Evaluation of the Performances of the First Grid-Connected Photovoltaic System in Sénégal

This document presents the evaluation and the monitoring of the performances of the first grid-connected photovoltaic system installed in the Center of Studies and Researches on the Renewable Energies (CERER) inaugurated on December 4th, 2012 by the governmental authorities of Senegal and Tenerife. This mini power plant of 3.15 kWc is a perfect example of the political will of the government which is to reduce the production cost of the electricity, with the diversification of the sources of production, and the greater use of the other sources such as the natural gas, the coal, the renewable energies. The evaluation of the performances of the installation is realized by using the indicators of efficiency and performance as the photovoltaic surface yield, the ratio of photovoltaic performance, the photovoltaic specific yield, and the losses of captures. The obtained results show that a big part of the energy shone during the period of observation was not able to be used further to circumstances such as the losses of conductivity, the heat losses or for example the defects on components. The analysis also shows that a large part of the produced energy is not injected because of the dilapidation of the network, the defects of landing but especially one disjunction sees frequently at the level of the point of injection.

Performance Assessment of Islanding Detection for Mul-ti-inverter Grid-connected Photovoltaic Systems

Islanding detection is an essential function for safety and reliability in grid-connected Distributed Generation Systems (DGS). Passive and active islanding detection methods have been analyzed in literature considering DGS with only one inverter connected to the utility. With the big scale application of photovoltaic (PV) power systems, islanding detection technology of multi-inverter DGS has been paid more attention. This paper analyzes the performance of diverse islanding detection methods in multiple inverters grid-connected PV systems. Non-Detection Zones (NDZ) of multi-inverter systems in a load parameter space are used as analytical tool. The paper provides guidance for the islanding detection design in multiple grid-connected inverters.

Design of Grid-Connected Photovoltaic System

This paper presents a grid connected photovoltaic system (PV) with a proposed high voltage conversion ratio DC-DC converter which steps up the variable low input voltages of photovoltaic module to the required DC link voltage. This voltage is applied to an H-bridge inverter which converts DC voltage into AC voltage and a low pass filter is used to filter the output. By adjusting the duty ratio of switches in DC-DC converter, the magnitude of inverter’s output voltage is controlled. The frequency and phase synchronization are ensured by a feedback signal taken from the grid. In this way, inverter is synchronized and connected with the grid to meet the energy demand. The PV system has been designed and simulated.

Combined Active Islanding Detection Method for Grid-connected Photovoltaic System

Unintentional islanding phenomenon has been one of the most important problems of gridconnected photovoltaic inverters. To prevent this phenomenon, all kinds of anti-islanding methods have been discussed. This paper presents a combined active islanding detection method, which consists of active frequency drift method and automatic phase-shift method. The traditional active anti-islanding methods of grid-connected PV inverters bear nondetection zone possibilities for certain paralleled RLC loads. The combined method shows islanding detection ability effectively, and it can eliminate nondetection zones even in the worst case conditions. Simulation in different load conditions is performed for verification.

Comparative Analysis of the Methods Used for Active Power Filtering in a Grid-Connected Photovoltaic System

This paper presents a comparison of the results obtained from the integration of the photovoltaic system to the electrical grid through the Active Power Filter.The innovative aspect of this article consists of the elaboration of 4 models in Matlab/Simulink for 4 methods of control of the Active Power Filter introduced between the photovoltaic system and the alternating current grid and the highlighting of the performances obtained regarding the quality and quantity of electricity transferred for each control method in part.Following the analysis of the results,it was found that by using the Indirect Control(CI)method of the Active Power Filter,the best results are obtained THDu=3.24%,THDi=2.46%if the photovoltaic system produces a larger amount of energy than the nonlinear load,and by using the methods of control of the Active Power Filter Synchronous Reference Frame(DQ)and Instantaneous Power(PQ)the best results are obtained:THDu=3.22%,THDi=5.26%for the method(DQ)and THDu=3.41%,THDi=5.17%for the method(PQ)if the photovoltaic system produces a smaller amount of energy than the nonlinear load.

Evaluation of Grid-Connected Photovoltaic Plants Based on Clustering Methods

Photovoltaic(PV)systems are electric power systems designed to sup-ply usable solar power by means of photovoltaics,which is the conversion of light into electricity using semiconducting materials.PV systems have gained much attention and are a very attractive energy resource nowadays.The substantial advantage of PV systems is the usage of the most abundant and free energy from the sun.PV systems play an important role in reducing feeder losses,improving voltage profiles and providing ancillary services to local loads.However,large PV grid-connected systems may have a destructive impact on the stability of the elec-tric grid.This is due to thefluctuations of the output AC power generated from the PV systems according to the variations in the solar energy levels.Thus,the elec-trical distribution system with high penetration of PV systems is subject to perfor-mance degradation and instabilities.For that,this project attempts to enhance the integration process of PV systems into electrical grids by analyzing the impact of installing grid-connected PV plants.To accomplish this,an indicative representa-tion of solar irradiation datasets is used for planning and powerflow studies of the electric network prior to PV systems installation.Those datasets contain lengthy historical observations of solar energy data,that requires extensive analysis and simulations.To overcome that the lengthy historical datasets are reduced and clus-tered while preserving the original data characteristics.The resultant clusters can be utilized in the planning stage and simulation studies.Accordingly,studies related to PV systems integration into the electric grid are conducted in an efficient manner,avoiding computing resources and processing times with easier and practical implementation.

