Real Photovoltaic System Research Articles

High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution

Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-processing, but their resolution is too coarse for applications such as local congestion management. In this paper we introduce computing methods for multi-site PV forecasting, which exploit the intuition that PV systems provide a dense network of simple weather stations. These methods rely entirely on production data and address the real-life challenges that come with them, such as noise and gaps. Our approach builds on graph signal processing for signal reconstruction and for forecasting with a linear, spatio-temporal autoregressive (ST-AR) model. It also introduces a data-driven clear-sky production estimation for normalization. The proposed framework was evaluated over one year on both 303 real PV systems under commercial monitoring across Switzerland, and 1000 simulated ones based on high-resolution weather data. The results demonstrate the performance and robustness of the approach: with gaps of four hours on average in the input data, the average daytime NRMSE over a six-hour forecasting horizon (in 15 min steps) and over all systems is 13.8% and 9% for the real and synthetic data sets, respectively.

Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities

The demand for renewable energy generation, especially photovoltaic (PV) power generation, has been growing over the past few years. However, the amount of generated energy by PV systems is highly dependent on weather conditions. Therefore, accurate forecasting of generated PV power is of importance for large-scale deployment of PV systems. Recently, machine learning (ML) methods have been widely used for PV power generation forecasting. A variety of these techniques, including artificial neural networks (ANNs), ridge regression, K-nearest neighbour (kNN) regression, decision trees, support vector regressions (SVRs) have been applied for this purpose and achieved good performance. In this paper, we briefly review the most recent ML techniques for PV energy generation forecasting and propose a new regression technique to automatically predict a PV system’s output based on historical input parameters. More specifically, the proposed loss function is a combination of three well-known loss functions: Correntropy, Absolute and Square Loss which encourages robustness and generalization jointly. We then integrate the proposed objective function into a Deep Learning model to predict a PV system’s output. By doing so, both the coefficients of loss functions and weight parameters of the ANN are learned jointly via back propagation. We investigate the effectiveness of the proposed method through comprehensive experiments on real data recorded by a real PV system. The experimental results confirm that our method outperforms the state-of-the-art ML methods for PV energy generation forecasting.

On‐site detection of bypass circuit opening failure in photovoltaic array under power generation operation

AbstractTo ensure the long‐term reliability of photovoltaic systems (PVSs), periodical inspections are necessary. Despite the risk of severe temperature rise, bypass circuit open‐circuit (BPC‐OC) failure has attracted low research interest compared with other types of failure. This paper presents the pulsed light irradiation (PLI) method for robust BPC‐OC failure detection that eliminates the need to switch off the power generation operation of the PVS. The proposed method detects the BPC‐OC failure of the solar cell string by measuring the modulated current induced by local PLI. Electrical circuit simulations as well as indoor and outdoor experiments are performed to verify the performance of the proposed method. Results of the outdoor experiment show that the PLI method performs well in a real PVS under power generation operation. Finally, the advantages and disadvantages of the proposed method are summarized.

Global Techno-Economic Performance of Bifacial and Tracking Photovoltaic Systems

Summary This work presents a worldwide analysis on the yield potential and cost effectiveness of photovoltaic farms composed of monofacial fixed-tilt and single/dual (1T/2T) tracker installations, as well as their bifacial counterparts. Our approach starts by estimating the irradiance reaching both the front and rear surfaces of the modules for the different system designs (validated based on data from real photovoltaic systems and results from the literature) to estimate their energy production. Subsequently, the overall system cost during their 25-year lifetime is factored in, and the levelized cost of electricity (LCOE) is obtained. The results reveal that bifacial-1T installations increase energy yield by 35% and reach the lowest LCOE for the majority of the world (93.1% of the land area). Although dual-axis trackers achieve the highest energy generation, their costs are still too high and are therefore not as cost effective. Sensitivity analyses are also provided to show the general robustness of our findings.

