Photovoltaic Characteristics Research Articles

Elucidating the potential of nitrogen-containing heterocyclic core-based non-fullerene acceptors for organic photovoltaic applications

Intramolecular noncovalent interactions are recognized as an efficient route to construct non-fused-core-based non-fullerene acceptors (NFAs) for efficient and cost-effective organic solar cells (OSCs). Herein, we engineered ten distinct structured NFAs molecules based on nitrogen-containing six-membered heterocycle cores. We incorporated various efficient functional groups into the synthetic reference molecule (RM) to design a new efficient series of NFAs (RM1-RM10). These materials are intensively investigated by performing advanced quantum chemical simulations, and the results are compared with those of synthetic RM molecules. We revealed the potential of these materials by investigating their optical, electronic, optoelectronic, and photovoltaic characteristics. By implementing various theoretical models, we explore the inner hidden potential of this designed series (RM1-RM10), such as density of state, transition density matrix, and electrostatic potential studies have been performed. Our applied theoretical modeling approach enables these photovoltaic materials (RM1-RM10) to have customized attributes by tuning their energy levels, binding energy, optical features, and also the photovoltaic characteristics of these materials. Newly developed molecules (RM1-RM10) show promising optoelectronic properties, including a lower energy gap (ranging from 1.81 eV to 1.63 eV) and an absorbed maximum absorption wavelength (760.36 nm), compared to the reference values, which have an energy gap of 1.81 eV and a wavelength of 684.16 nm. Moreover, to demonstrate the charge transfer behavior of these materials, a donor: acceptor (PTB7-Th:RM9) complex study is also performed to reveal the charge transfer phenomenon at the donor: acceptor interface. Therefore, our presented molecular modeling strategy holds significant potential for manufacturing materials with tailored qualities, which is crucial in advancing the organic photovoltaics field.

Cost-Effective Synthesis Method: Toxic Solvent-Free Approach for Stable Mixed Cation Perovskite Powders in Photovoltaic Applications.

Organometallic lead halide perovskite powders have gained widespread attention for their intriguing properties, showcasing remarkable performance in the optoelectronic applications. In this study, formamidinium lead iodide (α-FAPbI3) microcrystals (MCs) is synthesized using retrograde solubility-driven crystallization. Additionally, methylammonium lead bromide (MAPbBr3) and cesium lead iodide (δ-CsPbI3) MCs are prepared through a sonochemical process, employing low-grade PbX2 (X = I & Br) precursors and an eco-friendly green solvent (γ-Valerolactone). The study encompasses an analysis of the structural, optical, thermal, elemental, and morphological characteristics of FAPbI3, MAPbBr3, and CsPbI3 MCs. Upon analysing phase stability,a phase transition in FAPbI3 MCs is observed after 2 weeks. To address this issue, a powder-based mechanochemical method is employed to synthesize stable mixed cation perovskite powders (MCPs) by subjecting FAPbI3 and MAPbBr3 MCs with varying concentrations of CsPbI3. Furthermore, the performance of mixed cation perovskites are examined using the Solar Cell Capacitance Simulator (SCAPS-1D) software. The impact of cesium incorporation in the photovoltaic characteristics is elucidated. All mixed cation absorbers exhibited optimal device performance with a thickness ranging between 0.6-1.5µm. It's worth noting that the MCPs exhibit impressive ambient stability, remaining structurally intact and retaining their properties without significant degradation for 70 days of ambient exposure.

Solar Radiation Forecasting: A Systematic Meta-Review of Current Methods and Emerging Trends

Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of this source of energy. The need to optimise energy systems, ensure power continuity, and balance energy supply and demand is driving the continuous development of forecasting methods and approaches based on meteorological data or photovoltaic plant characteristics. This article presents the results of a meta-review of the solar forecasting literature, including the current state of knowledge and methodological discussion. It presents a comprehensive set of forecasting methods, evaluates current classifications, and proposes a new synthetic typology. The article emphasises the increasing role of artificial intelligence (AI) and machine learning (ML) techniques in improving forecast accuracy, alongside traditional statistical and physical models. It explores the challenges of hybrid and ensemble models, which combine multiple forecasting approaches to enhance performance. The paper addresses emerging trends in solar forecasting research, such as the integration of big data and advanced computational tools. Additionally, from a methodological perspective, the article outlines a rigorous approach to the meta-review research procedure, addresses the scientific challenges associated with conducting bibliometric research, and highlights best practices and principles. The article’s relevance consists of providing up-to-date knowledge on solar forecasting, along with insights on emerging trends, future research directions, and anticipating implications for theory and practice.

