Photovoltaic Research Articles

Application of improved Jellyfish search algorithm for 9-parameters cell extraction and GMPPT in PV systems

Optimization algorithms are essential tools used to address real-world problems through minimization or maximization processes. In the context of photovoltaic (PV) systems, various optimization algorithms have been employed to extract solar cell parameters using minimization techniques, and to identify the maximum power point (MPP) using maximization approaches. However, under partial shading conditions or during rapidly changing irradiance, many of these algorithms tend to get trapped in local minima, failing to locate the global maximum power point (GMPPT). This shortcoming leads to significant energy losses from PV cells. Similarly, the extraction of solar cell parameters is often compromised by the random search behavior and inadequate exploration and exploitation capabilities of many existing algorithms. The Jellyfish Search Optimization (JSO) algorithm is a recent, parameter-free method developed to tackle a wide range of optimization problems. Despite its innovative design, JSO is prone to premature convergence and exhibits a longer convergence time. To address these limitations, this paper proposes a modified version of the JSO algorithm, which integrates the state-of-the-art features of JSO with the Lévy flight characteristic from the cuckoo search algorithm. This combination aims to achieve a better balance between exploration and exploitation. To validate the effectiveness of the proposed Improved Jellyfish Search Optimization (IJSO) algorithm in PV systems, extensive experiments were conducted. These experiments included benchmarking with complex test functions, extracting cell parameters using various solar cell models, and maximizing energy output from PV systems under different environmental conditions. The results demonstrate that the proposed IJSO algorithm effectively enhances parameter extraction and global maximum power point tracking, making it a promising solution for optimizing energy extraction from PV cells in dynamic conditions.

Economic and Social Benefits of Aquavoltaics: A Case Study from Jiangsu, China

Aquavoltaics is an innovative and beneficial solution that makes dual use of water area for photovoltaic (PV) power generation and aquaculture. Currently, China has made remarkable developments in aquavoltaics. This paper first analyzes the current development status of aquavoltaics in China, then takes the TW “fishery–PV integration” base project in Nanjing, Jiangsu Province, as a case study to analyze its economic and social benefits, and finally puts forward countermeasure suggestions for the development of aquavoltaics in China. It is found that Jiangsu Province is one of the clustering areas for the development of aquavoltaics in China, and the development of aquavoltaics in this province has a high level of specialization. The payback period (PP) of the TW “fishery–PV integration” base project is 10.44 years, the net present value (NPV) is USD 18.5334 million (the discount rate is 5%), and the internal rate of return (IRR) is 8.06%. The social benefits of this project are mainly reflected in the promotion of energy conservation and emission reduction, the alleviation of energy shortages, the optimization of land use, and the development of culture, tourism, science, and education. The development of aquavoltaics should be promoted by strengthening scientific research, paying attention to the impact of PV panel erection on the ecological environment of the waters, emphasizing the fishery farming part of the aquavoltaic project, and improving the commercial operation mode of the aquavoltaic project.

Sinusoidal PWM Generation for 3 Phase Inverter and RPM Measurement using Hercules TMS570LC43xx Launchpad

This project focuses on implementing a 3 phase Sinusoidal PWM generation using the Hercules TMS570LC43xx Launchpad Development Kit (Launchpad). The primary objective is to generate synchronized Sinusoidal nature PWM signals using the onboard High-End Timer (HET) and Enhanced Pulse Width Modulation (ePWM) module, which can be given to the Inverter for conversion of Direct current (DC) power into Alternating current (AC) power. This conversion is essential in various applications where AC power is required but the power source provides DC power. It is used in Solar photovoltaic (PV) systems and other renewable energy installations. These systems generate power suitable for powering household appliances or feeding into the electrical grid. Itis alsoused in electric vehicles (EVs) to drive the electric motor with variable speed. For verification of the wave nature, we have used an external lowpass filter (LPF) to transform the dynamic PWM signals into sinusoidal waveforms, ensuring compatibility with various applications like Inverters which can be further used in equipment and machinery such as Brushless DC motors, pumps and compressors. With the addon functionality to control the signal’s frequency which will be given to the Inverter to control the speed of the motor. Additionally, the project incorporates RPM measurement of the motor using an optical encoder setup interfaced with the Enhanced Quadrature Encoder Pulse (eQEP) module on the Launchpad. This feature enables accurate measurement of rotational speeds, position and Revolution per minute (RPM), enhancing the functionality of the system in real world applications like the speed of conveyor belts and other automated transport systems. Through successful implementation, this project demonstrates wide control for the Inverter, achieving reliable synchronized 3 phase signals with its variable speed having 120-degree phase shift signals alongside precise RPM measurement. The project highlights the Launchpad’s capabilities in handling complex signal processing tasks essential for modern power electronics applications. Looking forward, this project establishes a foundation for future enhancements and innovations in power electronics.