Nonlinear Control for Positive Output Super Lift Luo Converter in Stand Alone Photovoltaic System

This paper proposes a stand-alone photovoltaic (PV) system based on a DC-DC positive output super lift Luo (POSLL) converter. A conventional sliding mode control, a sliding mode controller using a simple sign function and a linear controller using proportional integrator (PI) are used for the control of the PV panel voltage and POSLL converter inductor current and these methods are compared together. The POSLL converter is a DC-DC converter with higher voltage gain compared to other conventional DC-DC converters, and has a good voltage regulation with a simple structure. The stability and accessibility of the proposed nonlinear controls are investigated widely. The internal dynamics of the proposed closed-loop control systems are also investiged. A practical implementation of the system on a hardware setup is performed using a low cost Discovery real time digital control platform. The experimental and simulation results demonstrate the validity of the proposed control schemes over a stand-alone real photovoltaic system.

Estimating Solar Insolation and Power Generation of Photovoltaic Systems Using Previous Day Weather Data

Day‐ahead predictions of solar insolation are useful for forecasting the energy production of photovoltaic (PV) systems attached to buildings, and accurate forecasts are essential for operational efficiency and trading markets. In this study, a multilayer feed‐forward neural network‐based model that predicts the next day’s solar insolation by taking into consideration the weather conditions of the present day was proposed. The proposed insolation model was employed to estimate the energy production of a real PV system located in South Korea. Validation research was performed by comparing the model’s estimated energy production with the measured energy production data collected during the PV system operation. The accuracy indices for the optimal model, which included the root mean squared error, mean bias error, and mean absolute error, were 1.43 kWh/m2/day, −0.09 kWh/m2/day, and 1.15 kWh/m2/day, respectively. These values indicate that the proposed model is capable of producing reasonable insolation predictions; however, additional work is needed to achieve accurate estimates for energy trading.

The Dutch PV portal 2.0: An online photovoltaic performance modeling environment for the Netherlands

This paper describes the core model that lies behind an online modeling environment for photovoltaic (PV) energy generation in the Netherlands, called the Dutch PV Portal 2.0 (PVP 2.0). PVP 2.0 realizes three functionalities: (i) a real-time system efficiency breakdown figure, (ii) an estimate of national solar electricity production, and (iii) an economic analysis for small-scale to large scale PV systems. The unique and novel aspects of this website are the dynamically updated climate database, the rainfall-dependent soiling loss calculation, and the orientation-dependent inverter sizing factor. This paper also justifies the PVP 2.0 capabilities in large scale studies. First, the PVP 2.0 modeling approach was validated by yield comparison with 26 real PV systems distributed over the Netherlands. The validation resulted in −11% to +5.5% deviation from measured data. Then, a back-end sensitivity study found that a rain-free summer in the Netherlands results in an AC energy loss of 3.4% in that period, while a change in wind speed or ambient temperature could lead to losses around 2–4.5 GWh/year (0.58%–1.16%) on province scale. The core of the approach presented in this paper can be used to develop similar websites for other countries of interest with adapted add-ons depending on the target climate condition. Such study tools could eventually provide more quantitative insights about the impact of climate change (by applying probable scenarios) on the renewable energy production of the World.

Photovoltaic emulator based on PV simulator RT implementation using XSG tools for an FPGA control: Theory and experimentation

This paper presents an efficient field-programmable gate array (FPGA) implementation method for a photovoltaic (PV) simulator based on two-diode model applied to control a PV emulator. The hardware set up allows to repeat the real PV system behavior in the laboratory regardless of external climatic conditions change. The proposed approach has been designed through Xilinx System Generator (XSG) tools and MATLAB/Simulink environment and verified across cosimulation method. A real-time test bench is built based on the implemented PV simulator with a closed loop control using proportional integral (PI) regulator, a direct current/direct current (DC/DC) buck converter and a resistive load. Experimental results are in agreement compared with simulation ones and prove the high accuracy and efficiency of the proposed implementation method for allowing a good emulation of PV characteristics. From some experiments, the development of PV emulator constitutes an important challenge task in the PV energy field.

