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• LLC-resonant voltage-multiplier-based DPP optimizer is presented with low cost and good extensibility. • The switch count is limited to two for long-string photovoltaic systems. • The output power under severe shading scenario can be improved up to 32.9%. • The presented DPP optimizer cost for four-module-series-connection PV systems can be reduced up to 45.41%. Mismatched photovoltaic (PV) power systems due to the shadow effect will result in serious consequences such as reduced output power, hot spot problem, and low reliability. As one promising architecture to address this issue, differential power processing (DPP) optimizer has been extensively discussed to improve the actual energy yield through the charge redistribution among PV elements such as modules or sub-modules. However, since a large number of hardware components must be added in the conventional DPP optimizer, high cost and poor extensibility have become the bottleneck for the practical application of DPP technique in long-string photovoltaic systems. This paper presents an LLC-resonant voltage-multiplier-based DPP (LLC-VM-DPP) optimizer to address these problems. Specifically, the LLC resonant inverter with two switches is operating as a voltage equalizer to compensate the power reduction of shaded PV elements. The switch count is limited to two even for long-string photovoltaic systems. No feedback is required for the control implementation. Thus, the overall system performance such as the cost, circuit complexity, extensibility, power density, and efficiency can be improved. Simulation and experimental evaluation of the LLC-VM-DPP architecture for four-module-series-connection PV systems under different shading scenarios was carried out. Detailed power loss analysis was presented. With the LLC-VM-DPP architecture, the measured output power under severe shading scenario can be improved up to 32.9% while the presented DPP optimizer cost for four-module-series-connection PV systems can be reduced up to 45.41%. [ABSTRACT FROM AUTHOR]

• Nonisolated switching-capacitor-integrated three-port converter is presented. • Flexible power regulation and power balance among three ports are achieved. • The current stress is reduced and the overall efficiency can be improved. • The measured efficiency under a rated output power will be high up to 94%. Efficiency and power density of power converters for interfacing photovoltaic panels, energy storage components such as batteries, and loads in photovoltaic (PV) systems become more and more important. Compared with individual converter design for different terminals, power-integrated multiport converters shows obvious advantages in simplifying the system structure, reducing the component count, and improving the operation reliability. Originated from the high power-density switched capacitor topology, a nonisolated switching-capacitor-integrated three-port converter (SCI-TPC) is presented to achieve single-stage direct power conversion among three ports. In order to minimize the cross-regulation effect, pulse-width-modulation (PWM) and pulse-frequency-modulation (PFM) are adopted to realize the flexible power regulation and achieve power balance among three ports. Main operation modes, power flow distribution, and power transfer characteristic are analyzed. With the seamless PWM and PFM hybrid modulation, the current stress can be reduced and the overall conversion efficiency over a full operating range can be improved. Main experimental results are provided to validate the effectiveness of the proposed concept. [ABSTRACT FROM AUTHOR]

• A flexible power point tracking (FPPT) strategy is proposed without additional hardware cost. • The algorithm is simple and effective for both ramp-up and ramp-down rate control. • A ramp-rate measurement (RRM) method is proposed to detect the power ramp-rate event. • The proposed PRRC strategy can regulate the ramp rate under 3W/s, which is effective with low cost. Due to the intermittent nature of renewable power generation, the power ramp-rate control (PRRC) strategy becomes essential for Photovoltaic (PV) systems with the increased penetration ratio recently. However, most of the PRRC strategies are based on energy storage systems, which require high installation cost. Therefore, it is important to find alternative technology to avoid the additional hardware components and make the PV system more cost-effective. In this paper, a novel PRRC strategy is proposed, which is based on a flexible power point tracking (FPPT) strategy without the additional hardware cost. Besides, a ramp-rate measurement (RRM) method is proposed to detect the power ramp-rate event. The proposed PRRC algorithm is suitable for both of the ramp-up and ramp-down cases. Furthermore, it is simple and effective in regulating the PV power fluctuations under the framework of grid code. The effectiveness of the proposed PRRC strategy is validated through simulation and experimental evaluation under various scenarios. The experimental results based on the real-filed meteorological profile validate that the proposed PRRC strategy can effectively regulate the ramp rate under 3 W/s, which is corresponded to 5% of the rated PV power/min. [ABSTRACT FROM AUTHOR]

