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This paper studies the coordinated use of smart inverters with legacy voltage regulating devices to help increase the energy savings from conservation voltage reduction (CVR) in distribution systems with high photovoltaic penetration. Two voltage optimization algorithms are developed to evaluate the CVR benefit by considering two types of smart inverter functions: aggregated reactive power control and autonomous volt/VAR control. In each algorithm, smart inverters are coordinately controlled with the operation of legacy voltage regulating devices including load tap changers and capacitor banks. Both algorithms are tested on representative utility distribution system models. Simulation results demonstrate that the proposed algorithms can achieve around 1.8-3.6% energy savings when only using legacy voltage regulating devices and an additional 0.3-0.9% when adding smart inverters.

Cooling enhances the energy conversion efficiency and output of photovoltaic (PV) panels. In this work, the effects of natural convection, forced convection, and evaporative cooling on the performance of polycrystalline PV panels were investigated. The output and efficiency of a cooled PV panel were monitored and compared to those of an uncooled PV panel under the same conditions. The cooling was conducted using an insulated channel installed below a PV panel. Natural convection cooling was investigated for various channel air gaps (H = 30, 60, 90, and 120 mm). Natural convection currents in the cooling channels were capable of cooling the panel with wide air gaps. In forced convection cooling, the air was introduced by fans installed at the bottom opening of the cooling channel with various air velocities (ua = 1, 2, and 3 m/s). Evaporative natural convection cooling was performed by a wetted fabric along the lower surface of the cooling channel, whereas evaporative forced convection cooling by pushing air along the wetted lower surface of the channel. The experimental data showed that the panel efficiency and output increased due to cooling. The experimental results of natural convection cooling revealed that the use of an air gap of 120 mm to cool the solar panel contributed to an increase in the panel daily energy production and efficiency by 1.7% and 1.2%, respectively. For forced convection cooling, using air at a speed of 3 m/s increased the daily energy production by 4.4% and the efficiency by 4%. Natural convection evaporative cooling increased the daily energy production and the efficiency by 3.6% and 2.7%, respectively. Forced convection evaporative cooling contributed, at a speed of 2 m/s, to an increase in the daily energy production by 3.8% and an increase in efficiency of 3.8%.

Sun-oriented solar power production with sunlight-based vitality plays an important role. In reality, untimely or innovative countries gracefully take a move forward. When oil is used for power era, it contributes to a rise in poisoning and greenhouse gases. This creates natural complications. Another human need for existence can be filled by using numerous sun- oriented developments in vitality, the planet can still prevent worldwide problems which can also serve to decrease pollution at the same time. In far-off areas where communities of citizens do not approach electricity photovoltaic frameworks are added many any administration offices have taken the amounts of action to allow creativity in sun-driven vitality to be used for power production. Single axis monitoring devices are discussed in this article. This analysis supports the findings. In comparison with the static systems, the single axis monitoring system is more accurate. In either scenario, a single axis monitoring system is simpler to accomplish in cost and adaptability viewpoints than a static one.

The main purpose of this paper is to observe the effect PV variation of solar temperature and irradiance on different conditions and on the inverter output for a grid-connected system. Majorly temperature& solar irradiation effects the performance of a grid connected inverter, also on the photo-voltaic (PV) electric system. The simulation based study was carried out in order to evaluate the variation of inverter output with the variation of solar temperature and irradiance with the variation in climate. The analysis of Grid-connected inverter and their performance at various seasons and conditions is investigated. Solar power plant for a year. In solar power plant efficiency of inverter is also considered to calculate overall losses so, the inverter efficiency and plant performance are considered in this paper using MAT Lab software. In summer season the inverter performed efficiency is decreased because of peak temperature value and slightly increased with the increase in irradiance.

The effect of planar photonic crystal on CZTS/CdS solar cell is systematically investigated. The reflective properties of PhC ARC which consists of the periodic stack of ZnO and HfO2 with two numbers of periods having quarter wavelength thickness are analyzed. Similarly, the DBR having periodic stacks of HfO2 and ZnO dielectric layers with four numbers of periods having half wavelength thickness in CZTS/CdS solar cells are explored. Moreover, the results of the photovoltaic properties of CZTS/CdS solar cells are also analyzed. The outcome of the findings obtained from the computation using the transfer matrix method are very well agreeable with the recent literature. The planar (ZnO /HfO2)2 PhC ARC and (ZnO/HfO2)4 DBR has been expected to provide significant improvement in the performance of CZTS/CdS solar cells.