Improving the efficiency of a non-ideal grid coupled to a photovoltaic system with a shunt active power filter using a self-tuning filter and a predictive current controller

Introduction. Recently, photovoltaic (PV) systems are increasingly favored for converting solar energy into electricity. PV power systems have successfully evolved from small, standalone installations to large-scale, grid-connected systems. When the nonlinear loads are connected to a grid-tied PV system, the power quality can deteriorate due to the active power supplied by the PV array, there’s a noticeable decline in the quality of power delivered to consumers. Its combination with the shunt active power filter (SAPF) enhances system efficiency. Consequently, this integrated system is adept at not only powering local loads but also at compensating for reactive power and filtering out harmonic currents from the main grid. The novelty of the work describes how an operation of a small scale PV system connected to the low voltage distribution system, and nonlinear load can be achieved, the investigation aims to analyze the system’s behavior and elucidate the advantages of employing various control algorithms. These proposed algorithms are designed to ensure a unity power factor for the utility grid while prioritizing high convergence speed and robustness against load power fluctuations across different levels of solar irradiation affecting the PV modules. The purpose of this work is to enhance the dynamic performance of the SAPF by cooperatively using a self-tuning filter (STF) based instantaneous active and reactive power method (PQ) with a novel predictive current control, enhance the system resilience, ensure optimal management of the total active power between the PV system, the electrical network and the non-linear load by integrating the functionalities of the SAPF under different levels of solar irradiation and maintain the DC-link capacitor voltage constant. Methods. A novel predictive current controller is designed to generate the switching signals piloted the three phase source voltage inverter, also a novel algorithm of instantaneous active and reactive power is developed, based on STF, to extract accurately the harmonic reference under non ideal grid voltage, also the perturb and observe algorithm is used to extract, under step change of solar irradiation, the maximum power point tracking of the PV module and the PI controller is used to maintain constant the DC-link capacitor voltage of the SAPF. Results. The efficacy of the proposed system is primarily centered on the grid side, and the performance evaluation of the control system is conducted using the STF based PQ algorithm and predictive current control. In addition, comprehensive testing encompasses all modes of operation, including scenarios involving distorted voltage sources, step changes in solar radiation, and variations in nonlinear loads. Results highlight superior performance in both transient and stable states, affirming the robustness and effectiveness of the proposed controllers. Practical value. The total harmonic distortion value of the grid current for all tests respects the IEEE Standard 519-1992. References 21, tables 7, figures 25.

Energy, environmental, economic, and social assessment of photovoltaic potential on expressway slopes: A case in Fujian Province, China

Expressway slopes within the boundary of expressway construction land have the potential to be transformed from conventional land use to valuable utilization through the installation of photovoltaic (PV) systems. Considering the continuous increase in expressway mileage, the PV potential could be enormous; therefore, a method to quantify such potential is urgently needed. This study proposes a potential assessment method for expressway slope photovoltaics. First, the suitable locations of expressway slopes for installing PV systems are identified on the basis of publicly available digital maps, combined with the principles of PV site selection and geographic information systems. Then, the PVsyst model is used to simulate the power generation efficiency and power output of the PV systems and to evaluate their PV potential, contribution, and economic benefits. The implementation of the proposed method in Fujian Province, China, indicates that the installed capacity of PV systems could reach 16.3 GW, with an annual power output of 17,940 GWh, contributing to the peak shaving of power grids and regional energy supply. The reductions in CO2, SOx, and NOx emissions are 16.65 Mt, 8970 t, and 3947 t per year, respectively. Considering carbon trading, the payback period is shortened to 11.7 years, with the return on investment of 65.38 % and the net present value of 52.6 billion RMB over a 25-year operational period. Additionally, this project could create 19.88 % of jobs in the energy sector in Fujian Province, providing 27,861 jobs during the construction phase and 18,248 jobs during the operation and maintenance phase. Thus, this project is economically viable and generates positive energy, environmental, and social benefits, contributing to the promotion of local energy transition and sustainable development.