Simple and efficient approach to detect and diagnose electrical faults and partial shading in photovoltaic systems

Photovoltaic (PV) systems are continuously exposed to many potential faults, causing significant power generation losses. Accurate fault detection procedures are crucial to ensure the reliable operating condition. This paper presents simple, efficient and easy to implement approach to detect the most common failures, due to short-circuit (SC) and open-circuit (OC) faults, inverter disconnection (ID) and partial shading (PS). The proposed procedure introduces three indicators namely, current indicator α, voltage indicator β and power indicator γ with the main function to distinguish healthy and faulty operating conditions. To this end, single-diode model is adopted to generate a trusted PV model in combination with the best-so-far artificial bees colony (ABC) optimization algorithm in order to extract the unknown model parameters. Subsequently, the maximum power point (MPP) coordinates are estimated to mimic the real operating PV system. Measured and predicted MPP coordinates allow the calculation of current, voltage and power indicators. For each indicator, an upper and lower thresholds has been established by trial and error. The computed value of each indicator will reveal the healthy or faulty operation of the PV system when it is within or outside the predefined threshold respectively. An experimental evaluation is presented by using the monitored data of the 3.2 kWp grid-connected PV system located at the roof of the Renewable Energy Development Centre (CDER), Algeria.

Low-Cost Datalogger Intended for Remote Monitoring of Solar Photovoltaic Standalone Systems Based on Arduino™

A low-cost datalogger intended for standalone photovoltaic (PV) systems in developing countries was designed by employing open source software and hardware. The low-cost datalogger is capable of measuring electrical and meteorological parameters meeting the accuracy requirements established by the International Electro-technical Commission (IEC) standard for the PV monitoring systems. The new datalogger allows the installation of the monitoring system in areas deprived of telecommunications networks, storing data in SD card, and requiring minimal maintenance. A real standalone PV system similar to those employed in developing countries was installed at the IMDEA Water Institute facilities (Madrid, Spain) for testing and validating the new low-cost datalogger under real conditions. The results demonstrated compliance with the IEC standard, monitoring all of the requested parameters with high accuracy and low power consumption.

An improved and comprehensive mathematical model for solar photovoltaic modules under real operating conditions

This paper presents an improved and comprehensive mathematical model for photovoltaic (PV) device, developed in Matlab based on the basic circuit equation of a solar cell with the basic data provided by the manufacturer. The effects of solar radiation, ambient temperature and cell types, including monocrystalline and polycrystalline silicon are fully considered. First, based on the developed model, the characteristics of two types of PV modules has been obtained and verified by other widely used models. Results show that the model can produce the characteristic curves quickly and accurately because initial values assumption and multiple iterations can be avoided. This model is further validated through comparisons between simulated and the measured curves from a real PV system, and very good agreement is achieved between each other, with relative errors at 0.43% and 0.36% for two types of PV. Finally, this model is employed to simulate the performance of a PV system under actual typical cases. The relative error between the simulated and measured electricity on a sunny and cloudy day is 0.60% and −1.08%, respectively, demonstrating the effectiveness of the proposed method.

Optimal probabilistic planning of passive harmonic filters in distribution networks with high penetration of photovoltaic generation

In recent years, distribution networks have been increasingly affected by the random nature of harmonic sources introduced by nonlinear load and renewable energy sources (RES) such as photovoltaic (PV) systems. This paper presents an approach based on Genetic Algorithm (GA) and Monte-Carlo Simulation (MCS) for the optimal planning of single-tuned passive harmonic filters (PHFs) in a distribution network. The resistance and inductance of the lines within the network are modeled by frequency dependent characteristics. The probabilistic characteristics of the load and PV system currents are also considered for optimal planning of PHFs. In our optimization model, the objective function minimizes the total PHF installation cost and the energy losses, by considering the total harmonic distortion (THD) of bus voltages and maximum capacity of PHF as constraints. The proposed method is validated by a simulation study using an unbalanced three-phase real distribution system. An advantage of this method over most of the conventional approaches is that both harmonic current magnitude and phase angle of real PV systems are taken into account. Numerical results show the applicability and effectiveness of the proposed method.