Progress of semitransparent emerging photovoltaics for building integrated applications

With the rapid development of emerging photovoltaics technology in recent years,the application of building-integrated photovoltaics(BIPVs)has attracted the research interest of photovoltaic communities.To meet the practical application requirements of BIPVs,in addition to the evaluation indicator of power conversion efficiency(PCE),other key performance indicators such as heat-insulating ability,average visible light transmittance(AVT),color properties,and integrability are equally important.The traditional Si-based photovoltaic technology is typically limited by its opaque properties for application scenarios where transparency is required.The emerging PV technologies,such as organic and perovskite photovoltaics are promising candidates for BIPV applications,owing to their advantages such as high PCE,high AVT,and tunable properties.At present,the PCE of semitransparent perovskite solar cells(ST-PSCs)has attained 14%with AVT of 22–25%;for semitransparent organic solar cells(ST-OSCs),the PCE reached 13%with AVT of almost 40%.In this review article,we summarize recent advances in material selection,optical engineering,and device architecture design for high-performance semitransparent emerging PV devices,and discuss the application of optical modeling,as well as the challenges of commercializing these semitransparent solar cells for building-integrated applications.

Flexibility potential of Cs_(2)BX_(6)(B=Hf,Sn,Pt,Zr,Ti;X=I,Br,Cl)with application in photovoltaic devices and radiation detectors

As interest in double perovskites is growing,especially in applications like photovoltaic devices,understanding their mechanical properties is vital for device durability.Despite extensive exploration of structure and optical properties,research on mechanical aspects is limited.This article builds a vacancyordered double perovskite model,employing first-principles calculations to analyze mechanical,bonding,electronic,and optical properties.Results show Cs_(2)Hfl_(6),Cs_(2)SnBr_(6),Cs_(2)SnI_(6),and Cs_(2)PtBr_(6)have Young's moduli below 13 GPa,indicating flexibility.Geometric parameters explain flexibility variations with the changes of B and X site composition.Bonding characteristic exploration reveals the influence of B and X site electronegativity on mechanical strength.Cs_(2)SnBr_(6)and Cs_(2)PtBr_(6)are suitable for solar cells,while Cs_(2)HfI_(6)and Cs_(2)TiCl_(6)show potential for semi-transparent solar cells.Optical property calculations highlight the high light absorption coefficients of up to 3.5×10^(5) cm^(-1)for Cs_(2)HfI_(6)and Cs_(2)TiCl_(6).Solar cell simulation shows Cs_(2)PtBr_(6)achieves 22.4%of conversion effciency.Cs_(2)ZrCl_(6)holds promise for ionizing radiation detection with its 3.68 eV bandgap and high absorption coefficient.Vacancy-ordered double perovskites offer superior flexibility,providing valuable insights for designing stable and flexible devices.This understanding enhances the development of functional devices based on these perovskites,especially for applications requiring high stability and flexibility.

Recent advances in two-dimensional photovoltaic devices

Two-dimensional(2D)materials have attracted tremendous interest in view of the outstanding optoelectronic properties,showing new possibilities for future photovoltaic devices toward high performance,high specific power and flexibility.In recent years,substantial works have focused on 2D photovoltaic devices,and great progress has been achieved.Here,we present the review of recent advances in 2D photovoltaic devices,focusing on 2D-material-based Schottky junctions,homojunctions,2D−2D heterojunctions,2D−3D heterojunctions,and bulk photovoltaic effect devices.Furthermore,advanced strategies for improving the photovoltaic performances are demonstrated in detail.Finally,conclusions and outlooks are delivered,providing a guideline for the further development of 2D photovoltaic devices.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Enhancement of vertical phase separation in sequentially deposited organic photovoltaics through the independent processing of additives

Herein,the impact of the independent control of processing additives on vertical phase separation in sequentially deposited (SD) organic photovoltaics (OPVs) and its subsequent effects on charge carrier kinetics at the electron donor-acceptor interface are investigated.The film morphology exhibits notable variations,significantly depending on the layer to which 1,8-diiodooctane (DIO) was applied.Grazing incidence wide-angle X-ray scattering analysis reveals distinctly separated donor/acceptor phases and vertical crystallinity details in SD films.Time-of-flight secondary ion mass spectrometry analysis is employed to obtain component distributions in diverse vertical phase structures of SD films depending on additive control.In addition,nanosecond transient absorption spectroscopy shows that DIO control significantly affects the dynamics of separated charges in SD films.In SD OPVs,DIO appears to act through distinct mechanisms with minimal restriction,depending on the applied layer.This study emphasizes the significance of morphological optimization in improving device performance and underscores the importance of independent additive control in the advancement of OPV technology.