The control of a microgrid is quite challenging thus this work implements a robust and fast control technique based on circular limited cycle oscillator frequency locked loop with inner loop filter (CLO-FLL-WIF) for switching operation between an islanded and the grid-connected modes. This microgrid combing solar PV (Photovoltaic) generation, SyRG (Synchronous Reluctance Generator) for pico-hydro generation, and the battery, which works in both standalone and grid-connected modes while feeding local loads uninterruptedly. The output power conversion of a PV array is influenced by irradiation of solar PV array and has low efficiency, therefore, a MPPT (Maximum Power Point Tracking) namely an INC (Incremental Conductance) method is used. In the implemented system, the interfaced power converter is gated in the grid-connected mode and islanded mode using same enhanced second order generalized integrator with a modified frequency locked loop (ESOGI-MFLL) control method. The comparative results validate that the response of ESOGI-MFLL in comparison to the existing control algorithm, is faster under load and generation perturbations. The implemented control techniques are used for fundamental extraction of load component of voltage and current for assessment of reference currents with their respective phases of synchronization while maintaining the required IEEE power quality standard-519. Simulated results of a microgrid for grid-tied PV-BES-SyRG are obtained in MATLAB/Simulink platform to demonstrate its performance.

This article proposes a supervised learning approach for centralized localization of faults in microgrids with radial configuration that can operate in grid-connected or islanded mode. The key concept is to identify faults by learning and analyzing the features of voltage and current disturbances detected by a microgrid central protection unit. Two algorithms are developed that determine fault indices and transient features for simulation-based training, classification, and backup protection purposes. The proposed data-driven approach is effective under high penetration of distributed energy resources (DERs), and is robust under microgrid topology variations. Moreover, it requires few sensors (two for radial structure) and is easy to implement, yet provides high degree of reliability. The performance and accuracy of the developed approach are verified through extensive simulations of low-voltage microgrids that incorporate different types of DERs, including wind and solar photovoltaic systems.

A novel single-switch coupled-inductor switched-capacitor (CISC) high step-up converter is proposed which has a boost-type input structure allowing an improved input current ripple compared to other leading CISC converters. This is important for sustainable energy applications such as photovoltaic (PV) cells and fuel cells where high current ripple can degrade performance or lifetime. Though large input filters can be added between the energy source and the boost converter to smooth a pulsed converter input current, the proposed converter naturally has a more moderate current ripple, reducing the need for additional filtering. With regards to the coupled inductor, the leakage inductor energy is recycled without using an extra clamped circuit, and core utilization is high. The detailed theoretical operation is presented and an experimental prototype (200 W, 36 V to 48 V input, 400 V output) achieves a maximum efficiency of 97.1%.

Solar energy is widely available in nature and electricity can be easily extracted using solar PV cells. A fuel cell being reliable and environment friendly becomes a good choice for the backup so as to compensate for continuously varying solar irradiation. This paper presents simple control schemes for power management of the DC microgrid consisting of PV modules and fuel cell as energy sources and a hydrogen electrolyzer system for storing the excess power generated. The supercapacitor bank is used as a short term energy storage device for providing the energy buffer whenever sudden fluctuations occur in the input power and the load demand. A new power control strategy is developed for a hydrogen storage system. The performance of the system is assessed with and without the supercapacitor bank and the results are compared. A comparative study of the voltage regulation of the microgrid is presented with the controller of the supercapacitor bank, realized using a traditional PI controller and an intelligent fuzzy logic controller.

This article investigates the coordinated allocation of battery energy storage system (BESS) and soft open point (SOP) in high photovoltaic penetrated distribution network incorporating demand response (DR), and conservation voltage reduction (CVR) schemes. To do so, a new two-stage coordinated optimization framework has been developed for integrated planning of BESS and SOP considering DR and CVR schemes. In stage 1, optimal location and size determination of BESS and SOP devices has been carried out simultaneously. Whereas, stage 2 performs the optimal operation of BESS and SOP corresponding to CVR and DR schemes. The objective of the proposed methodology is to minimize the total investment and operating cost of BESS and SOP devices. Besides, it includes the cost of purchased power from substation, cost of energy not served and cost of $\text{CO}_2$ emission. Meanwhile, to address high-level uncertainties related to PV generation and load demands, a stochastic module has been adopted, which produces several scenarios by Monte Carlo simulation at each hour. Furthermore, K-means clustering technique has been employed to determine the reduced scenarios with high quality and diversity. The proposed framework has been implemented on IEEE 33-bus distribution system for different cases and solved by using hybrid optimization solver. The test results demonstrate the effectiveness of proposed framework in improving the system efficiency, enhancing the flexibility, reliability and reducing carbon emission footprint of distribution systems.

In this paper, four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance. The deployable solar array model consists of a rigid main-body, two panels and four key mechanisms, containing torsion spring mechanism, closed cable loop mechanism, latch mechanism and attitude adjustment mechanism. Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation, respectively. The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model. The latch time, stabilization time, maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works. To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties, a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints. Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected. Besides, increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system. That may provide some references for optimization design of deployable space mechanisms considering clearance joints.

