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With the increase of the component number, the power stress distribution among differential power processing (DPP) converters, control implementation, system cost, and reliability become the most challenging issues for a practical photovoltaic (PV) DPP system. This article introduces an improved power-rating balance (IPRB) control for the PV-to-bus based DPP architecture that ensures each PV submodule operate at its true maximum power point (MPP) while achieving more balanced power stress distribution and higher reliability. Specifically, a submodule-level finite-state-machine-based MPP tracking is implemented to guarantee always maximum power yield, whereas a string-level power-rating balancing (PRB) control is adopted to balance the unit-maximum proceeded power by DPP converters based on the built power flow model with respect to the string current. A comprehensive comparison of advanced control strategies for PV-to-bus DPP architectures, including least power point tracking, voltage equalization (VE) based PRB control, and the proposed IPRB, has been carried out with the mission-profile-based reliability assessment under different partial shading scenarios. Component-failure-rate-based reliability analysis shows that the PV-to-bus DPP architecture with the proposed IPRB control can significantly improve the system reliability. Main simulation and experimental evaluations are carried out to verify the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

Maximum power point tracking (MPPT) is required in PV power systems for the highest solar energy harvest. This article proposes a self-tuning scheme to improve the MPPT performance in terms of high accuracy and speed. The scheme adopts the reinforcement learning (RL) and Beta parameter for the highest MPPT performance. The tracking speed and accuracy are significantly improved since the RL algorithm is enhanced for high convergence speed, meanwhile, the guiding variable $\beta$ is introduced to constrain the exploration space. Simulation and experimental test are applied to validate the superior performance of the proposed solution following the EN50530 dynamic test procedure. [ABSTRACT FROM AUTHOR]

• 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]

As the “brain” of the modern photovoltaic power systems, dc solid-state transformers (SSTs) are playing an increasing important role in integrating different photovoltaic modules, batteries, and supercapacitors. This paper aims at improving the conversion efficiency of dc SST for a wide operating range by minimizing the backflow power of the dc SST system. First, the mathematical model of the backflow power from both input and output sides of dc SST is obtained. Then, the penalty function is derived and an enhanced triple phase shift control (ETPS) strategy is proposed to minimize the backflow power for various transmission power and voltage conversion conditions. A comprehensive comparison of the proposed ETPS with other advanced control strategies was carried out through theoretical analysis and experimental tests. Main experimental results are illustrated to verify the effectiveness of the proposed method. [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]

Passing cloud results in rapid changes of irradiance. The intermittency of photovoltaic (PV) power output has drawn serious concern especially for utility-scale PV system. Consequently, power ramp-rate control (PRRC) has been introduced to avoid significant PV power fluctuations. PRRC is usually implemented either by curtailing active power output or implementing energy storage system (ESS). However, current active power curtailment cannot deal with the irradiance ramp-down fluctuations, and the high cost of the ESS is still hindering its extensive application. In this paper, two innovative PRRC strategies are presented, which utilize the short-term forecasting. The first solution does not require any ESS, during the power ramp-down event, the PV generation will be curtailed before the actual shading occurs. The second solution requires only one-quarter of the energy capacity of the conventional ESS control strategy. To provide the PV generation forecasts, a dynamic model based on spatio-temporal theory is formulated. The effectiveness of the proposed forecasting model and control strategies have been verified through experiment and case studies. [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]

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]

When the photovoltaic (PV) string is under the partial shading condition (PSC), the conventional maximum power point tracking (MPPT) techniques may fail to track the global maximum power point (GMPP). Although some global MPPT (GMPPT) techniques have been proposed, they may overlook the GMPP and fail to detect the PSC occurrence. Therefore, a novel GMPPT technique is proposed in this paper by modifying the conventional beta method. The proposed technique is more accurate than the previous techniques since it can guarantee that all the peaks in the $\beta$ range and never overlook the GMPP. Furthermore, the proposed technique can inherently detect the PSC occurrence without setting any additional threshold parameters or periodical interruption, which is simpler and more effective. In order to verify the advantages of the proposed technique, a prototype with buck-boost converter was constructed. For a fair comparison, two popular GMPPT techniques were also implemented and tested in the same prototype under various scenarios. The performance improvement with the proposed technique for different PSCs has been validated by both simulation and experimental results. [ABSTRACT FROM PUBLISHER]

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]

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]

In this study maximum power point tracking (MPPT) is applied to the photovoltaic (PV) system to harvest the maximum power output. The output power of the PV effect changes according to external solar irradiation and ambient temperature conditions. In the existing MPPT strategies, most of them only take variations in radiation level into account, rarely considering the impact of temperature changes. However, the temperature coefficients (TC) play an important role in the PV system, especially in applications where ambient temperature changes are relatively large. In this paper, an MPPT method is presented for a PV system that considers the temperature change by using variable universe fuzzy logic control (VUFLC). By considering the ambient temperature change in PV modules, the proposed control method can regulate the contraction and expansion factor of VUFLC, which eliminates the influence of temperature variability and improves the performance of MPPT, therefore achieving fast and accurate tracking control. The proposed method was evaluated for a PV module under different ambient conditions and its control performance is compared with other MPPT strategies by simulation and experimental results. [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]