Pyro‐Phototronic Circularly Polarized Light Detection Based on Deuterated L‐Alanine Doped Triglycine Sulfate's Bulk Photovoltaic Effect

AbstractIn this study, a detector is developed using deuterated L‐alanine doped triglycine sulfate (DLATGS) crystals capable of detecting circularly polarized light (CPL) and various polarization states. As a primary pyroelectric detection crystal, DLATGS has exhibited notable optical responses to both linearly and circularly polarized light during the tests, demonstrating a favorable polarization ratio of 3.86 and an anisotropic factor of 0.529. The research discovers the broad‐spectrum bulk photovoltaic (BPVE) characteristics in DLATGS, highlighting its potential for CPL detection. By integrating linear and circular bulk photovoltaic effect theories (LBPV and CBPV), the crystal's ability to differentiate between various polarization modes, including left‐/right‐handed polarized light, is confirmed. The BPVE and pyro‐phototronic coupling responses is characterized, laying a theoretical foundation for a rare pyroelectric effect‐based multifunctional polarization detector. The overall consistency of phenomena and theoretical framework bridges the gap between theoretical predictions and experimental validation. This work not only advances the understanding of DLATGS crystals but also sets the stage for further exploration into chiral materials and the development of TGS‐type crystals in future photoelectronic detectors.

Boosting prairie dog optimizer for optimal planning of multiple wind turbine and photovoltaic distributed generators in distribution networks considering different dynamic load models

Deploying distributed generators (DGs) supplied by renewable energy resources poses a significant challenge for efficient power grid operation. The proper sizing and placement of DGs, specifically photovoltaics (PVs) and wind turbines (WTs), remain crucial due to the uncertain characteristics of renewable energy. To overcome these challenges, this study explores an enhanced version of a meta-heuristic technique called the prairie dog optimizer (PDO). The modified prairie dogs optimizer (mPDO) incorporates a novel exploration phase inspired by the slime mold algorithm (SMA) food approach. The mPDO algorithm is proposed to analyze the substantial effects of different dynamic load characteristics on the performance of the distribution networks and the designing of the PV-based and WT-based DGs. The optimization problem incorporates various operational constraints to mitigate energy loss in the distribution networks. Further, the study addresses uncertainties related to the random characteristics of PV and WT power outputs by employing appropriate probability distributions. The mPDO algorithm is evaluated using cec2020 benchmark suit test functions and rigorous statistical analysis to mathematically measure its success rate and efficacy while considering different type of optimization problems. The developed mPDO algorithm is applied to incorporate both PV and WT units, individually and simultaneously, into the IEEE 69-bus distribution network. This is achieved considering residential, commercial, industrial, and mixed time-varying voltage-dependent load demands. The efficacy of the modified algorithm is demonstrated using the standard benchmark functions, and a comparative analysis is conducted with the original PDO and other well-known algorithms, utilizing various statistical metrics. The numerical findings emphasize the significant influence of load type and time-varying generation in DG planning. Moreover, the mPDO algorithm beats the alternatives and improves distributed generators' technical advantages across all examined scenarios.

Systematic Engineering of Near-Infrared Small Molecules Based on 4H-Cyclopenta[1,2-b:5,4-b']dithiophene Acceptors for Organic Solar Cells.