Power quality enhancement of grid-integrated solar photovoltaic system with unified power quality conditioner

Introduction. To enhance the quality of power and ensure a consistent electricity supply, this study proposes the utilization of a unified power quality conditioner (UPQC) system integrated with solar photovoltaic (PV) technology. The innovation involves single DC-link connecting back-to-back voltage-compensating components arranged in series and shunt, forming the PV-UPQC. The shunt compensator utilizes energy from a PV array to address harmonics in the load current. The objective is to mitigate voltage dips and spikes by injecting voltage that is either in phase with or out of phase with the common coupling point through a series compensator. The method combines the benefits of generating renewable energy to enhance electrical quality. The goal of the paper is the power quality enhancement of grid-integrated solar PV system. The novelty of the proposed work consists of enhancement of grid-integrated solar PV system with UPQC. The purpose of integrating a UPQC into a grid-connected solar PV system is to enhance power quality by mitigating issues such as voltage fluctuations, harmonics and reactive power imbalance. Methods. The proposed topology is implemented in MATLAB/Simulink with grid-integrated solar PV system with UPQC. Results. Integrating UPQC with a grid-connected solar PV system yields substantial improvements in power quality. This includes effectively mitigating voltage fluctuations and harmonics, resulting in smoother operation and reduced disturbances on the grid. Practical value. The proposed topology has proven to be extremely useful for grid-integrated solar PV system with UPQC applications. References 15, table 2, figures 9.

Assessment of merits and demerits of perpendicular and slanted photovoltaic/thermal facades

This study compares the thermal and electrical energy production potential and wind load assessment of perpendicular versus slanted photovoltaic (PV) facades. The goal is to identify the optimal facade orientation for societal adoption based on energy efficiency and wind load considerations. Using Hybrid RANS/LES models, the aerodynamic performance and energy yield of both orientations are analyzed under varying angles and environmental conditions. The findings show that while the slanted façade is better designed to capture solar irradiance, it produces 4 to 8 % less energy than the perpendicular façade and yields approximately 2 % less exergy efficiency due to wind regime. However, the slanted design reduces wind load by 9.8 %, enhancing structural stability. The maximum thermal energy output of 217 kW is recorded from the perpendicular façade at a wind speed of 1 m/s, while the slanted façade generates a peak electrical power of 68 kW at 8 m/s wind speed. Overall, the perpendicular façade underscores more efficient in equal weather conditions, making it a sustainable choice for PV installation. These results provide valuable insights for architects, engineers, and policymakers in optimizing PV facade design for urban environments.

Online application of the periodic linear regression method for daily monitoring of photovoltaic systems performance

This paper presents an analysis of the performance of photovoltaic (PV) systems using daily applications of the periodic linear regression method to the performance indicators Final Yield (YF) and Reference Yield (YR). The research was conducted on PV systems installed on rooftops and ground at the Federal Institute of Education, Science, and Technology of Goiás (IFG), Itumbiara Campus, from July 2022 to August 2023. The Energy Monitoring and Management Software (SMGE) was developed to calculate the performance indicators and perform linear regression to analyze the performance of the systems. The results demonstrate that the efficiency of the systems can be monitored by analyzing variations in the slopes of the linear regression lines. An increase in energy conversion efficiency was observed following the cleaning of the PV panels, as reflected in significant changes in the regression slopes. Additionally, natural events, such as rainfall, positively impacted system efficiency. These findings highlight the importance of proper maintenance of PV panels, whether through scheduled cleaning or natural events like rain.