• The PV-Isolated Port based differential power processing technique was designed. • The power rating analysis of PV-IP based DPP systems is presented. • A protection strategy is proposed to realize modular design. • The measured improvements for the severe mismatch is 77.14%. In a photovoltaic generation system (PGS), photovoltaic (PV) modules are often connected in series for increased string voltage. However, a significant reduction in the actual output power is observed due to the manufacturing tolerance, module aging and partial shaded. Compared with conventional methods such as bypass diodes and PV module reconfiguration, modular distributed architecture especially the differential power processing (DPP) is able to yield high output power even under partial shading conditions. Moreover, the system efficiency is improved since only the differential power is processed by the DPP converters. This paper mainly focuses on the power rating analysis and protection of PV-isolated Port (PV-IP) based DPP systems considering the significant power stress difference among DPP converters under different partial shading conditions. The voltage equalization (VE) control used in this work is able to provide up to 77% efficiency improvement through the simulation evaluation. The protection algorithm is proposed for the PV-IP DPP architecture to improve the system reliability even when some DPP converters are found failed. With the proposed protection strategy, not only the high output power yield can be maintained, but also the modular design of DPP converters with smaller power capacity can be achieved. Simulation and indoor experimental tests under various partial shading conditions were carried out to validate the effectiveness of the proposed power rating analysis and protection scheme. [ABSTRACT FROM AUTHOR]

Highlights • A novel GMPPT algorithm with fast tracking speed is proposed. • Variable perturbation frequency to speed up the dynamic tracking speed. • Fixed duty cycle is implemented with the perturb and observe (P&O) to realize the zero oscillation. • The measured efficiency with the proposed control is 22.6% higher than the conventional PSO. Abstract By combing the advantages of two widely-used methods together, namely the particle swarm optimization (PSO) and the perturb and observe (PO), this paper develops and discusses a novel GMPPT algorithm with fast tracking speed for different partial shading patterns and zero steady-state oscillation. Three key elements that form the foundation of the proposed algorithm have been discussed: (1) variable perturbation frequency (VPF) to speed up the dynamic tracking speed; (2) PO tracking is used after convergence of PSO to tackle the reinitialization problem of the PSO since PSO is often unable to detect the small change in the PV system; (3) fixed duty cycle is implemented for the steady state with the PO to realize the zero oscillation. Different partial shading patterns and varying irradiance scenarios are used to evaluate the transient as well as steady state operation of the algorithm. Both simulation and experimental results show that the VPF can greatly reduce the duration of the searching interval of the PSO tracking stage while the following PO tracking stage ensure the correct detection of the proposed algorithm for small changes in the PV system and zero oscillation for the steady state operation. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a novel beta parameter three-input one-output fuzzy-logic based maximum power point tracking (MPPT) algorithm is presented for the photovoltaic (PV) system application. The conventional fuzzy-logic controllers (FLCs) exhibit obvious limitations such as their dependence on the user's knowledge about the system and complicated rules. Furthermore, they show inherent dilemma between the rules number of FLC and the universality for various operating conditions, which is revealed and explained with details in this paper. Thus, a novel FLC is proposed by introducing a third input: an intermediate variable β. It can simplify the fuzzy rule membership functions and cover wider operating conditions. The dependence on the user's knowledge about the system is reduced. The converging speed for transients is improved and oscillations around the MPPs are completely eliminated compared with conventional MPPT methods. Typical operation conditions such as varying solar irradiation and load resistance are tested for fair comparison of various algorithms. An experimental prototype was designed and main experimental results were presented to verify the advantages of the proposed algorithm. Highlights • A novel FLC is proposed by introducing an intermediate variable β and it can simplify the fuzzy rule membership functions. • The dependency on the designer's knowledge of the system can be reduced by using the proposed algorithm. • The converging speed for transients is improved and oscillations around the MPPs are eliminated. • Various scenarios are analyzed and simulated according to the irradiance change and load variation. • Both simulation and experimental evaluation demonstrate the superior performance over other traditional MPPT methods. [ABSTRACT FROM AUTHOR]

