Photovoltaic System Applications Research Articles

Parameter Estimation of Modified Double-Diode and Triple-Diode Photovoltaic Models Based on Wild Horse Optimizer

The increase in industrial and commercial applications of photovoltaic systems (PV) has a significant impact on the increase in interest in studying the improvement of the efficiency of these systems. Estimating the efficiency of PV is considered one of the most important problems facing those in charge of manufacturing these systems, which makes it interesting to many researchers. The difficulty in estimating the efficiency of PV is due to the high non-linear current–voltage characteristics and power–voltage characteristics. In addition, the absence of ample efficiency information in the manufacturers’ datasheets has led to the development of an effective electrical mathematical equivalent model necessary to simulate the PV module. In this paper, an application for an optimization algorithm named Wild Horse Optimizer (WHO) is proposed to extract the parameters of a double-diode PV model (DDM), modified double-diode PV model (MDDM), triple-diode PV model (TDM), and modified triple-diode PV model (MTDM). This study focuses on two main objectives. The first concerns comparing the original models (DDM and TDM) and their modification (MDDM and MTDM). The second concerns the algorithm behavior with the optimization problem and comparing this behavior with other recent algorithms. The evaluation process uses different methods, such as Root Mean Square Error (RMSE) for accuracy and statistical analysis for robustness. Based on the results obtained by the WHO, the estimated parameters using the WHO are more accurate than those obtained by the other studied optimization algorithms; furthermore, the MDDM and MTDM modifications enhanced the original DDM and TDM efficiencies.

Mathematical modelling for solar cell, panel and array for photovoltaic system

Renewable energy is considered as next alternative to fossil fuels and nowadays, it attracts much attention in agriculture and environmental protection. Application of solar photovoltaic system is drying and dehydration of products, heating, irrigation, greenhouse and power generation etc. Temperature and sun radiation varies nonlinearly. Power generation varies with reference to radiation and temperature in photo-voltaic (PV) system. PV characteristic is nonlinear and PV cell is the basic unit for electricity generation. To get the characteristic response of PV, it aimed to develop a solar cell/panel model and array on a platform like MATLAB. In this research paper, step by step procedure has been defined for modelling solar cell, panel, and array models of the photovoltaic system. Kyocera solar KC-200GT 200W solar panel is used as a reference model for further modelling. The PV array characteristic are simulated for different irradiance(200W/m2,400 W/m2 ,600 W/m2 ,800W/m2 ,1000W/m2)and temperature variation(25°C, 35°C, 45°C, 55°C, 75°C). The output characteristic of the reference model matches with simulated results. The output reduced when the solar irradiation reduced from 1000 to 200 W/m2. As the temperature increased, the output voltage decreases, whereas the output current increases slightly. This model would be useful for investigating the effect of different parameters like series resistance, shunt resistance, thermal voltage, solar cell temperature coefficient of short circuit current etc. It would also be useful for investigating the working parameters like temperature & radiation condition and different series and parallel combinations of panels. This modelling is useful in investigating the performance of solar arrays in different applications of solar power generation, as well as modelling provides a major role in the mounting of PV panels.

Sensitivity Analysis for 3E Assessment of BIPV System Performance in Abadan in Southwestern Iran

In Iran, due to the problems and constraints of fossil fuels and the need to maximize the use of solar potential, one of the best ways is the application of photovoltaic systems integrated with buildings. Due to the significant dependence of solar cell performance on the availability of radiation, it is necessary for architects to have an accurate assessment of the amount of electricity produced in different conditions. Therefore, in the present work, using HOMER software, the energy-econo-Enviro (3E) potential of a Building Integrated Photovoltaic (BIPV) in Abadan was studied. The effect of slope and azimuth of solar cells as well as cloudiness and system losses were investigated using sensitivity analysis. The results showed that the PV-grid system was the most economical option and after the azimuth angle of zero degree, the positive azimuth angle was the most economical. The results also showed that the slope of 30 degree and the angle of azimuth equal to zero was appropriate, for which the price per kWh of generated electricity was calculated to be $0.09. For the use of solar cells in the vertical wall of the building, the southwest direction was the most suitable and based on the results, it was suggested that the western wall of the building should be in the form of “inclined PVs with windows”. The authors of this paper hope that the results of the present work can be used by architects and energy decision-makers as a guide in developing the BIPV use in Iran.