Investigating and Analyzing the Influence of a Solar Power Plant’s Life Cycle on the Depletion of Natural Materials and Mineral Resources

The production process requires massive amounts of minerals, fossil fuels, and energy. The efficient use of energy and natural resources appears to be crucial to the state of affairs. It should be noted that the post-consumer management of solar power plant elements results in a certain amount of power and matter, as well as harmful effects on the natural world. The major goal of this study was to examine the environmental effect of the solar power plant throughout its life cycle, taking into consideration the depletion of natural materials and mineral resources, using the ReCiPe 2016 model. A life cycle study was performed on an actual 2 MW solar power facility located in northern Poland. This study was conducted using the ReCiPe 2016 model and the Life Cycle Assessment (LCA) methodology. The analyzed renewable energy system’s impact was assessed utilizing 22 impact categories, focusing mostly on the depletion of natural resources. A Life Cycle Assessment was conducted for two post-consumer development scenarios (landfill and recycling). This research focuses on the full solar power plant, not just the photovoltaic panels. Recycling, as a kind of post-consumer development, can provide major environmental benefits and minimize negative environmental consequences throughout the solar power plant’s life cycle. The exceedingly harmful effects can be evident in losses related to water and the aquatic environment. The obtained study findings enabled the development of sustainable-friendly recommendations towards the continuous advancement of the life cycle of solar power plants, thereby reducing the use of rare earth minerals.

An efficient and resilient energy management strategy for hybrid microgrids inspired by the honey badger's behavior

This manuscript introduces a highly efficient hybrid renewable energy system (HRES) that combines photovoltaic (PV) panels and wind turbines (WTs) as primary power sources, supplemented by three backup systems: batteries, hydrogen energy storage systems (HESSs), and supercapacitors (SCs). This system employs a multi-objective optimization algorithm to dynamically identify the best energy management system (EMS). The performance of the proposed EMS across different operational scenarios is assessed using seven distinct algorithms to identify the best solution, particularly emphasizing two main objective functions: operating cost and loss of power supply probability (LPSP). Furthermore, the study rigorously evaluates the performance of these algorithms against nine benchmarks to determine the most appropriate algorithm for the HRES under consideration. In the 1st scenario, power demand is met using both primary and backup energy sources. The honey badger algorithm (HBA) proved its cost-effectiveness and efficiency by achieving the lowest overall operating cost and the highest efficiency of 95.893 %. Additionally, its computation time was notably faster, being 70 s–488 s quicker than the other algorithms. The 2nd scenario arises when power demand exceeds the available generation capacity because of the charging limits of all energy storage systems (ESSs), which prevents them from providing power to the load. The HBA achieved the lowest cost and matched the highest efficiency score of 96.691 %. Furthermore, HBA provided the quickest optimization, completing the process 400 s–450 s faster than the other techniques. In the 3rd scenario, the generated power surpasses the current load demand, and the ESS components are fully charged therefore, the proposed EMS efficiently directs excess power to a dummy load, preventing overcharging of storage components and enhancing grid stability. The HBA consistently exceeded the performance of other algorithms, achieving the lowest average cost, maintaining the highest efficiency of 95.305 %, and solving the optimization problem 300 s–500 s faster than the alternatives. Consequently, these results highlight HBA's flexibility and effectiveness, positioning it as a reliable choice for optimizing energy systems across various operational scenarios.

Possibility of Substitution of LOD1 Data for LOD2 Data on Photovoltaic Potential Estimation at City Districts Level Using a 3D City Model

Abstract. We developed a system to estimate the photovoltaic (PV) potential of urban buildings using a 3D city model at level of detail 2 (LOD2), considering an arrangement of solar panels. Although the PV potential estimation of buildings at the level of city districts prefers LOD2 data, many urban city districts with buildings capable of installing solar panels on façades do not have LOD2 data owing to the high production cost of LOD2 data. Therefore, we investigated the possibility of utilising LOD1 data instead of LOD2 data in the PV potential estimation of buildings at the level of city districts. We conducted an experiment in the investigation using 3D city model data from 24 city districts, which are most of the large cities with LOD2 data in Japan. The experiment results suggest that LOD1 would not be a substitute for LOD2 data in the PV potential estimation of building roofs. The cause of the inadaptability is that most roofs in LOD2 buildings have more small polygons than LOD1 building roofs. Roofs of a LOD2 building with many small polygons have fewer solar panels than roofs of a LOD1 building with a large polygon. On the contrary, the experiment results indicate that LOD1 may be a substitute directly for LOD2 in the PV potential estimation of building façades that are expected to be used as a mounting platform for solar panels in urban buildings from now on. The average of the relative differences in the calculated PV potential of building façades between using LOD1 data and using LOD2 data is approximately 10% in the experiment.