Nonfullerene acceptors (NFAs) have emerged as tremendous materials, efficiently advancing bulk-heterojunction organic solar cells (OSCs) technology. Unlike their fullerene counterparts, NFAs offer the unique advantage of finely tunable electronic energy levels and optical characteristics, which correspond to substantial enhancement in power conversion efficiency of OSCs. Herein, we have introduced a new series of near-infrared NFAs (AY1-AY8) to advance this technology further. Our research deeply investigates the structure-property relationship and thoroughly explores the optical, optoelectronics, photophysical, and photovoltaic characteristics of a synthetic reference molecule (R) and the modeled AY1-AY8 NFAs series. We performed advanced quantum chemical simulations using density functional theory (DFT) and time-dependent DFT methods. Additionally, we also estimated key geometric characteristics such as frontier molecular orbitals, hole-electron overlap, density of states, molecular electrostatic potential, molecular excitation and binding energies, transition density matrix, and reorganizational energy of electrons and holes and compared them with those of a synthetic reference molecule (R). Our findings show that all designed materials (AY1-AY8) exhibit red-shift absorption, improved electronic charge mobility, and low binding and excitation energies compared to R. Notably, these designed materials (AY1-AY8) display significantly narrower electronic energy gaps (E g 1.89-1.71 eV), indicating enhanced charge shifting from the highest occupied molecular orbital to lowest unoccupied molecular orbital and broadening of the absorption spectrum. Moreover, we also revealed a comprehensive study of the donor/acceptor complex of PTB7-Th/AY8 to understand charge shifting between donor and acceptor molecules. Therefore, we strongly recommend this designed (AY1-AY8) series to the experimentalists for the future development of highly efficient OSC devices.

Multifunction realization in MoS2/WS2/h-BN heterojunction: Integrated self-powered high-performance photodetection, visualization, nonvolatile memory, and synaptic simulation

Nowadays, efficient performance, functional diversification, device miniaturization and systematic integration are the trends for developing new electronic information technology. However, photodetectors with only optoelectronic detection functions cannot satisfy the growing demands of the multifunction required in single devices. This paper presents a MoS2/WS2/h-BN van der Waals heterojunction device realizing multifunctional applications which integrated self-powered high-performance photodetection, visualization, nonvolatile memory, and synaptic simulation. The heterojunction achieves a high responsivity of 9.28 A/W, an excellent specific detectivity of 6.1×1012 Jones, a large external quantum efficiency of 2358 %, a considerable on/off ratio of 7×105 and an ultrafast response time of 0.6 μs at 1 V bias under 488 nm laser irradiation. Besides, the photodetector shows excellent photovoltaic characteristics with a short-circuit current of 0.22 μA and an open-circuit voltage of 0.34 V. Moreover, the device also shows a favorable optical response to 532 and 633 nm lasers. The device also realizes visualization and can be used as an imaging sensor. In addition, the device integrates nonvolatile memory function due to the charge storage effect of h-BN and h-BN/SiO2 interface. Furthermore, biological synaptic functions, such as the memory process, short- and long-term plasticity, and double pulse facilitation, are also successfully simulated. This work realizes the high-performance and multifunctional applications of MoS2/WS2/h-BN device based on a new strategy of utilizing h-BN as a heterojunction substrate.

Advancing optoelectronic characteristics of Diketopyrrolopyrrole-Based molecules as donors for organic and as hole transporting materials for perovskite solar cells

A stable and efficient hole-transport material (HTM) is crucial for high-performance perovskite solar cells (PSCs). A 2,2′,7,7′-tetrakis[N,N-di(4-methoxyphenyl)amino]-9,9′-spirobifluorene (Spiro-MeOTAD) being used widely to prepare highly efficient PSCs. However, Spiro-MeOTAD has some limitations due to its complex synthesis, which increases its cost, and it also requires dopants to improve its performance. Therefore, we designed thirteen unique small-molecule-based HTMs (MK1-MK13), which are easy to synthesize, highly cost-effective, and don’t require dopants to prepare efficient PSCs. Their electrical and optical properties are then investigated theoretically using advanced quantum chemical approaches. The designed molecules showed lower energy gaps and improved optical and optoelectronic characteristics because of the improved phase inversion geometry. The detailed photo-physical and optoelectronic characteristics have been studied using density functional theory (DFT) and time-dependent (TD-DFT) calculations. Moreover, we investigated the impact of holes and electrons and the density of states, open-circuit voltage, frontier molecular orbital, transition density matrix, and other structural and photovoltaic characteristics of these materials. Among these, the MK3 molecule possesses the much narrower optical band gap of 1.04 eV and absorbance (λ max) of 684 nm, respectively. In addition, a profound investigation of the MK3/PC61BM blend shows excellent charge transfer at the acceptor–donor interface. Therefore, our proposed technique is necessary for generating appropriate photovoltaic materials for efficient optoelectronic devices and is helpful in further advancing the field.

