid connecting charging. All these converters make the on-board power electronics converter complicated. In this paper, a modular tri-port high-power converter for SRM based PHETs is proposed to combine the multiple electrical energy components into one converter. The modular tri-port high-power converter can not only support flexible energy flow, but also support parallel and series winding connections according to different conditions. Furthermore, ac grid connecting nodes are also developed in the drive, which allows the proposed converter to work as a grid connecting charger without extra facilities. The simulation and experiments are employed to verify the feasibility of the proposed converter and corresponding control strategies. [ABSTRACT FROM PUBLISHER]

A new model of the optimum tilt angle of a soiled photovoltaic (PV) panel is proposed in this paper. The tilt angle is a key factor that influences the output power of PV panel, while dust deposition is an inevitable external element to be considered. In this paper, the solar radiation model is studied by analysing the Hay, Davies, Klucher, Reindl (HDKR) model. The cell temperature of a PV panel is also investigated to evaluate the power output. A fitting formula is derived to express the relationship between the dust deposition density and the tilt angle, and it is integrated in the output model of a fixed-type PV panel. Besides, the effect of dust deposition on the transmittance is analysed. An inverse correlation between the dust deposition density and tilt angle can be obtained, and the optimum tilt angle is calculated to maximize the power output of a soiled PV panel. Simulation is conducted by Matlab to demonstrate the validity of the proposed model of the optimum tilt angle with the shielding effect by dust. Furthermore, the relationship between dust deposition and the working temperature of PV panel is investigated by indoor experiments. [ABSTRACT FROM AUTHOR]

• A partial shading emulator for module-level emulations of utility-scale PV systems is proposed. • A fully customizable cloud shadow model that can reproduce real cloud coverage natures is introduced. • Two endogenous factors, namely PV array arrangement and system orientation are evaluated. • Three exogenous factors, namely shadow intensity, shadow velocity, and shadow size are explored. • Cloud shadow transitions exploited from real measurements are applied for assessing ramp-rates in reality. The short-term power output variability of solar photovoltaic (PV) systems caused by passing clouds is becoming a major concern for grid operators. As the penetration of utility-scale PV systems boosts, the rapid power fluctuations greatly challenge the grid transient stability. In this regard, the concept of power ramp-rate (RR) has been recently imposed to quantify the PV fluctuations, and a series of ramp regulations are implemented by utilities. However, due to the limitations in terms of high-resolution simulation of utility-scale PV systems and reproducing cloud shadow natures, current studies still show deficiencies in comprehensively investigating the RRs rising from both endogenous and exogenous factors during cloud shadow transitions. With the objective of producing high-resolution and high-accuracy emulations of utility-scale PV systems under passing clouds, thus providing a clearer understanding on the cloud-induced RRs, this paper first sets forth a partial shading emulator that is capable of efficiently mimicking the behaviors of an arbitrary partially shaded PV system, in accuracy of the PV module level. Then a fully customizable shadow model that can reproduce the natures of a real cloud shadow is introduced. Based on the developed emulation tools, the effects of two endogenous factors i.e., PV array arrangement and system orientation, and three exogenous factors i.e., shadow intensity, shadow velocity, and shadow size on RRs are explored for a range of utility-scale PV systems from 1 MW to 60 MW. Furthermore, in order to assess the RRs in reality, a total of 3747 cloud shadow transitions exploited from real measurements have been applied for emulations. The results reveal that the RRs caused by passing clouds are critical problems for system operations, and a larger system can suffer more from ramp violations, indicating that the advanced ramp control strategies should be essential for contemporary utility-scale PV systems. [ABSTRACT FROM AUTHOR]

• A concentric sensor network for PV power nowcasting. • A comprehensive framework for spatial and temporal predictor preselection. • Consistent PV nowcasts at a fixed prediction horizon, with cloud dynamics contained. • Strong model adaptability to various weather conditions. • A practice of integrating the nowcasts to PV grid-friendly control. The increasing penetration of photovoltaics (PV) systems introduces more uncertainties to the power system, and has drawn serious concern for maintaining the grid stability. Consequently, the PV power grid-friendly control (GFC) has been imposed by utilities to provide additional flexibilities for power system operations. Conventional GFC strategies show limitations to estimate real-time maximum available power, especially when fast moving clouds occur. In this regards, the spatio-temporal (ST) PV nowcasting using a sensor network provides a remedy to the above issue. However, current ST nowcasting methods suffer from the problems such as predictor mis-selection, inconsistent nowcasting, and poor model adaptability, which still hinder their practical use for GFC. In this paper, a novel ST PV power nowcasting method with predictor preselection is presented, which can be used for GFC. The proposed method enables a fast and precise predictor preselection in different scenarios, and provides consistent PV nowcasts with cloud information interpolated. The effectiveness of the proposed nowcasting method is evaluated in a real sensor network. The experimental results reveal that the proposed method has strong robustness in case of various weather conditions, with fewer training data used. Compared with the conventional methods, the proposed method shows an average nRMSE and nPMAE improvements over 13.5 % and 41.3 % respectively in the cloudy days. A practice of integrating the proposed nowcasting method to GFC operation is also demonstrated. The results show that the proposed method is promising to improve the performance of GFC. [ABSTRACT FROM AUTHOR]

Reliability is one of the critical issues for a modular multilevel converter (MMC) since it consists of a large number of series-connected power electronics submodules (SMs). In this paper, a complete control strategy including fault detection, localization, and tolerant operation is proposed for the MMC under an insulated gate bipolar transistor (IGBT) open circuit fault. According to the output characteristics of the SM with the open-circuit fault of IGBT, a fault detection method based on the circulating current and output current observation is used. In order to further precisely locate the position of the faulty SM, a fault localization method based on the SM capacitor voltage observation is developed. After the faulty SM is isolated, the continuous operation of the converter is ensured by adopting the fault-tolerant strategy based on the use of redundant modules. To verify the proposed fault detection, fault localization, and fault-tolerant operation strategies, a 900 kVA MMC system under the conditions of an IGBT open circuit is developed in the Matlab/Simulink platform. The capabilities of rapid detection, precise positioning, and fault-tolerant operation of the investigated detection and control algorithms are also demonstrated. [ABSTRACT FROM AUTHOR]