Forecasting the Energy and Economic Benefits of Photovoltaic Technology in China’s Rural Areas

In recent years, with the rapid development of China’s economy, China’s energy demand has also been growing rapidly. Promoting the use of renewable energy in China has become an urgent need. This study evaluates the potential of solar photovoltaic (PV) power generation on the roofs of residential buildings in rural areas of mainland China and calculates the area that can used for generating energy, the installed capacity, and the power generation, and conducts a comprehensive analysis of the economic benefits of investing in the construction of distributed PV systems in various provinces. The findings unveiled in this study indicate that China still has more than 6.4 billion m2 of rural construction area available for the installation of PV modules. If this is all used for solar power generation, the annual power generation can reach up to 1.55 times the electricity consumption of urban and rural residents for the whole society. Through a comprehensive evaluation of energy efficiency and economic benefits, the Chinese mainland can be divided into three types of resource areas. The three types of resource areas have their own advantages and disadvantages. According to their own characteristics and advantages, we can reasonably formulate relevant policies to accelerate the development of PV system application in rural areas.

Performance of Active Clamp and Interleaved Active Clamp Fly back DC-DC Converters for PV Systems

The Flyback converter topology is a well-known and widely used for AC-DC and DC-DC power converters that cover a broad-spectrum including switching power supplies, photovoltaic (PV) system, electric cars, and fuel cell-based generation systems, and among other applications. In this work, Active Clamp Flyback (ACF) and Interleaved Active Clamp (IACF) converters are designed and simulated for the use of DC-DC converters of PV system applications. Two control systems are used to control the output voltage of the DC-DC converters for various PV conditions, which are PID (proportional integral derivatives) and FLC (fuzzy logic controller). MATLAB/SIMULINK is used to model and simulate the proposed system, where the proposed control systems are developed to regulate the output voltage for the load requirements. The simulation results of the proposed PV systems indicate that the output voltage stabilizes effectively to the required voltage (24 V) for various loads/applications while the input voltage (output from the solar panel) to the converters is varying regrading to different sun radiation levels and other parameters. The efficiency of ACF and IACF converters are found to be 88% and 90%, respectively.

A novel UV sensor-based dual-axis solar tracking system: Implementation and performance analysis

The application of photovoltaic (PV) systems has been increasing rapidly worldwide in the field of sustainable electricity generation. However, the efficiency of PV systems depends significantly on the orientation of solar PV modules. To enhance the efficiency of PV systems, previous studies focused mainly on the development of sensor-based solar tracking systems using sun position sensors. In particular, they used light-dependent resistors (LDRs), which detect the visible light spectrum. However, LDRs have significant limitations (e.g., saturation of light intensity and ineffectiveness under low-visibility conditions) that can adversely affect the solar tracking performance. Utilization of ultraviolet (UV) spectrum captured by UV sensors displays the potential for overcoming the limitations of LDRs. This is owing to the enhancement of UV radiation by the cloud effect during overcast conditions and the capability of UV sensors. Considering this, we propose a novel UV sensor-based dual-axis solar tracking system to improve tracking movements and PV energy generation by utilizing the advantages of UV radiation enhancement and UV sensor capability. Four intensity signals of UV radiation obtained by UV sensors are compared and employed as inputs to the solar tracking system after it is implemented on a pseudo-azimuthal mounting structure, which is capable of following the sun trajectory through daily and elevation angles. A comparative analysis is performed to evaluate the solar tracking performance of the proposed solar tracking system with respect to that of a fixed flat-plate system and conventional LDR-based solar tracking system. The experimental results reveal that our tracking system increases energy generation (after accounting for the operational energy consumption) by 19.97% and 11.00% compared with the fixed flat-plate system and LDR-based solar tracking system, respectively. Moreover, the proposed solar tracking system performs effectively in terms of movement tracking under the tested conditions. Finally, the economic performance evaluation demonstrates that the proposed tracking system is profitable.

Investigation of Thermal Stress Arising in a Graphene Neutral Density Filter for Concentrated Photovoltaic System

As an excellent heat spreader candidate, graphene attracts considerable interest concerning its application in concentrated photovoltaic (CPV) systems. The consequences of employing a graphene-coated neutral density (GCND) filter to mitigate concentrated light impact adequately. Hence, the temperature for a concentrated photovoltaic system is reported in this work. A systematic thermal characterisation study was carried out using three different thickness-based GCND filters. Interestingly, using the GCND filter, the focal spot temperature remained considerably lower than that of the incident temperature for a more extended period. The graphene coating orientation further influenced the temperature gradient behaviour of the focal spot and incident temperature. The thermal and electrical results depended on the GC samples’ thickness and emplacement, leading to dramatic differences in their respective photovoltaic performance. As a base substrate of the GCND filter, the low-iron glass suffered extreme thermal stress under concentrated solar irradiance. This thermal stress phenomenon on the GCND filter was further analysed. This study suggests that using GCND leads to lower temperature maintenance of the CPV focal point, which minimises the PV cell thermal stress. However, the GCND filter also experienced considerable thermal stress during the CPV experiment.