Decentralised control strategy for effective utilisation of distributed community energy storage in PV-rich LV distribution network

Integrating a high-capacity residential-scale photovoltaic (PV) system into a low-voltage (LV) network results in voltage rise. Conversely, voltage drops occur during periods of high demand. Furthermore, PV generation characteristics vary with seasonality and daily weather conditions, complicating voltage rise and drop management. On the other hand, community energy storage (CES) emerges as a solution for future community energy management. This study presents an application of distributed CES to effectively manage voltage rise and drop, addressing a prominent challenge accompanying the widespread adoption of PV. However, upon introducing the CES and its accompanying energy capacity, the control strategy must effectively incorporate the utilisation of the CES’s available capacity year-round. In brief, CES control should adapt to the characteristics of PV by charging the CES during high PV generation. It should also release active power to meet high demand by discharging the CES. This will enable both voltage management and effective CES capacity utilisation in response to PV variations due to seasonality and daily weather conditions. The goal mentioned above can be effectively accomplished by forecasting PV output and using the data to adapt to PV characteristics in a centralised manner. However, due to the challenges associated with centralised control, the present paper proposes a decentralised control algorithm that determines charging and discharging power rates for distributed CES, aligning with the PV and load characteristics in an LV distribution network. The proposed control framework consists of two stages: the first stage regularly updates power references based on clear-sky PV profiles, active power measurements at the LV transformer, and CES active power and energy level. The second stage is activated to mitigate voltage transient caused by fast-moving clouds and small increments in solar irradiance, load between consecutive updates of the first stage. To illustrate and validate the concept, a 13-bus LV distribution network is used, and the proposed control algorithm is implemented on a co-simulation platform that combines MATLAB with a real-time digital simulator.

Superior performance of rubidium/acetate co-doped CsPbIBr2 perovskite solar cells: A comprehensive analysis

The development of remarkably resourceful, effectively phase stable, and highly crystalline-minimal defect perovskite (PVT)-based solar cells (PSCs) is extremely needful for the existing energy requisites. The strategy of incorporating appropriate dopants such as metal cations/anions into inorganic PVT lattices has been recognized as a successful methodology to attain aforesaid PSCs. On that account, this analysis reveals the implication of rubidium (Rb)/ acetate (Ac) (cation/anion) co-doping upon cesium (Cs)-based, bromine (Br)-rich PVT: CsPbIBr2 against undoped equivalent. The thorough numerical study on recommended structure: FTO/SnO2/CsPbIBr2/CuAlO2/Ag specifying recombination profiles and performance parameters with respect to layer parameters of PVT absorber and charge transport layers conveyed supreme behavior from co-doped devices. It is evidenced that highest efficiency of 16.79 % is accomplished from Rb/Ac co-doped PSC for PVT electron mobility of 25 cm2V-1s−1. The work reveals the progress in photovoltaic characteristics of inorganic PSCs through the involvement of multi-source co-doping.