Inherent Water Competition Effect-Enabled Colloidal Electrode for Ultra-stable Aqueous Zn-I Batteries.

Electrode material stability is crucial for the development of next-generation ultralong-lifetime batteries. However, current solid- and liquid-state electrode materials face challenges such as rigid atomic structure collapse and uncontrolled species migration, respectively, which contradict the theoretical requirements for ultralong operation lifetimes. Herein, we present a design concept for a soft colloid polyvinylpyrrolidone iodine (PVP-I) electrode, leveraging the inherent water molecule competition effect between (SO4)2- from the electrolyte and PVP-I from the cathode in an aqueous Zn||PVP-I battery. Electrochemical demonstrations measured under various simulated and practical (integrated with photovoltaic solar panel) conditions highlight the potential for an ultralong battery lifetime. The PVP-I colloid exhibits a dynamic response to the electric field during battery operation. More importantly, the water competition effect between (SO4)2- from the electrolyte and water-soluble polymer cathode materials establishes a new electrolyte/cathode interfacial design platform for advancing ultralong-lifetime aqueous batteries.

A review of the state of the art in solar photovoltaic output power forecasting using data-driven models

A review of the state of the art in solar photovoltaic output power forecasting using data-driven models

Experimental investigation on wind loads and wind-induced responses of large-span flexible photovoltaic support structure

Flexible photovoltaic (PV) support structure offers benefits such as low construction costs, large span length, high clearance, and high adaptability to complex terrains. However, due to the high flexibility and low damping of the cable system, wind load becomes the primary control factor for structural safety and the key consideration in the design. In this study, a 45 m span flexible PV support structure with 3 spans and 12 rows was designed. The wind loads on PV panels were obtained by wind tunnel tests on a rigid model and the wind-induced responses were investigated by wind tunnel tests on an aeroelastic model. The shielding effects and tilt angle of PV modules on the wind load and wind-induced vibration of the flexible PV support were studied. The experimental results show that in the rigid model wind tunnel test, the wind pressure on the surface of PV modules exhibits a gradient distribution along the direction of wind flow, with symmetric distribution along the mid span. With the increase in the tilt angle of the PV module, the shielding effect becomes significant and the most pronounced shielding effect on the mean wind pressure coefficient occurs in the second row of the windward zone. In aeroelastic model wind tunnel tests, the mean vertical displacement of the flexible PV support structure increases with the increase of wind speed and tilt angle of PV modules. Due to the wind-resistant anchor cables set in both the windward and leeward zones, the vibration amplitude near the edge rows is significantly smaller than that of the middle rows when the structure is subjected to wind suction. When the flexible PV support structure is subjected to wind pressure, the maximum mean vertical displacement occurs in the first rows at high wind speeds. The shielding effect has a noticeable impact on the wind-induced response of the leeward zone at α = 20° under wind pressure, resulting in the decrease of amplitude vibration by approximately 53 %. The wind vibration coefficients in different zones under the wind pressure or wind suction are mostly between 2.0 and 2.15. Compared with the experimental results, the current Chinese national standards are relatively conservative in the equivalent static wind loads of flexible PV support structure.