Highlights • A current sensorless maximum power point tracking (MPPT) algorithm is proposed. • Drift-free technique is achieved and high tracking efficiency is realized. • A mathematical expression is obtained for the drift-free criterion. • Threshold is determined by the Lambert W function under the EN50530 standard. • The proposed algorithm was experimentally evaluated under different scenarios. Abstract High system cost and reduced output power due to the changing weather conditions such as the irradiance or temperature are two major concerns for a practical photovoltaic (PV) system design. This paper presents a current sensorless (CS) maximum power point tracking (MPPT) algorithm that uses only one single-input-voltage sensor (SIVS) and totally eliminates the expensive current sensors, which can significantly reduce the system cost and retain the advantages of the widely used MPPT algorithms such as incremental conductance (INC). To further eliminate the drift effect, which is a severe phenomenon due to the incorrect decision in duty cycle for fast irradiation change, drift-free technique is adopted in the presented algorithm by incorporating the information of change in duty cycle (Δ D) and change in input voltage (Δ V). A mathematical expression is given to define the drift-free criterion and the threshold is determined by the Lambert W function with respect to the dynamic EN50530 test standard. Experimental results under different scenarios are presented to validate the advantages of the presented method in terms of the tracking efficiency and drift-free characteristic. [ABSTRACT FROM AUTHOR]

Due to dust, structural interfering from surrounding buildings or trees, partial shading conditions (PSCs) are frequently occurred in photovoltaic (PV) arrays, which affects the generated power and system reliability significantly. Under PSCs, PV arrays exhibit multiple local maximum power points (LMPPs), which make the conventional maximum power point tracking (MPPT) algorithms difficult to quickly allocate the optimal operating point with the maximum output power. In order to solve this issue, a novel power-increment based global MPPT (GMPPT) algorithm is proposed by combining the voltage line, the load line, and the power line altogether in determining the tracking direction and the step size. The proposed algorithm retains the advantages of the conventional power incremental based GMPPT technique. Moreover, it can realize a successful convergence to the GMPP under any pattern of PSC, which is difficult to accomplish for some GMPPT algorithms. It simplifies the control implementation since it is not necessary to know exactly the internal connection of the PV array for the practical implementation of the algorithm. Furthermore, the proposed algorithm shows improved tracking speed and higher accuracy than other GMPPT techniques. It directly regulates the duty-cycle of the power interface rather than the output power command. Thus, the circuit design becomes easier. Finally, various partial shading scenarios are evaluated experimentally in order to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Partial shading brings many serious problems in the solar photovoltaic system (SPV) such as the significant reduction in power harvest, hot spots, and the emergence of the multiple maximum power points (MPPs). This paper presents a bidirectional flyback converter (BFC) based isolated-port differential power processing (DPP) architecture at the submodule level. Bidirectional flyback converters (BFCs) are designed for submodules with both discontinuous condition mode (DCM) and continuous condition model (CCM) modes for light-load and heavy-load conditions to improve the efficiency. The voltage equalization with open-loop control is adopted for each BFC, this control method keeps the voltage in primary and secondary of the BFCs equal and it does not require additional voltage or current sensors. It’s simple, easy-to-implement and well suited for low-cost integrated hardware scheme. Both simulation and experimental results for an isolated-port DPP regulated 72-cells photovoltaic (PV) module under various partial shading scenarios were provided. It shows that this structure can distinctly mitigate the energy loss in a PV system, increase output power harvest, and achieve high efficiency under partial shading condition. The measured efficiency with the isolated-port DPP structure was 90.23% under severe shading condition. The measured output power improvement under severe mismatch condition was high up to 43.1%. [ABSTRACT FROM AUTHOR]

The output power of long strings of photovoltaic (PV) modules are vulnerable to the effect of mismatching and partial shading among different level PV elements such as cells, sub-modules and modules. In this paper, a sub-module synchronous buck converter (SBC) with the distributed maximum power point tracking (DMPPT) control is presented in order to achieve optimal output power of the PV module, low system cost, and high efficiency even under partial shading conditions. Main shading patterns in a PV module are classified and their typical characteristics are illustrated. In order to improve the efficiency, a series-connected DC optimizer structure is implemented and a two-switch synchronous buck converter is delicately designed for each sub-module. A two-step perturb & observe based MPPT algorithm is adopted: firstly, a coarse tracking is implemented with large step size in order to improve the tracking speed and followed by a refined tracking process with a small step size with aim to minimizing the static oscillations. Furthermore, a bypass mode is triggered in order to maximize the system efficiency when no mismatch among sub-modules is detected. In the proposed sub-module DMPPT PV system, only the output voltage is sampled, which reduces the current sensor and simplifies the implementation difficulty. A PV system with the proposed sub-module DMPPT algorithm and SBC power interface was built in Matlab/Simulink. Main simulation results were provided for various shading patterns and working scenarios. A 100 W low-cost and high efficiency sub-module integrated synchronous buck converter was designed. The experimental measured efficiency of the SBC was high up to 98.7 % . By comparing the actual power yield under shading conditions, an average 27.55 % output power improvement was achieved with the proposed sub-module DMPPT algorithm. [ABSTRACT FROM AUTHOR]