Reaction, structure and spectroscopic properties of bis(cyano) cobalt(III) porphyrin complexes

Cyanocobalamin and analogues have drawn much attention for the promising applications in photovoltaic and photocatalytic systems. In this study, two low spin bis(cyano) cobalt(III) porphyrin complexes [K(222)][Co[Formula: see text](TPP)(CN)2] and [K(222)][Co[Formula: see text](TMP)(CN)2] (222 = 4,7,13,16,21,24-hexaoxo-1,10-diazabicyclo[8.8.8]hexacosane, TPP = meso-tetraphenylporphyrin dianion, TMP = meso-tetramesitylporphyrin dianion), which were isolated from the reactions between [Co[Formula: see text](Porph)] (Porph = Porphyrin) and [K(222)(CN)], are characterized by a single crystal X-ray diffraction, FT-IR and UV-vis spectroscopies. Combined UV-vis and electron paramagnetic resonance (EPR) investigations have been conducted to understand the reaction mechanisms. The work gives new insights into the reactivities and spectroscopic properties of cyano cobalt macrocyclic complexes.

Comparison study of lead-acid and lithium-ıon batteries for solar photovoltaic applications

The battery energy storage systems are very essential for maintaining constant power supply when using solar photovoltaic systems for power generation. The viability and ability of battery energy storage systems are assessed based on battery usage in Solar Photovoltaic utility grid-connected systems. The power supply quality and reliability are improved by utilizing battery energy storage technologies in conjunction with solar photovoltaic systems. This paper presents a comparative analysis of Lead-Acid Storage battery and Lithium-ion battery banks connected to a utility grid. The battery mathematical model simulation study gives their performance characteristics of these batteries under grid-connected loads. Cost-benefit analysis of battery usage for determining the best battery suitable for solar photovoltaic system applications is also presented in this paper.

A taxonomical review on recent artificial intelligence applications to PV integration into power grids

The exponential growth of solar power has been witnessed in the past decade and is projected by the ambitious policy targets. Nevertheless, the proliferation of solar energy poses challenges to power system operations, mostly due to its uncertainty, locational specificity, and variability. The prevalence of smart grids enables artificial intelligence (AI) techniques to mitigate solar integration problems with massive amounts of solar energy data. Different AI subfields (e.g., machine learning, deep learning, ensemble learning, and metaheuristic learning) have brought breakthroughs in solar energy, especially in its grid integration. However, AI research in solar integration is still at the preliminary stage, and is lagging behind the AI mainstream. Aiming to inspire deep AI involvement in the solar energy domain, this paper presents a taxonomical overview of AI applications in solar photovoltaic (PV) systems. Text mining techniques are first used as an assistive tool to collect, analyze, and categorize a large volume of literature in this field. Then, based on the constructed literature infrastructure, recent advancements in AI applications to solar forecasting, PV array detection, PV system fault detection, design optimization, and maximum power point tracking control problems are comprehensively reviewed. Current challenges and future trends of AI applications in solar integration are also discussed for each application theme.

Evaluation for block-scale solar energy potential of industrial block and optimization of application strategies: A case study of Wuhan, China

Industrial blocks are an important part of the city which is very suitable for PV application because of its large-scale, unified property rights and simple form. In this study, a multi-dimensional evaluation method of solar energy potential suitable for the block-scale is constructed. Then, 48 cases of industrial blocks in a typical city of china were selected as examples. Basing on morphological parameters, all cases were classified into 7 types by clustering algorithm. Afterwards, the total amount and distribution of the solar energy potential were calculated. Finally, the strategies of the photovoltaic system application in blocks were proposed according to types of blocks. It is found that there is significant difference in solar energy potential between different types of industrial blocks. Among them, solar energy potential of single-storey types is the highest up to 90.85 kW h/m2•year, while solar energy potential of high-rise type blocks is relatively lower which is only 55.64 kW h/m2•year. In addition, block shape has obvious impact on solar energy potential, among which building density having the greatest influence, as building density increases from 20 % to 55 %, the solar energy potential also increased by 138.74 % from 42.54 kW h/m2•year to 101.56 kW h/m2•year.