Aging Retardation of Lead-Acid Batteries by Adjusting Charge Controller Threshold Values in Off-grid Photovoltaic System

Hybrid systems or coupled power plants with energy storage are becoming more and more popular due to the rising need for energy. Researchers have been conducting several experiments to assure longer-lasting battery use due to the increasing widespread use of energy storage and the depletion of resources such as silicon and precious metals. In this study, a simulation study is carried out in PVSyst software on lead-acid batteries, which have a low cycle and a very traditional electrochemical structure. The simulation is realized by scaling Spain’s consumption curve in 2023, taken from the European Network of Transmission System Operators for Electricity (ENTSO-E), together with lead acid batteries and off-grid photovoltaic (PV) modules. After the off-grid system design is created and consumption data is imported, it is aimed to extend battery life by changing the charge-discharge threshold values of the charge controllers. Threshold values are in two categories, high and low, and seventeen different cases are simulated. According to the results of the simulation, the state of charge (SOC) levels of the batteries decreases significantly due to radiation and cloudiness in the winter months and remain high in the spring and summer months. When charge controllers are set to high thresholds levels, they cause gassing currents that rise to an average of 20 amps, while battery life extends up to 5.3 years. When low threshold values are used, negligible levels of oxygen and hydrogen gasses are formed in the battery, but battery life decreases to 4.1 years.

A perspective on solar railway potential for the UK

AbstractIn the face of climate change challenges, energy demand is still increasing, and renewable energy is becoming increasingly necessary as a sustainable resource. Solar energy stands out as a promising renewable resource, yet its widespread adoption faces challenges, notably the substantial land requirements for photovoltaic (PV) panels. This conflict intensifies as land could be more efficiently utilized for agriculture and development. Conversely, railway infrastructure occupies expansive tracts of land, presenting an opportunity to integrate PV panels without disrupting rail operations. However, a comprehensive assessment of the solar potential along railway tracks on a national scale is lacking for different countries and the UK is one of them. This study addresses this gap by evaluating the feasibility of installing PV panels on railway tracks throughout the UK to generate electricity. Utilizing mathematical models tailored to five distinct solar panel technologies, the study incorporates various factors, including solar radiation levels across different months. Assumptions were made where necessary, with values for certain variables averaged to facilitate calculations. The findings reveal that solar energy harnessed from railways could satisfy up to 8% of the UK's total electricity demand, with a minimum contribution of 0.3%. This study provides valuable insights from a UK‐centric perspective and offers a replicable framework for similar assessments in other countries with extensive railway networks, such as China and India. By leveraging existing infrastructure for renewable energy generation, such initiatives could contribute significantly to global sustainability efforts.

A method for configuring hybrid electrolyzers based on joint wind and photovoltaic power generation modeling using copula functions

Considering the specific wind and photovoltaic power characteristics of a certain region, this study investigates the optimal ratio of Alkaline Electrolysis Cells (AEL) to Proton Exchange Membrane (PEM) electrolyzers in a hybrid electrolysis system for hydrogen production. A flexible model for configuring the hybrid electrolysis system is proposed, based on a copula function for joint wind and solar power modeling. This model generates wind and photovoltaic power generation scenarios using the copula function, incorporating a selection mechanism to ensure that the output scenarios are more representative of the actual data characteristics of wind and photovoltaic power output. Consequently, considering both the fluctuation and amplitude, the wind and photovoltaic power data are decomposed using the Ensemble empirical mode decomposition method. The decomposed components are then allocated to the two types of electrolyzers. Furthermore, the optimal configuration of the hybrid electrolysis system is determined by minimizing the costs associated with wasted power, electricity purchases, and other expenses. Finally, a case study of a 100 MW wind farm and a 50 MW photovoltaic power station in Northwest China is presented, concluding that the optimal configuration ratio of AEL to PEM electrolyzers is 2:1. In a Matlab/Simulink platform, the performance metrics of the hybrid electrolysis system were validated. It was found that the hydrogen production rate of the hybrid electrolyzer is comparable to that of the PEM electrolyzer, but with a lower required cost. Additionally, the hydrogen production rate and volume of the optimal configuration for the hybrid electrolyzer determined by the model proposed in this paper are higher than those obtained through the optimization algorithm's optimal configuration.