VERIFICATION OF IEEE STANDARDS 929-2000 AND 1547-2003 TO A SMALL PHOTOVOLTAIC SYSTEM CONNECTED TO BEER ELABD DISTRIBUTION GRID-NORTH SINAI-EGYPT

This paper studied the power quality of grid connected photovoltaic (PV) system by verification of IEEE standards 929-2000 and 1547-2003 for a small PV system connected to a grid. For practical considerations, the PV system data extracted from a real standalone PV system and the distribution grid is simulated based on real data extracted from North Sinai distribution network. The Suggested system is simulated under different climate conditions to get real simulation of solar irradiation. A 10 KW grid connected PV system is modeled and simulated by using Matlab/Simulink software and the power quality parameters are studied under different levels of irradiance for the proposed system according to IEEE standards. System operated under normal and abnormal utility conditions. Results show a good compatibility with IEEE standards for subsystem proposed system in case of normal utility operation. In case of abnormal utility conditions, the PV system must island for protection issues.

Short-term photovoltaic solar power forecasting using a hybrid Wavelet-PSO-SVM model based on SCADA and Meteorological information

Abstract Photovoltaic (PV) solar power generation is always associated with uncertainties due to solar irradiance and other weather parameters intermittency. This creates a huge barrier in integrating solar power into the grid and biases power industries against deploying PV systems. Thus accurate short-term forecasts are important to efficiently integrate PV systems into the grid. This paper proposes a hybrid forecasting model combining wavelet transform, particle swarm optimization and support vector machine (Hybrid WT-PSO-SVM) for short-term (one-day-ahead) generation power forecasting of a real microgrid PV system. The model is developed by incorporating the interactions of the PV system Supervisory Control and Data Acquisition (SCADA) actual power record with Numerical Weather Prediction (NWP) meteorological data for one year with a time-step of 1 h. In the proposed model, the wavelet is employed to have a considerable impact on ill-behaved meteorological and SCADA data, and SVM techniques map the NWP meteorological variables and SCADA solar power nonlinear relationship in a better way. The PSO is used to optimize the parameters of the SVM to achieve a higher forecasting accuracy. The forecasting accuracy of the proposed model has been compared with other seven forecasting strategies and reveals outperformed performance with respect to forecasting accuracy improvement.

The effect of shading on photovoltaic solar panels

A modelling description of photovoltaic (PV) modules in a PSPICE environment is presented. To validate the simulation model, a lab prototype is used to create similar conditions as those existing in real photovoltaic systems. The effects of partial shading of solar cell strings and temperature on the performance of various PV modules are analyzed. The simulation results show a very good agreement with those obtained experimentally in similar conditions, either in lab, at Lisbon University, and under outdoor testing in Sweden, using PV solar collectors manufactured by Solarus Sunpower AB. The potential of the simulation analysis is highlighted as a flexible and powerful tool for the design of new and more competitive PV module configurations for the collectors in solar panels.

Approach for locating and tracking the maximum power point of a photovoltaic generator using a centered differentiation method

Abstract In this study, we propose a new experimental method for the real-time estimation of the slope at a generic point on the P – V curve for a photovoltaic generator. The slope is obtained using a centered differentiation method, but we consider that the solar irradiation can change during readings, so the method is improved. The novel feature of this method is that we obtain readings at three consecutive times in two different places (two on the left-hand side and one on the right-hand side of the point where the slope should be calculated), instead of obtaining readings at two consecutive times in two different places like the standard centered differentiation method. We performed an analysis and used the proposed method to delimit the error achieved. A mathematical calculation was also conducted based on a standard photovoltaic generator to evaluate the error with the new method. In the case of constant solar irradiance, the results were the same as those with the standard centered differentiation method. The proposed method is applicable to real photovoltaic systems and it can be used to locate and track the position of the maximum power point.