Implementation of LED Lighting Powered by Solar Energy for Bicycles

The high efficiency, simple driving, environmental protection and long life of high power white-light diodes have attracted a lot of attention from industry and academia. High-efficiency white LEDs have the potential to replace traditional lighting such as incandescent bulbs and fluorescent lamps, and can be used in residential environments, industry and commercial advertising. Because of the advantages of light-emitting diodes, such as power saving, environmental protection, long life and fast response time, they will replace traditional light-emitting elements as the new lighting source in the future. Under the restrictions and regulations of the Kyoto Protocol, we will cooperate with the country to actively promote energy-saving technology and energy industry in the future. This paper proposes the development of LED lighting and photovoltaic, and the application of solar photovoltaic systems to bicycles, in line with the green technology industry LED lighting and solar photovoltaic industry development. Energy-saving LEDs can be combined with stand-alone lighting systems to enable the sustainable development of renewable energy development and energy conservation policies in Taiwan. Keywords: Solar cells, Light-emitting diodes, LED lamp drivers, White LEDs.

Risk-Benefit Assessment Scheme for Renewable Solar Solutions in Traditional and Historic Buildings

Within the framework of IEA-SHC Task 59, a multidisciplinary team of experts from around the world has come together to investigate current approaches for energy retrofit of the built heritage with energy efficiency conservation-compatible measures, in accordance with cultural and heritage values, and to check and adapt the new standard EN-16883:2017 for historic buildings. This paper introduces activities within IEA-SHC Task 59 (Subtask C) focused on retrofit solutions with high impact on sustainability, energy efficiency, and the integration of renewables, which is the main goal of the solar group, focused on the integrated solar systems for historic buildings. Relying on an extensive, detailed, and accurate collection of case studies of application of solar photovoltaic and thermal systems in historic buildings, the assessment criteria of the standard have been reviewed and tailored for better solar implementation evaluation in a heritage context. All this is studied based on technical compatibility, the heritage significance of the building and its settings, the economic viability, the energy performances and indoor environmental quality and use, as well as the impact on the outdoor environment of solar renewables.

Centralised coordination of EVs charging and PV active power curtailment over multiple aggregators in low voltage networks

Widespread application of residential photovoltaic (PV) systems and electric vehicles (EVs) has led the distribution system operators (DSOs) to face new technical challenges such as overloading and significant voltage variations, especially on low voltage (LV) grids. This adverse effect may be mitigated by employing the aggregators as intermediary actors to coordinate the operation at the distribution level. Therefore, this paper proposes a centralised coordination strategy to mitigate both PV and EV impacts, such as voltage rising/dropping at noon or evening, respectively, by defining the optimal export limit of PV power and EVs charging among multiple aggregators at the DSO level. The latter is in charge to dictate the optimal aggregated signals to every aggregator by employing a mixed-integer quadratic programming (MIQP) approach. The aggregated PV power is evenly managed for each aggregator by weighting. Two convex optimisation models are defined to satisfy both power and voltage constraints of the LV network. Each proposed optimisation approach can be utilised when there is or no detailed information about the LV network topology. The concepts discussed in this paper are tested on a real low voltage network considering a critical penetration level of EVs and PVs.

A chronological review of prospects of solar photovoltaic systems in Bangladesh: Feasibility study analysis, policies, barriers, and recommendations

The main focus of this paper is to present the current prospects, potentials, research activities, future concerns, and applications of solar photovoltaic (PV) systems in Bangladesh. Despite the existence of several articles in the literature on solar energy prospects in Bangladesh, the diffusion of several solar PV applications throughout the country, their rapid progress analysis, and existing feasibility study outcome analysis are still unrevealed. Therefore, an endeavour has been made for the first time to condense the government and non-government contributions to disseminating solar energy throughout the country. Twenty-one feasibility studies at different locations of Bangladesh are reviewed and analysed, in terms of financial viability, sensitivity analysis, and greenhouse gas emissions, to foresee the prospects of solar energy in Bangladesh. Sensitivity analyses are performed, with six sensitivity variables, which reveal that the total net present cost of the solar project implementation may be increased by 20% (maximum) in the lowest solar potential area than the highest one with an average payback period of 13 years. This paper also identifies the policy gaps, classifies the barriers into eight categories, and discusses the conceivable approaches to defeat those barriers, followed by recommendations in six different aspects.

Adaptive single carrier multilevel modulation for grid connected single phase modular multilevel inverter

In this paper, an adaptive single carrier multilevel (ASCM) Modulation technique is proposed to simplify the implementation of the single phase modular multilevel converter based on the grid connected to string inverter (MMSI) for the photovoltaic generation system applications. The main characteristics of adaptive single carrier multilevel modulation are reduction in switching losses and the harmonics performance improvement. The control configuration of MMSI, includes the proposed ASCM modulation scheme is designed. In order to investigate the performance of the proposed methods, the simulation model of the MMSI is developed in the MATLAB/SIMULINK environmental to verify the performance of the ASCM technique. The laboratory prototype for MMSI is developed using the DSP TMS32F2407. The experimental results are included to support the simulation result.

