Solar Photovoltaics Development in Nigeria: Drivers, Barriers, and Policies

Energy access is vital to a nation’s economic growth and its populace’s social well-being. Still, there is a lack of adequate energy in Nigeria, negatively affecting the country’s socio-economic development. Due to the inadequate energy supply, some manufacturing companies shut their operations, and most Nigerians now use backup generators (BUGs) with their attendant health hazards, environmental pollution, and global warming. The need for energy access and a sustainable energy supply through renewable energy (RE) resources necessitates adopting solar photovoltaics (PV) in Nigeria. Studies on Nigeria’s energy accessibility and sustainability are generally on RE development and a few on solar PV applications. This research covers the need for an in-depth analysis of the growth of solar PV in Nigeria, and the research question is: What factors promote or limit the adoption of solar photovoltaics in Nigeria? A method of Systematic Literature Review (SLR) and Thematic Analysis (TA) is employed for the analysis. The research findings are divided into drivers, barriers, and policies. Some identified factors promoting the adoption of solar PV are energy poverty and the urgency to improve electricity supply, the ease of its operation and maintenance, and the Nigerian government’s commitment to clean electricity supply with policy initiatives and increased awareness of solar PV applications. Conversely, some noticed factors mitigating the growth of solar PV are poor tariff systems, dual subsidies of electricity and petroleum, and lack of finance and economic incentives.

Smart Monitoring of Solar Photovoltaic Panels by the Approach of Machine Learning

The exploitation of renewable energy has become a pressing task due to climate change and the recent energy crisis caused by regional conflicts.This has further accelerated the rapid development of the global photovoltaic(PV)market,thereby making the management and maintenance of solar photovoltaic(SPV)panels a new area of business as neglecting it may lead to significant financial losses and failure to combat climate change and the energy crisis.SPV panels face many risks that may degrade their power generation performance,damage their structures,or even cause the complete loss of their power generation capacity during their long service life.It is hoped that these problems can be identified and resolved as soon as possible.However,this is a challenging task as a solar power plant(SPP)may contain hundreds even thousands of SPV panels.To provide a potential solution for this issue,a smart drone-based SPV panel condition monitoring(CM)technique has been studied in this paper.In the study,the U-Net neural network(UNNN),which is ideal for undertaking image segmentation tasks and good at handling small sample size problem,is adopted to automatically create mask images from the collected true color thermal infrared images.The support vector machine(SVM),which performs very well in highdimensional feature spaces and is therefore good at image recognition,is employed to classifying the mask images generated by the UNNN.The research result has shown that with the aid of the UNNN and SVM,the thermal infrared images that are remotely collected by drones from SPPs can be automatically and effectively processed,analyzed,and classified with reasonable accuracy(over 80%).Particularly,the mask images produced by the trained UNNN,which contain less interference items than true color thermal infrared images,significantly benefit the assessing accuracy of the health state of SPV panels.It is anticipated that the technical approach presented in this paper will serve as an inspiration for the exploration of more advanced and dependable smart asset management techniques within the solar power industry.

Wind-sand movement characteristics and erosion mechanism of a solar photovoltaic array in the middle of the Hobq Desert,Northwestern China

The operation and power generation of utility-scale solar energy infrastructure in desert areas are affected by changes in surface erosion processes resulting from the construction of solar photovoltaic(PV)power stations.However,few studies have addressed the interactions between solar PV arrays and aeolian erosion processes.In this study,wind flow field characteristics and the vertical distribution of sediments were investigated in the near-surface transport layer at three different locations with respect to the solar PV arrays in a 200 WM-p PV power station in the central Hobq Desert,northwestern China.The results indicate that the sediment transport varied around the panels,with the greatest transport occurring between the panels,followed by behind and in front of the panels.The sediment fluxes of all of the observation sites obey an exponential function.The secondary flow field zones formed around the PV panels:the conflux accelerating zone between the panels,the resistance decelerating zone of the under panels,and the transition zone of the rapid velocity increase in front of and behind the panels.This resulted in a greater shear force in front of the panels under the downward flow diversion effect of PV panels,and the wind erosion depressions were finally formed here.The results of this study provide information for planning better technical schemes for wind-sand hazards at solar PV power stations,which would ensure operational stability and safety in desert areas.