Locating the suitable large-scale solar farms in China's deserts with environmental considerations

Desert areas offer rich solar resources and low land use costs, ideal for large-scale new energy development. However, desert ecosystems are fragile, and large-scale photovoltaic (PV) power facilities pose ecological risks. Current assessments of PV plant sites in deserts lack consideration of wind-sand hazards and ecological impacts. In this study, we have developed a new large-scale photovoltaic (PV) site selection model that integrates the analytic hierarchy process with geographic information system technology, and applies it to the desert regions of China. The results show that the potential for large-scale PV power plants in China's deserts is significant, with 69.4 % of the region assessed as medium or higher. The most suitable area is 12.7 × 104 km2 (7.6 % of the overall study area), mainly centered in the Tibetan Plateau's Qaidam Basin Desert and the deserts of northern China, characterized by favorable solar resources, climate, and terrain. Across all regions, gravel deserts are recognized as more suitable for the construction of large-scale PV power projects than sandy deserts. Considering varying PV installation density scenarios with an installed capacity potential of 36.4–84.9 TW and system costs ranging from 10.0 to 33.5 trillion USD, the study estimates an annual solar power generation potential of 47–110 PWh which is 1.7–3.9 times the global electricity demand. Carbon emissions could be reduced by 26.8–62.6 gigatons annually, offsetting 73–170 % of global emissions. Covering just 4.8–11.5 % of China's desert area (8 × 104–19.4 × 104 km2) would meet the projected 2025 electricity needs of the country. This study lays the groundwork for spatial planning and benefit assessment of large-scale PV projects in desert regions, and reduces conflicts between PV plant construction and local ecosystem.

In‐use dissipation of technology‐critical elements from vehicles and renewable energy technologies in Vienna, Austria: A public health matter?

AbstractThe rollout of electric vehicles and photovoltaic panels is essential to mitigate climate change. However, they depend on technology‐critical elements (TCEs), which can be harmful to human health and whose use is rapidly expanding, while recycling is lacking. While mining has received substantial attention, in‐use dissipation in urban areas has so far not been assessed, for example, corrosion and abrasion of vehicle components and weather‐related effects affecting thin‐film photovoltaic panels. Therefore, the question arises to which extent TCEs dissipate during use and which potential non‐occupational human health impacts could occur. We assessed the available information on urban in‐use dissipation and human health concerns and conducted exploratory modeling of in‐use technology stocks, in‐ and outflows, and in‐use dissipation of neodymium, dysprosium, lanthanum, praseodymium, cerium, gallium, germanium, and tellurium contained in 21 vehicle and renewable energy technologies, for Vienna, Austria. In prospective scenarios, TCE dynamics in a trend‐continuation vis à vis official city policy plans and a more ambitious transition scenario were then assessed. We find that electrifying the vehicle fleet without demand‐reduction is the main driver of TCE consumption, effectively doubling cumulative end‐of‐life outflows to 3,073 [2,452–3,966] t and cumulative in‐use dissipation to 9.3 [5.2–15.7] t by the year 2060. Sufficiency‐based measures could reduce demand and in‐use dissipation well below levels with continued trends, thus highlighting the need to combine decarbonization with demand‐reducing measures. These results help assess potential future in‐use dissipation dynamics and inform discussions about potential public health hazards associated with exposure to TCEs accumulating in the urban environment.

Improvement of Power Production Efficiency Following the Application of the GD InC Maximum Power Point Tracking Method in Photovoltaic Systems

This paper proposes a new maximum power point tracking (MPPT) method based on machine learning with improved power production efficiency for application to photovoltaic (PV) systems. Power loss occurs in the incremental conductance (InC) method, depending on the size of the voltage step used to track the maximum power point. Additionally, the size of the voltage step must be specified by the initial user; however, an appropriate size cannot be determined in a rapidly changing environment. To solve this problem, this study presents a gradient descent InC (GD InC) method that optimizes the size of the voltage step by applying an optimization method based on machine learning. The effectiveness of the GD InC method was verified and the optimized size of the voltage step was confirmed to produce the largest amount of power. When the size of the voltage step was optimized, a maximum difference of 4.53% was observed compared with the case when the smallest amount of power was produced. The effectiveness of the GD InC method, which improved the efficiency of power production by optimizing the size of the voltage step, was verified. Power can be produced efficiently by applying the GD InC method to PV systems.