Solar forecasting is a crucial and cost-effective tool for better utilization of solar energy for smart environment design. Artificial intelligence (AI) technologies, such as machine learning (ML) and deep learning (DL), have gained great popularity and been widely applied in solar forecasting in recent years. However, conventional AI-based forecasting methods suffer from high variability and stochasticity of solar irradiation, making unreliable predictions due to heterogeneous solar resources. Moreover, the training process of DL models is less flexible and requires immense data. Even for a well-trained model, it can still yield deteriorated performances on other datasets of varying data distributions. To tackle the deficiencies of AI forecasting models, we present a flexible distributed solar forecasting framework based on a novel spatial and temporal attention-based neural network (STANN) in conjunction with federated learning (FL) technique, considering multi-horizon forecasting scenario from 5–30 min. The STANN model consists of a feature extractor and a forecaster, which can be respectively trained on various local datasets for better localization, and updated to further improve forecasting accuracy through global parameter aggregation under the proposed framework without data gathering. We evaluate effectiveness of the proposed method by conducting extensive experiments on real-world datasets and compare it to other popular forecasting models. The results demonstrate that our approach outperforms the other benchmarks with higher forecasting accuracy for all forecast horizons and better generalization on various datasets, achieving the highest forecast skill of 28.83% at 30 min horizon and an improvement of 11.2% compared with the centralized, localized, and conventional FL training methods. • Data heterogeneity affects solar forecasting performance at different locations. • Spatial and temporal attentions improve both feature extraction and forecasting accuracy. • The proposed framework localizes the feature extractors, while collaboratively training the forecasters in a federated way. • Ten real-world datasets collected at different locations are rendered for training. • Four training strategies are compared and the proposed one outperforms the others. [ABSTRACT FROM AUTHOR]

For Fuel Cell Electric Vehicles, DC-DC power converters are essential to provide energy storage buffers between fuel cell stacks and the traction system because fuel cells show characteristics of low-voltage high-current output and wide output voltage variation. This paper presents a hybrid-mode two-phase interleaved boost converter for fuel cell electric vehicle application in order to improve the power density, minimize the input current ripple, and enhance the system efficiency. Two operation modes are adopted in the practical design: mode I and mode II are used with each boost converter operating in continuous conduction mode and discontinuous conduction mode. The operation, design and control of the interleaved boost converter for different operating modes are discussed with their equivalent circuits. The boundary conditions are distinguished with respect to switching duty ratio and load conditions. Transitions between continuous conduction mode and discontinuous conduction mode are illustrated for the whole duty ratio range. The expressions for inductor current ripple, input current ripple and output voltage ripple are derived and verified by simulation and experimental tests. The efficiency and power density improvements are illustrated to verify the effectiveness of the proposed design scheme. [ABSTRACT FROM AUTHOR]

Due to the intermittent nature of the renewable energy sources including photovoltaic and wind energy, the energy storage systems are essential to stabilize dc bus voltage. Considering the discharge depth of super-capacitors and energy-storage batteries, the bidirectional isolated power interface will operate for a wide range of voltage and power. This study focuses on in-depth analysis of the dual-active-bridge dc–dc converter that is controlled by the dual-phase-shift scheme to improve the conversion efficiency in distributed power system. The power flow of each operating mode with dual-phase-shift control is characterized based on a detailed analysis of the effects of “minor parameters”, including the deadtime and power device voltage drops. The complete output power plane of the dual-active-bridge converter with dual-phase-shift control is obtained and compared with experimental results. The optimal operating mode is determined according to the practical output power range and the power flow characteristics. Experimental evaluation shows the effectiveness of the proposed power flow model with dual-phase-shift control and significant efficiency improvement using the optimal mode of dual-phase-shift compared with the conventional phase shift control. [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]

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]