Forestvoltaics,Floatovoltaics and Building Applied Photovoltaics(BAPV)Potential for a University Campus

The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.

Semitransparent organic photovoltaics enabled by transparent p-type inorganic semiconductor and near-infrared acceptor

Semitransparent organic photovoltaics(STOPVs)have gained wide attention owing to their promising applications in building-integrated photovoltaics,agrivoltaics,and floating photovoltaics.Organic semiconductors with high charge carrier mobility usually have planar and conjugated structures,thereby showing strong absorption in visible region.In this work,a new concept of incorporating transparent inorganic semiconductors is proposed for high-performance STOPVs.Copper(I)thiocyanate(CuSCN)is a visible-transparent inorganic semiconductor with an ionization potential of 5.45 eV and high hole mobility.The transparency of CuSCN benefits high average visible transmittance(AVT)of STOPVs.The energy levels of CuSCN as donor match those of near-infrared small molecule acceptor BTP-eC9,and the formed heterojunction exhibits an ability of exciton dissociation.High mobility of CuSCN contributes to a more favorable charge transport channel and suppresses charge recombination.The control STOPVs based on PM6/BTP-eC9 exhibit an AVT of 19.0%with a power conversion efficiency(PCE)of 12.7%.Partial replacement of PM6 with CuSCN leads to a 63%increase in transmittance,resulting in a higher AVT of 30.9%and a comparable PCE of 10.8%.

Electro-Optical Model of Soiling Effects on Photovoltaic Panels and Performance Implications

In this paper,a detailed model of a photovoltaic(PV)panel is used to study the accumulation of dust on solar panels.The presence of dust diminishes the incident light intensity penetrating the panel’s cover glass,as it increases the reflection of light by particles.This phenomenon,commonly known as the“soiling effect”,presents a significant challenge to PV systems on a global scale.Two basic models of the equivalent circuits of a solar cell can be found,namely the single-diode model and the two-diode models.The limitation of efficiency data in manufacturers’datasheets has encouraged us to develop an equivalent electrical model that is efficient under dust conditions,integrated with optical transmittance considerations to investigate the soiling effect.The proposed approach is based on the use of experimental current-voltage(I-V)characteristics with simulated data using MATLAB/Simulink.Our research outcomes underscores the feasibility of accurately quantifying the reduction in energy production resulting from soiling by assessing the optical transmittance of accumulated dust on the surface of PV glass.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.

A novel cascaded H-bridge photovoltaic inverter with flexible arc suppression function

This paper presents a novel approach that simultaneously enables photovoltaic(PV)inversion and flexible arc suppression during single-phase grounding faults.Inverters compensate for ground currents through an arc-elimination function,while outputting a PV direct current(DC)power supply.This method effectively reduces the residual grounding current.To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models,an adaptive fuzzy neural network imitating a sliding mode controller was designed.An online adaptive adjustment law for network parameters was developed,based on the Lyapunov stability theorem,to improve the robustness of the inverter to fault and connection locations.Furthermore,a new arc-suppression control exit strategy is proposed to allow a zerosequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time.Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults.Compared to other methods,the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.

Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles

The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO2 emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.

Analysis and Modeling of Time Output Characteristics for Distributed Photovoltaic and Energy Storage

Due to the unpredictable output characteristics of distributed photovoltaics,their integration into the grid can lead to voltage fluctuations within the regional power grid.Therefore,the development of spatial-temporal coordination and optimization control methods for distributed photovoltaics and energy storage systems is of utmost importance in various scenarios.This paper approaches the issue from the perspective of spatiotemporal forecasting of distributed photovoltaic(PV)generation and proposes a Temporal Convolutional-Long Short-Term Memory prediction model that combines Temporal Convolutional Networks(TCN)and Long Short-Term Memory(LSTM).To begin with,an analysis of the spatiotemporal distribution patterns of PV generation is conducted,and outlier data is handled using the 3σ rule.Subsequently,a novel approach that combines temporal convolution and LSTM networks is introduced,with TCN extracting spatial features and LSTM capturing temporal features.Finally,a real spatiotemporal dataset from Gansu,China,is established to compare the performance of the proposed network against other models.The results demonstrate that the model presented in this paper exhibits the highest predictive accuracy,with a single-step Mean Absolute Error(MAE)of 1.782 and an average Root Mean Square Error(RMSE)of 3.72 for multi-step predictions.