Development of Cloud Movement Prediction Method for Solar Photovoltaic System

Variability of power generation due to the prevalence of cloud cover over solar photovoltaics(PV)power plants is a challenge faced by grid operators and independent system operators(ISOs)in the integration of solar energy into the grid.Solar forecasts generated through ground⁃based sky imaging systems are useful for short⁃term cloud motion predictions.However,the cost of sky imaging systems currently available in industries is relatively high.Hence,a ground⁃based camera system utilizing a simple webcam is proposed in this study.The proposed method can produce predictions with high levels of accuracy.Forecasts were generated through video analysis using MATLAB for the computation of cloud motion predictions.The image processing involved in the implementation of the proposed system is based on the detection of cloud regions in the form of a cluster of white pixels within individual frames and tracking their motion through comparison of subsequent frames.This study describes the techniques and processes used in the development of the proposed method,along with the evaluation of performance through analysis of the results.The predictions were carried out over multiple time horizons.The time horizons selected include 5,10,15,20,25,and 30 s.The overall results computed showed promising accuracy levels above 94.60%,which makes it adequate for generating reliable forecasts.

Research on Key Technologies of Solar Photovoltaic Building Integration

On December 21,2020,The State Council Information Office issued a white paper titled"China's Energy Development in the New Era,"in which the installed capacity of hydropower,wind power,photovoltaic power and biomass power generation in China ranked first in the world[1].Solar photovoltaic power generation is the most important development direction of clean energy in the world.It is an important energy strategy to combine it with the field of construction in China.This paper mainly introduces the characteristics and problems of the key technologies of solar photovoltaic building integration,and explores its future development direction and ways,in order to constantly promote the industrialization of new energy technology in China.

Impact of utility-scale solar photovoltaic array on the aeolian sediment transport in Hobq Desert, China

Deserts are ideal places to develop ground-mounted large-scale solar photovoltaic (PV) powerstation. Unfortunately, solar energy production, operation, and maintenance are affected bygeomorphological changes caused by surface erosion that may occur after the construction of the solar PVpower station. In order to avoid damage to a solar PV power station in sandy areas, it is necessary toinvestigate the characteristics of wind-sand movement under the interference of solar PV array. The studywas undertaken by measuring sediment transport of different wind directions above shifting dunes andthree observation sites around the PV panels in the Hobq Desert, China. The results showed that the twoparameterexponential function provides better fit for the measured flux density profiles to the near-surfaceof solar PV array. However, the saltation height of sand particles changes with the intersection anglebetween the solar PV array and wind direction exceed 45°. The sediment transport rate above shifting duneswas always the greatest, while that around the test PV panels varied accordingly to the wind direction.Moreover, the aeolian sediment transport on the solar PV array was significantly affected by wind direction.The value of sand inhibition rate ranged from 35.46% to 88.51% at different wind directions. When theintersection angle exceeds 45°, the mean value of sediment transport rate above the solar PV array reducesto 82.58% compared with the shifting dunes. The results of our study expand our understanding of theformation and evolution of aeolian geomorphology at the solar PV footprint. This will facilitate the designand control engineering plans for solar PV array in sandy areas that operate according to the wind regime.