The optimal configuration of energy sources in a nanogrid is important due to intermittency of renewable energy sources and variability in load. An oversized configuration gives the maximum power supply availability to load. However, this would result in higher cost of electricity and excess power generation. Since, dc nanogrids are seldom connected to central grid, the surplus power cannot be sold back. On the other end, economical configuration leads to undersized system, i.e., insufficient generation to meet the load demand. Hence, in general, a multiobjective Grey-Wolf optimization-based optimal sizing algorithm is proposed to get optimal configuration for the area of photovoltaic (PV) panel installation, rating of the wind energy conversion system and capacity of battery energy storage system. Furthermore, there is need for real-time energy management in dc nanogrid due to uncertainty in power generation and load forecasting. A virtual energy storage (VES)-based energy management is proposed in this article to enhance the availability of power supply. The VES concept models the high thermal inertia loads such as air-conditioner and refrigerator analogous to electrochemical battery. A priority-based strategy in VES algorithm turn-on and turn-off thermal loads during the power deficit and surplus renewable generation receptively. The VES-based energy management does not compromise the comfort of customers and does not change the usual number of switching in thermal loads.

The present work carries about a unique experimental investigation in the thermal management and cooling realms of the Photovoltaic (PV) panels under the most harsh environmental conditions. The performance of the heat sink and thermal storage heat sink techniques were analysed amongst the three passively cooled PV panels. Moreover, the efficacy of the immersion and coolant thermal properties was evaluated and discussed for the four actively cooled Photovoltaic Thermal (PVT) collectors. Even though, it was found that the heat sink-based PV panel configuration is more performant relatively compared to the PCM heat sink based-PV one since a drop of ten-degree in PV cell temperature was recorded, but still, the heat dissipation rate is not enough to withstand the severe mechanical and electrical degradation challenges under the harsh environmental climate of Saudi Arabia. For the actively cooled PVT collectors, it was found that the immersion technique protects the PV panel from the hot spot apparatuses and lead to better heat dissipation uniformity. The heat pipes based-PVT collector immersed in regular water has recorded the optimal temperature distribution and maximum temperature drop by 53% relatively compared to best passively cooled configuration. With ethylene glycol, engine oil, and active cooling without immersion, the steady-state PV temperature has been reduced relatively compared to a passively cooled PV panel by about 48%, 25%, and 21%, respectively.

The exploration of low bandgap perovskite material to approach Shockley-Queisser limit of photovoltaic device is of great significance, but it is still challenging. During the past few years, tin–lead (Sn-Pb) mixed perovskites with low bandgaps have been rapidly developed, and their single junction solar cells have reached power conversion efficiency (PCE) over 21%, which also makes them ideal candidate as low bandgap sub-cell for tandem device. Nevertheless, due to the incorporation of unstable Sn2+, the stability issue becomes the vital problem for the further development of Sn-Pb mixed perovskite solar cells (PSCs). In this review, we are dedicated to give a full view in current understanding on the stability issue of Sn-Pb mixed perovskites and their PSCs. We begin with the demonstration on the origin of instability of Sn-Pb mixed perovskites, including oxidation of Sn2+, defects, and interfacial layer induced instability. Sequentially, the up-to-date developments on the stability improvement of Sn-Pb mixed perovskites and their PSCs is systematically reviewed, including composition engineering, additive engineering, and interfacial engineering. At last, the current challenges and future perspectives on the stability study of Sn-Pb mixed PSCs are discussed, which we hope could promote the further application of Sn-Pb mixed perovskites towards commercialization.

With the characteristics of module-level maximum power point tracking, module-level monitoring, and panel shut- off , single-phase cascaded H-bridge (CHB) inverter has outstanding advantages applied to household photovoltaic (PV) power generation occasion. However, unbalanced output powers among PV panels is an inherent problem of single-phase CHB PV inverter, which will make the H-bridges (HBs) with higher powers overmodulation, resulting in deteriorated grid current and even system instability. Aiming at this issue, this article proposes a power adaptive control strategy, which divides system operation into three modes, and calculates modulation waveforms by using different methods in different modes. By flexibly adjusting the transmission power of HBs in different modes, all the HBs are able to avoid overmodulation, and single-phase CHB PV grid-connected inverter can still operate normally even if the maximum powers among PV panels are seriously unbalanced. The effectiveness of the proposed control strategy is verified by simulation and experimental results.