A Combination of INC and Fuzzy Logic-Based Variable Step Size for Enhancing MPPT of PV Systems

The significance of using the variable step Incremental Conductance (INC) technique in Maximum Power Point monitoring (MPPT) of photovoltaic (PV) systems resides in its capacity to improve the efficiency of energy conversion. This is accomplished through the constant measurement and comparison of incremental changes in current and voltage, precisely monitoring the maximum power point amidst changing environmental conditions. This traditional INC-MPPT approach has two primary disadvantages. Initially, it employs a predetermined scaling factor that necessitates human adjustment. Furthermore, it adjusts the inclination of the PV characteristics curve to modify the step size. This implies that even little changes in PV module voltage will have a substantial impact on the total step size. As a result, it shifts the operating point away from the intended reference maximum power point. The objective of this work is to improve the efficiency of traditional INC by overcoming the constraints associated with step size modifications. This is achieved by using a fuzzy logic (FL) technique to adjust the step size adaptively in response to environmental changes. The presented INC-FL-MPPT successfully achieves MPPT for a PV system under enhanced steady-state and transient-state settings. The results demonstrate the superiority of the suggested approach compared to three distinct MPPT strategies, namely Perturb and Observe (PO), Classical INC, and PO-FL technique.

Computational study on metal-free dye-sensitized solar cells utilizing heterocyclic derivative π-spacers with open and fused rings: Design and analysis of D-π-A-π-A dye sensitizers

A series of metal-free dye-sensitized solar cells featuring a D-π-A-π-A configuration is devised, employing various heterocyclic derivative π-spacers in both open and fused configurations. Employing DFT and TD-DFT methods, the optoelectronic and photovoltaic characteristics of the dye are scrutinized. To evaluate the impact of diverse heterocyclic spacers, structural parameters such as distance and dihedral angle, alongside thermodynamic metrics including electron injection efficiency (ΔGinject), regeneration efficiency (ΔGreg), light harvesting efficiency (LHE), open-circuit photovoltage (VOC), and short-circuit current density (JSC) are assessed. Results indicate that selected dyes with open and fused configurations of heterocyclic π-spacers such as O-CNC-2, O-CNN-4, O-NNC-7, O-NNN-8, F-NNC-2, and F-NNN-1 exhibited superior electron density distribution, higher ΔGinject, lower ΔGreg, elevated VOC, and JSC compared to their counterparts based on open configurations. These D-π-A-π-A dyes can emerge as promising candidates for future applications in solar cells.

Optimization of the structural, optical, and photovoltaic characteristics of a novel ruthenium(III) complex as a photosensitizer for solar cells

A novel ruthenium(III) complex, [Ru(DAP)2(H2O)2]Cl3 (where DAP = 5,6-Diamino-1,3-dimethylpyrimidine-2,4(1H,3H)-dione), was synthesized for potential application as a photosensitizer dye in solar cell. The ruthenium complex was made and precipitated as violet crystals by reaction of K2[RuCl5H2O] with the ligand DAP, in an aqueous ethanol (1:1; v/v)). Elemental analysis, magnetic, thermal, X-ray diffraction, electron scanning microscope and spectroscopic techniques were used for physico-chemical characterizations. Additionally, the electrochemical properties were studied by cyclic voltammetry and voltammogram showed different peaks with different oxidation potentials confirming an extraordinary electrochemical property for the complex. The fabrication of nanostructured films of ruthenium(III) complex was achieved through the thermal evaporation technique, and from which optical and electrical characterizations were studied and interpreted. A solar cell hybridizing organic and inorganic materials, incorporating a ruthenium(III) complex and silicon, was fabricated. The current-voltage characteristic of this cell was measured, and from which the photovoltaic parameters were estimated. The solar cell exhibits a filling factor of 0.40 and an efficiency of 3.58 %.