Dust Deposition’s Effect on Solar Photovoltaic Module Performance:An Experimental Study in India’s Tropical Region

A solar PV panel works with maximum efficiency only when it is operated around its optimum operating point or maximum power point.Unfortunately,the performance of the solar cell is affected by several factors like sun direction,solar irradiance,dust accumulation,module temperature,as well as the load on the system.Dust deposition is one of the most prominent factors that influence the performance of solar panels.Because the solar panel is exposed to the atmosphere,dust will accumulate on its surface,reducing the quantity of sunlight reaching the solar cell and diminishing output.In the proposed work,a detailed investigation of the performance of solar PV modules is carried out under the tropical climatic condition of Chennai,India,where the presence of dust particles is very high.The data corresponding to four different dust samples of various densities at four solar irradiation levels of 220,525,702,and 905 W/m^(2)are collected,and performance analysis is carried out.Based on the analysis carried out,the maximum power loss is found to be 73.51%,66.29%,65.46%,and 61.42%,for coal,sand,brick powder,and chalk dust respectively.Hence,it can be said that coal dust contributes to the maximum power loss among all four dust samples.Due to heat dissipation produced by dust deposition,the performance of solar PV modules is degraded as the temperature rose.

The Role of Geotechnical Engineering in Photovoltaic Solar Photovoltaic Energy in Arid Climate Regions

The photovoltaic solar energy is comprised of many engineering disci-plines.Geotechnical engineering is one of those disciplines in which it has important functions in the solar photovoltaic technology and particularly for large scale projects which usually employed in open areas such as parks or deserts.The aim of this paper is to present in depth the role of the geotechnical engineering in the solar photovoltaic energy and clarifying the common challenges facing this technology in arid climate regions.It is found that the lack of specialised codes and specifi cations that needed for foundation design and in selecting the proper foundation types.This would significantly affect the development of this technology in terms of efficien-cy and performance of the proposed solar photovoltaic systems.The hot weather climate and induced stresses by wind speed are also critical issues that should be considered.In order to avoid the uncertainty of data such as soil properties,the use of numerical modelling techniques is an eff ective method to help determining the most proper parameters needed for design and analyse purposes.

Performance Assessment of Motorized Solar Photovoltaic Louvers System Using PVSYST Software

In the realm of technological market penetration of solar photovoltaic louvers(PVL)addressing environmental difficulties and the industrial revolution,a new avenue of renewable energy is introduced.Moreover,solar energy exploitation through building façades was addressed through motorized solar photovoltaic louvers(MPVL).On the other hand,proponents exalted the benefits of MPVL overlooking the typical analyses.In this communication,we attempted to perform a thorough industrial system evaluation of the MPVL.This communication presents a methodology to validate the industrial claims about MPVL devices and their economic efficiency and the insight on how geographical location influences their utilization and augment their potential benefits.This task is carried out by evaluating the extent of solar energy that can be harvested using solar photovoltaic system(PVSYST)software and investigating whether existing product claims are associated with MPVL are feasible in different locations.The performance and operational losses(temperature,internal network,power electronics)were evaluated.To design and assess the performance of different configurations based on the geographical analogy,simulation tools were successfully carried out based on different topographical locations.Based on these findings,various factors affect the employment of MPVL such as geographical and weather conditions,solar irradiation,and installation efficiency.tt is assumed that we successfully shed light and provided insights into the complexity associated with MPVL.

Extension of Distribution Transformer Life in the Presence of Smart Inverter-based Distributed Solar Photovoltaic Systems

A transformer is an essential but expensive power delivery equipment for a distribution utility.In many distribution utilities worldwide,a sizable percentage of transformers are near the end of their designed life.At the same time,distribution utilities are adopting smart inverter-based distributed solar photovoltaic(SPV)systems to maximize renewable generation.The central objective of this paper is to propose a methodology to quantify the effect of smart inverter-based distributed SPV systems on the aging of distribution transformers.The proposed method is first tested on a modified IEEE-123 node distribution feeder.After that,the procedure is applied to a practical distribution system,i.e.,the Indian Institute of Technology(IIT)Roorkee campus,India.The transformer aging models,alongside advanced control functionalities of grid-tied smart inverter-based SPV systems,are implemented in MATLAB.The open-source simulation tool(OpenDSS)is used to model distribution networks.To analyze effectiveness of various inverter functionalities,time-series simulations are performed using exponential load models,considering daily load curves from multiple seasons,load types,current harmonics,etc.Findings show replacing a traditional inverter with a smart inverter-based SPV system can enable local reactive power generation and may extend the life of a distribution transformer.Simulation results demonstrate,simply by incorporating smart inverter-based SPV systems,transformer aging is reduced by 15%to 22%in comparison to SPV systems operating with traditional inverters.