A new maximum power point method based on a sliding mode approach for solar energy harvesting

This paper presents a photovoltaic (PV) system with a maximum power point tracking (MPPT) facility. The goal of this work is to maximize power extraction from the photovoltaic generator (PVG). This goal is achieved using a sliding mode controller (SMC) that drives a boost converter connected between the PVG and the load. The system is modeled and tested under MATLAB/SIMULINK environment. In simulation, the sliding mode controller offers fast and accurate convergence to the maximum power operating point that outperforms the well-known perturbation and observation method (P&O). The sliding mode controller performance is evaluated during steady-state, against load varying and panel partial shadow (PS) disturbances. To confirm the above conclusion, a practical implementation of the maximum power point tracker based sliding mode controller on a hardware setup is performed on a dSPACE real time digital control platform. The data acquisition and the control system are conducted all around dSPACE 1104 controller board and its RTI environment. The experimental results demonstrate the validity of the proposed control scheme over a stand-alone real photovoltaic system.

Diseño e Implementación de un Sistema de Control estable basado en Lógica Borrosa para optimizar el rendimiento de un sistema de Generación Fotovoltaico

This paper presents a new control scheme for a standalone photovoltaic (PV) system based on a fuzzy-logic (FLC). The proposed control system provides good tracking for the optimal reference voltage, at which the maximum power generation is obtained. The photovoltaic system is connected to a load through a DC/DC boost converter. The FLC controller provides the appropriate duty cycle (D) to the DC/DC converter in order to get the maximum power from the PV system. A method for the stability analysis of the closed-loop system is also proposed. The stability analysis is based on the Lyapunov methods and is a semi-qualitative analysis because there is no closed loop system model available for the analytical analysis. Both simulation results and experimental tests on a real PV system show that the FLC provides good tracking for the maximum power point (MPP).Finally, the performance of the FLC on a real PV system consisting of a commercial solar panels Atersa model A55 is analyzed. To perform the experimental tests the proposed control strategy has been implemented on the dSPACE digital signal processor model DS1104. The experimental results demonstrate the good performance of the proposed FLC control scheme over a commercial photovoltaic system

A power and energy procedure in operating photovoltaic systems to quantify the losses according to the causes

Recently, after high feed-in tariffs in Italy, retroactive cuts in the energy payments have generated economic concern about several grid-connected photovoltaic (PV) systems with poor performance. In this paper the proposed procedure suggests some rules for determining the sources of losses and thus minimizing poor performance in the energy production. The on-site field inspection, the identification of the irradiance sensors, as close as possible the PV system, and the assessment of energy production are three preliminary steps which do not require experimental tests. The fourth step is to test the arrays of PV modules on-site. The fifth step is to test only the PV strings or single modules belonging to arrays with poor performance (e.g. mismatch of current–voltage curves). The sixth step is to use the thermo-graphic camera and the electroluminescence at the PV-module level. The seventh step is to monitor the DC racks of each inverter or the individual inverter, if equipped with only one Maximum Power Point Tracker (MPPT). Experimental results on real PV systems show the effectiveness of this procedure.

Power Quality in Low-Voltage Distribution Network with Distributed Generation

The aim of this work is to combine electromagnetic compatibility standardization and control strategy of low-voltage distributed generations in order to define possible impact of the generation unit on power quality at the point of common coupling with low-voltage distribution network. Selected relations between power quality indices and parameters as well as regulation characteristic of the distributed generation is discussed. Verification of predicted impact of the distributed generation on power quality is performed using a field-measurement case study of power quality behaviour in real photovoltaic system connected to low-voltage distribution network‥