OPTIMIZATION OF THE PEROVSKITE SOLAR CELL STRUCTURE

An experimental perovskite solar cell (PSC) with the structure Au/Spiro-MeOTAD/CH3NH3PbI3/PEDOT:PSS/ITO was fabricated. The measurements of main photovoltaic characteristics were provided. The current-voltage dependences (I-V curves) were measured conducted in the voltage range from -1V to 1V. During the measurements, the corresponding values were calculated of the short-circuit current density(Jsc) and open-circuit voltage(Uoc) were obtained as 1.23 mA/cm² and 0.19 V, respectively. Subsequently, an analytical model corresponding to this structure was formulated. For modeling the parameters of the perovskite solar cell, the Comsol Multiphysics environment was used, this environment is based on the finite element method. The relevant computations were provided to obtain the corresponding values of the short-circuit current density and open-circuit voltage as 3.29 mA/cm² and 0.2 V, respectively, with the maximum theoretically calculated power of this structure being 0.11 W. The experimental outcomes were juxtaposed with the predictions of the analytical computations, and the modeling results were empirically validated. An analytically accomplished model of the same structure was built by adding an electron transport layer (ETL). An organic material BCP (Bathocuproine) was used as an supplementary ETL layer. During the optimization of the PSC, the main datums were mathematically counted. Such values as the short-circuit current density of 10.17 mA/cm², open-circuit voltage of 1.2 V, and the maximum power value of Au/BCP/Spiro-MeOTAD/CH3NH3PbI3/PEDOT:PSS/ITO structure, which is 3.21 W were rated. A comparison of the volt-ampere characteristics of perovskite cells in dark and light modes was conducted for primary and optimized structures. The main parameters, obtained during the modeling of the experimental sample and subsequent model optimization, were compared. Specifically one of the key parameters of solar cell heterostructures the fill factor was evaluated and found to have increased from 16.52% to 25.00%, respectively. The light-sensitive behavior of the perovskite cell were visibly enhanced.

Optoelectronic and transport properties of Lead-Free halide based Na2AgTlZ6 (Z = Cl, Br, I) double perovskites for energy harvesting applications

The bandgap engineering and deliberate band edge manipulation of perovskites make them potential candidates for the photovoltaic industry. Here we theoretically investigate the structure, density of states, and photovoltaic and thermoelectric characteristics of Na2AgTlZ6 (Z = Cl, Br, I) using WIEN2k code. The incorporation of Br and I at the Cl site caused the increase in lattice constant which leads to the decrease in bulk modulus and Debye temperature. The computed values of Poisson (<0.26) and Pugh (<1.75) ratio verified their brittle nature. The bandgap analysis reveals direct bandgap nature and bandgap value lie in the visible region for parent composition and infrared and far infrared when Cl is replaced with Br and I. The density of state plots uncovers the shifting of energy states in valence and conduction bands towards the Fermi level with the increasing number of electrons in the halogens. The increase in the value of dielectric constant, refractive index, and shifting of peaks towards lower energy value is witnessed with atomic number of halogen atoms. The viability of these compositions for thermoelectric devices is further confirmed when electrical conductivity and Seebeck coefficient dependent Figure of merit and power factor are evaluated in the temperature range of 200–800 K. In addition, the anisotropic nature of studied compositions is explored through the computation of the modulus of elasticity including Young’s modulus, Shear modulus in addition to compressibility, and Poisson’s ratio.

Heat-Annealed Zinc Oxide on Flexible Carbon Nanotube Paper and Exposed to Gradient Light to Enhance Its Photoelectric Response.

Buckypaper (BP), a flexible and porous material, exhibits photovoltaic properties when exposed to light. In this study, we employed radio frequency (RF) sputtering of zinc oxide (ZnO) followed by rapid thermal annealing to enhance the photovoltaic response of BP. We investigated the impact of various sputtering parameters, such as the gas flow ratio of argon to oxygen and deposition time, on the morphology, composition, resistivity, and photovoltaic characteristics of ZnO-modified BP. Additionally, the photovoltaic performance of the samples under different illumination modes and wavelengths was compared. It was found that optimal sputtering conditions-argon to oxygen flow ratio of 1:2, deposition time of 20 min, and power of 100 watts-resulted in a ZnO film thickness of approximately 45 nanometers. After annealing at 400 °C for 10 min, the ZnO-modified BP demonstrated a significant increase in photocurrent and photovoltage, along with a reduction in resistivity, compared to unmodified BP. Moreover, under gradient illumination, the ZnO-modified BP exhibited a photovoltage enhancement of 14.70-fold and a photocurrent increase of 13.86-fold, compared to uniform illumination. Under blue light, it showed a higher photovoltaic response than under other colors. The enhancement in photovoltaic response is attributed to the formation of a Schottky junction between ZnO and BP, an increased carrier concentration gradient, and an expanded light absorption spectrum. Our results validate that ZnO sputtering followed by annealing is an effective method for modifying BP for photovoltaic applications such as solar cells and photodetectors.