Comprehensive Examination of Solar Panel Design: A Focus on Thermal Dynamics

In the 21st century, the deployment of ground-based Solar Photovoltaic (PV) Modules has seen exponential growth, driven by increasing demands for green, clean, and renewable energy sources. However, their usage is constrained by certain limitations. Notably, the efficiency of solar PV modules on the ground peaks at a maximum of 25%, and there are concerns regarding their long-term reliability, with an expected lifespan of approximately 25 years without failures. This study focuses on analyzing the thermal efficiency of PV Modules. We have investigated the temperature profile of PV Modules under varying environmental conditions, such as air velocity and ambient temperature, utilizing Computational Fluid Dynamics (CFD). This analysis is crucial as the efficiency of PV Modules is significantly impacted by changes in the temperature differential relative to the environment. Furthermore, the study highlights the effect of airflow over solar panels on their temperature. It is found that a decrease in the temperature of the PV Module increases Open Circuit Voltage, underlining the importance of thermal management in optimizing solar panel performance.

Optimization of Distributed Solar Photovoltaic Power Generation in Day-ahead Electricity Market Incorporating Irradiance Uncertainty

This paper proposes a simple and practical approach to model the uncertainty of solar irradiance and determines the optimized day-ahead(DA)schedule of electricity mar-ket.The problem formulation incorporates the power output of distributed solar photovoltaic generator(DSPVG)and forecasted load demands with a specified level of certainty.The proposed approach determines the certainty levels of the random variables(solar irradiance and forecasted load demand)from their probability density function curves.In this process of optimization,the energy storage system(ESS)has also been mod-eled based on the fact that the energy stored during low locational marginal price(LMP)periods and dispatched during high LMP periods would strengthen the economy of DA schedule.The objective of the formulated non-linear optimization problem is to maximize the social welfare of market participants,which incorporates the assured generation outputs of DSPVG,subject to real and reactive power balance and transmission capability constraints of the system and charging/dis-charging and energy storage constraints of ESS.The simulation has been performed on the Indian utility 62-bus system.The results are presented with a large number of cases to demonstrate the effectiveness of the proposed approach for the efficient,economic and reliable operation of DA electricity markets.

Experimental research on charging characteristics of a solar photovoltaic system by the pressure-control method

The charging characteristics of the valve-regulated lead acid(VRLA) battery driven by solar energy were experimentally studied through the pressure-control method in this paper.The aims of the research were to increase charging efficiency to make the most of solar energy and to improve charging quality to prolong life of battery.The charging process of a 12 V 12 A·h VRLA battery has been tested under the mode of a stand-alone photovoltaic(PV) system.Results show that the pressure-control method can effectively control PV charging of the VRLA battery and make the best of PV cells through the maximum power point tracking(MPPT).The damage of VRLA battery by excess oxygen accumulation can be avoided through the inner pressure control of VRLA battery.Parameters such as solar radiation intensity,charging power,inner pressure of the battery,and charging current and voltage during the charging process were measured and analyzed.

Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm

This paper proposes to resolve optimal solar photovoltaic(SPV)system locations and sizes in electrical distribution networks using a novel Archimedes optimization algorithm(AOA)inspired by physical principles in order to minimize network dependence and greenhouse gas(GHG)emissions to the greatest extent possible.Loss sensitivity factors are used to predefine the search space for sites,and AOA is used to identify the optimal locations and sizes of SPV systems for reducing grid dependence and GHG emissions from conventional power plants.Experiments with composite agriculture loads on a practical Indian 22-bus agricultural feeder,a 28-bus rural feeder and an IEEE 85-bus feeder demonstrated the critical nature of optimally distributed SPV systems for minimizing grid reliance and reducing GHG emissions from conventional energy sources.Additionally,the voltage profile of the network has been enhanced,resulting in significant reductions in distribution losses.The results of AOA were compared to those of several other nature-inspired heuristic algorithms previously published in the literature,and it was observed that AOA outperformed them in terms of convergence and redundancy when solving complex,non-linear and multivariable optimization problems.