Developing automated methods to estimate spectrally resolved direct normal irradiance for solar energy applications

We describe four schemes designed to estimate spectrally resolved direct normal irradiance (DNI) for multi-junction concentrator photovoltaic systems applications. The schemes have increasing levels of complexity in terms of aerosol and circumsolar irradiance (CSI) treatment, ranging from a climatological aerosol classification with no account of CSI, to an approach which includes explicit aerosol typing and type dependent CSI contribution. When tested against ground-based broadband and spectral measurements at five sites spanning a range of aerosol conditions, the most sophisticated scheme yields an average bias of +0.068%, well within photometer calibration uncertainties. The average spread of error is 2.5%. These statistics are markedly better than the climatological approach, which carries an average bias of −1.76% and a spread of 4%. They also improve on an intermediate approach which uses Angström exponents to estimate the spectral variation in aerosol optical depth across the solar energy relevant wavelength domain. This approach results in systematic under and over-estimations of DNI at short and long wavelengths respectively. Incorporating spectral CSI particularly benefits sites which experience a significant amount of coarse aerosol. All approaches we describe use freely available reanalyses and software tools, and can be easily applied to alternative aerosol measurements, including those from satellite.

A high gain soft-switching active-clamped coupled-inductor-based converter for grid-tied photovoltaic applications

Due to increased demand for electricity and to curtail large consumption of fossil fuels, researchers are more focused on renewable energy sources, particularly solar photovoltaic (PV). In general, grid-tied PV systems require a high voltage boosting stage, leading to reduced efficiency. A converter is proposed along with the high gain and soft-switching capabilities by using an active-clamped circuit to the coupled inductor for grid-tied PV system applications. In this circuit, high gain is achieved by incorporating switched capacitors (SCs) in conjunction with the coupled inductor and regenerative diodes. The SCs are connected in such a way that, they store the energy in parallel and deliver the energy in a series. By using the active-clamped circuit, the switching overvoltages are diminished and also improvement in converter efficiency with the zero-voltage switching (ZVS). The operating principle of the converter and its design procedure is presented. Finally, to validate the theoretical analysis, the obtained experimental results from a laboratory prototype of 500 W rated at 100 kHz with the variation of input voltage, 36–48 V, and output voltage 400 V are presented.

Efficient maximum power point tracking for a photovoltaic using hybrid shuffled frog-leaping and pattern search algorithm under changing environmental conditions

During recent decades, the power system has experienced the ever-increasing penetration level of renewable energy sources (RESs), both in a centralized and a distributed manner. Solar energy in the form of solar photovoltaic (PV) panels has captured attention in power systems, particularly at the distribution level and it is being used all around the world with acceptable solar irradiance. However, such technology is associated with severe technical shortfall in harnessing the maximum power. Accordingly, several techniques have been introduced for the maximum power point tracking (MPPT) of PV systems. In this respect, an MPPT technique, augmented by the incremental conductance (INC) and hybrid shuffled frog-leaping and pattern search algorithm (HSFLA-PS) based adaptive neuro-fuzzy inference system (ANFIS) has been presented in this paper for the solar PV systems applications. The proposed framework is comprised of two stages. The optimal values of the voltages for different values of temperatures and solar irradiances are derived in the first stage by utilizing the SFLA-PS method. After implementing the training process, the ANFIS would give an optimal voltage, taking into account different values of solar irradiance. The INC method will be initialized from this point to search for the maximum power point known as “MPP”. The merit of the combinatorial ANFIS and INC method is that it would need a lower number of samples for the training process. The results, obtained from simulating the proposed framework indicate that the combinatorial HSFLA-PS-ANFIS-INC technique would result in the global maxima in various climate conditions at a higher convergence rate and efficiency.

An Online Method of Estimating State of Health of a Li-Ion Battery

Li-ion batteries are playing a crucial role in the fields of renewable energy systems and electric vehicles. The reliability of these systems depends on a battery management system (BMS) which monitors the state of charge (SoC) and state of health (SoH) effectively. Knowing the SoH of a battery in advance enhances the system reliability. This article proposes an accurate online estimation of SoH of a Li-ion battery integrated in solar photovoltaic system (SPV) applications. The proposed method uses the modified coulomb counting method to estimate the SoH of a battery. The proposed SoH estimation method is simulated in MATLAB/Simulink by considering the aging factors such as temperature, charge/discharge rates and depth of discharge. Moreover, the proposed method is validated using an experimental prototype and the results are found to be satisfactory.