Tracking deep-level defects in degrading perovskite solar cells with a multifactorial approach

In this work, we provide a mechanistic understanding of the degradation of perovskite solar cells in operation by focusing on methylammonium lead triiodide (CH3NH3PbI3 or MAPbI3) and tracking the evolution of electronic defects via photo-induced current transient spectroscopy (PICTS). Moreover, we also record the degradation of its photovaltaic characteristics over time under various electric load and temperature conditions. Using PICTS, we found that bands of trap states, initially highly localized deep within the band gap of the perovskite, widened over the exposure period. This effect was exacerbated with increasing temperature. Further, using the design of experiment methodology for this multifactorial study, we found that two interaction factors (temperature× load & temperature× time) were significant in the degradation of the perovskite cells, validating the importance of our holistic approach. Through these observations, we establish a mechanistic link between deep-level traps and photovoltaic characteristics.

Multi-Task neural network model considering low power output risk for short-term photovoltaic forecasting

As the proportion of installed photovoltaic power generation continues to increase, low output under the influence of large-scale weather systems has an increasingly significant influence on the power grid. There is an urgent need to improve photovoltaic power generation forecasting accuracy and reduce the risk of insufficient output in forecast results. To this end, a multi-task neural network model considering low power output risk (LPOMTN) for short-term photovoltaic forecasting is proposed. First, a numerical weather forecast encoder based on multi-scale CNN-Attention is established, which can extract multi-time scale photovoltaic output characteristics. Then a low-output day prediction module based on parallel CNN decoding and a photovoltaic low-output process prediction module based on the clear-sky model and LSTM were established. The latter uses the prediction results of the former as input, and the two modules perform training modeling in a multi-task learning manner to strengthen the model’s sensitivity to low-output states and improve the accuracy of low-output process predictions. The calculation example results show that LPOMTN has higher average forecasting accuracy for power output processes compared to methods such as XGBoost.

Enhancement of p-CuO/n-ZnO Heterojunction Photovoltaic Characteristics by Preparation Route and Sn Doping

Enhancement of p-CuO/n-ZnO Heterojunction Photovoltaic Characteristics by Preparation Route and Sn Doping

Modified Rime-Ice Growth Optimizer with Polynomial Differential Learning Operator for Single- and Double-Diode PV Parameter Estimation Problem

A recent optimization algorithm, the Rime Optimization Algorithm (RIME), was developed to efficiently utilize the physical phenomenon of rime-ice growth. It simulates the hard-rime and soft-rime processes, constructing the mechanisms of hard-rime puncture and soft-rime search. In this study, an enhanced version, termed Modified RIME (MRIME), is introduced, integrating a Polynomial Differential Learning Operator (PDLO). The incorporation of PDLO introduces non-linearities to the RIME algorithm, enhancing its adaptability, convergence speed, and global search capability compared to the conventional RIME approach. The proposed MRIME algorithm is designed to identify photovoltaic (PV) module characteristics by considering diverse equivalent circuits, including the One-Diode Model (ONE-DM) and Two-Diode Model TWO-DM, to determine the unspecified parameters of the PV. The MRIME approach is compared to the conventional RIME method using two commercial PV modules, namely the STM6-40/36 module and R.T.C. France cell. The simulation results are juxtaposed with those from contemporary algorithms based on published research. The outcomes related to recent algorithms are also compared with those of the MRIME algorithm in relation to various existing studies. The simulation results indicate that the MRIME algorithm demonstrates substantial improvement rates for the STM6-40/36 module and R.T.C. France cell, achieving 1.16% and 18.45% improvement for the ONE-DM, respectively. For the TWO-DM, it shows significant improvement rates for the two modules, reaching 1.14% and 50.42%, respectively. The MRIME algorithm, in comparison to previously published results, establishes substantial superiority and robustness.