Performance comparison of mono and polycrystalline silicon solar photovoltaic modules under tropical wet and dry climatic conditions in east-central India

This work focuses on the performance comparison of monocrystalline and polycrystalline Si solar photovoltaic(SPV)modules under tropical wet and dry climatic conditions in east-central India(21.16°N 81.65°E,Raipur,Chhattisgarh).This study would help to select the SPV module for system installation in the east-central part of the country.For comparative analysis,we used performance ratio(PR)and efficiency as figures of merit.The plane-of-array(POA)irradiance was used to determine the efficiency of the modules.The decomposition and transposition models calculated the POA values from the measured global horizontal irradiance.The data were analysed systematically for 6 months in the non-rainy season,from October 2020 to March 2021.Special attention was given to solar irradiance,ambient temperature and module temperature-the parameters that affect the performance of PV modules.The month of October showed the highest variation in irradiance and temperature.The highest average module temperatures(51-52℃)were observed in October-November,while the lowest average module temperatures(34℃ for mono-Si and 36℃ for poly-Si)were observed in December.The highest value of average monthly POA irradiance(568 W/m^(2))was observed in February and the lowest(483 W/m^(2))in December.The results showed that the monocrystalline SPV module performed better than the polycrystalline module under all weather conditions.The maximum observed values of mono-Si and poly-Si panel PRs were 0.89 and 0.86,respectively,in December.

Assessment of high-gain quadratic boost converter with hybrid-based maximum power point tracking technique for solar photovoltaic systems

Solar photovoltaic(SPV)modules have a low output voltage and are load-dependent.Therefore,it is critical that the SPV system has an adequate DC-DC converter to regulate and improve the output voltage to get maximum output voltage.To meet load requirements,the voltage must be increased,necessitating the use of energy-efficient power electronic converters.The performance of an SPV system coupled to a high-gain quadratic boost converter(HG-QBC)with a load is investigated in this paper.The suggested HG-QBC for the SPV system at a lower value of duty ratio provides high voltage gain with a boost factor of four times.An analytical comparison is carried out with the various existing boost converters in terms of the components and the boost factor.The issue of locating the maximum power generation point from the SPV system is crucial.As a result,choosing an appropriate maximum power point tracker(MPPT)-based technique to obtain the peak power output of the SPV system under the rapidly varying atmospheric conditions is vital.To determine the highest output power of an SPV system,a hybrid-based MPPT with a neural network assisted by a perturb and observe(P&O)technique is proposed.For the HG-QBC,a comparison of the proposed MPPT with a traditional P&O-based MPPT is illustrated.The comparative analysis takes into account rise time,settling time and voltage ripples.The output voltage and power characteristics of the proposed model are analysed under constant and varying irradiation conditions using MATLAB®/Simulink®.The results of a hybrid-based MPPT show that the oscillations are minimum at the maximum power point with fewer ripples of 0.20%and a settling time of 1.2 s in comparison with the other two techniques.

Effect of the Dynamic Resistance on the Maximum Output Power in Dynamic Modelling of Photovoltaic Solar Cells

Several studies on PV solar cells are found in the literature which use static models. Those models are mainly one-diode, two-diode or three-diode models. In the dynamic modelling, a variable parallel capacitance is incorporated. Unlike the previous studies which do not clearly establish a relationship between the capacitance and the voltage, in the present paper, the link between the capacitance and the voltage is investigated and established. In dynamic modelling investigated in this paper, the dynamic resistance is introduced in the modelling of the solar cell. It is introduced in the current-voltage characteristic. The value of the dynamic resistance is evaluated at the maximum power point and its effect on the maximum power is investigated. The study shows for the first time, that the dynamic resistance must be introduced in the current-voltage characteristic, because it has an influence on the PV cell output.

Renewable Energy: Prospects and Challenges in Bangladesh

Among expert scientists and politicians, there is increasing agreement that it is absolutely necessary to reduce the emission of greenhouse gas (GHG) to lessen the severity of climate change. Although little, renewable energy sources currently reduce GHG that are being emitted from the energy industries. According to the majority of long-term energy estimates, renewable energy will be a substantial addition to the supply of energy worldwide by the end of this century, as capacity of renewable energy is gradually increasing in the early decades. However, developing nations like Bangladesh are largely reliant on pricey imported energy supplies (coal, gas, and oil) that lay a heavy weight on the country’s economy. Also, air pollution growing in importance as a national and international environmental issue. Regarding the development of clean and sustainable energy, renewable energy sources seem to be among the most practical and efficient alternatives, in both Bangladesh and globally. The geographic advantages of Bangladesh allow for widespread usage of the majority of such renewable energy sources. The comparative potential and use of fossil fuels against renewable energy sources globally and in Bangladesh is explored in this review.

Modeling and Implementation of a Highly Efficient Solar-Powered Storage Installation through Self-Reconfigurable Batteries

Self-reconfigurable batteries represent a new and promising technique of electrochemical storage. The application of self-reconfigurable batteries can resolve the challenge of efficient renewable storage in solar-powered installations. In this paper, the problem of solar panel’s Maximum Power Point (MPP) tracking utilizing self-reconfigurable batteries is explored through modeling. The efficiency of energy storage is improved by removing the intervening DC/DC converter, which is usually necessary for solar PV applications. To make such a system functional, a Switching Battery Management System (SBMS) is proposed instead of a traditional couple of DC/DC converter and usual BMS. This system allows the series connection of multiple battery modules of different sizes, States-of-Charge (SoC), and States-of-Health (SoH). Two main challenges arise by the proposed implementation: tracking MPP of solar panels through battery cell switching and maintaining an equal (balanced) SoC of the separate cells/modules. The theoretical investigation includes developing the distinct software parts: digital twins of the battery module and solar PV modules that interact with the SBMS and the algorithm according to which the proposed SBMS will operate. The SBMS algorithm, based on sorting the battery cells according to their SoC, resolves both challenges. Having this promising theoretical starting point, a working prototype was developed. The prototype worked as expected and was tested under field conditions, being integrated into the power grid as part of a virtual power plant.

Composite Semiconductor Quantum Dots CdSe/CdS Co-sensitized TiO_2 Nanorod Array Solar Cells

CdSe/CdS semiconductor quantum dots co-sensitized TiO2 nanorod array was fabricated on the transparent conductive fluorine-doped tin oxide （FTO） substrate using the hydrothermal and successive ionic layer adsorption and reaction （SILAR） process. The structural and morphological properties of the samples were characterized by X-ray diffraction （XRD）, field-emission scanning electron microscopy （FESEM）, and transmission electron microscopy （TEM）. The results indicate that CdSe/CdS QDs are uniformly coated on the surface of the TiO2 nanorods. The shift of light absorption edge was monitored by taking UV-visible absorption spectra. Compared with the absorption spectra of the TiO2 nanorod array, deposition of CdSe/CdS QDs shifts the absorption edge to the higher wavelength. The enhanced light absorption in the visible-light region of CdSe/CdS/TiO2 nanorod array indicates that CdSe/CdS layers can act as co-sensitizers in quantum dots sensitized solar cells （QDSSCs）. By optimizing the CdSe layer deposition cycles, a photocurrent of 5.78 mA/cm2, an open circuit photovoltage of 0.469 V and a conversion efficiency of 1.34 % were obtained under an illumination of 100 mw/cm2.