A rational design of efficient low-band-gap non-fullerene acceptors (NFAs) for high-performance organic solar cells (OSCs) remains challenging; the main constraint being the decrease in the energy level of the lowest unoccupied molecular orbitals (LUMOs) as the bandgap of A-D-A-type NFAs decrease. Therefore, the short current density (Jsc) and open-circuit voltage (Voc) result in a trade-off relationship, making it difficult to obtain efficient OSCs. Herein, three NFAs (IFL-ED-4F, IDT-ED-4F, and IDTT-ED-2F) were synthesized to address the above-mentioned issue by introducing 3,4-ethylenedioxythiophene (EDOT) as a π-bridge. These NFAs exhibit relatively low bandgaps (1.67, 1.42, and 1.49 eV, respectively) and upshifted LUMO levels (-3.88, −3.84, and −3.81 eV, respectively) compared with most reported low-band-gap NFAs. Consequently, the photovoltaic devices based on IDT-ED-4F blended with a PBDB-T donor polymer showed the best power conversion efficiency (PCE) of 10.4% with a high Jsc of 22.1 mA cm−2 and Voc of 0.884 V among the examined NFAs. In contrast, IDTT-ED-4F, which was designed with an asymmetric structure of the D-π-A type, showed the lowest efficiency of 1.5% owing to the poor morphology and charge transport properties of the binary blend. However, when this was introduced as the third component of the PM6:BTP-BO-4Cl, complementary absorption and cascade energy-level alignment between the two substances could be achieved. Surprisingly, the IDTT-ED-4F-based ternary blend device not only improved the Jsc and Voc, but also achieved a PCE of 15.2%, which is approximately 5.3% higher than that of the reference device with a minimized energy loss of 0.488 eV. In addition, the universality of IDTT-ED-2F as a third component was effectively demonstrated in other photoactive systems, specifically, PM6:BTP-eC9 and PTB7-Th:IEICO-4F. This work facilitates a better understanding of the structure–property relationship for utilizing efficient EDOT-bridged NFAs in high-performance OSC applications.

Solar energy is the centre of attention and major need of the world. The advancement in the photovoltaic devices plays the key role in the path of solar energy applications. The progress in the perovskite solar cell technologies in the direction of their theoretical power conversion efficiency necessitates elusive control above the carrier dynamics all over the whole device. In the present investigation, a comparative study via SCAPS simulation has been done for the optimization of the device in the light of high power conversion efficiency of organic–inorganic perovskite-based photovoltaic solar cells. Perovskite absorber layers CH3NH3PbI3 and CH3NH3SnI3 are sandwiched in between the TiO2 as electron transport layer (ETL) and spiro-OMeTAD as hole transport layer (HTL) to design the hetrostructures for the simulation. We have achieved enhancement in the power conversion efficiencies of both the devices as compared to the reported experimental and theoretical studies previously.

Outstanding material properties allowed perovskite solar cells’ power conversion efficiencies (PCEs) exceed 25% within a decade, demonstrating the most rapid increase rate in PCEs among all the existing photovoltaic (PV) technologies. Despite such significant progress perovskite technology commercialization requires further enhancement in device performance. Here, we report a strategy for optimizing interfacial quality of the perovskite solar cells (PSCs). The interfacial layer between the electron transport layer (ETL) and the perovskite absorber were optimized by interface engineering technique via preparing the ETL consisted of Tin(IV) oxide (SnO2) quantum dots (QDs), SnO2 nanoparticle (NP) and a passivation layer based on Poly(methyl methacrylate): [6,6]-phenyl-C61-butyric acid methyl ester (PMMA:PCBM). It was demonstrated that the PSCs with a single-layer ETL made of SnO2 QDs exhibit strong I-V hysteresis, while the application of a triple-layer ETL effectively suppresses the hysteresis due to the optimization of ETL/perovskite interface. This work demonstrated the effective protocol which can substantially improve the performance of PSCs and eliminate the I-V hysteresis.

Some revised versions of the analog ensemble (AnEn) algorithm to improve its performance when predicting rare events of solar power production are presented. Rare events are considered both extremely cloudy situations and clear sky conditions with very low aerosol concentrations. In these cases, the solar power production can be respectively unusually low or high, making it more difficult to find good analog dates in a historical archive of past forecasts. The lack of suitable quality analogs determines conditional biases from the AnEn when predicting these rare events. Here, an application of the AnEn to predict solar power generated by two photovoltaic plants located in Kuwait is presented. The modified versions of the AnEn are compared to the standard algorithm. We focus the verification of the AnEn’s performance over the rare conditions outlining the improvements achieved with the new AnEn models.

Cu(In,Ga)Se2 (CIGS) is a promising candidate to replace crystalline silicon solar cells and dominate the photovoltaic market in the future. Alkali elements such as sodium (Na), potassium (K), rubidium (Rb), and Cesium (Cs) are commonly accepted as indispensable parts to boost cell efficiencies of CIGS thin-film solar cells. Therefore, a comprehensive understanding of alkali effects on the electronic and chemical properties of the CIGS layer as well as the underlying mechanisms is of paramount importance for achieving high-performance solar cells. This paper reviews the development process and incorporation pathways of alkalis and then overviews the roles of different alkali elements and their effects on CIGS cells in detail. Furthermore, the unsolved problems and future development prospects are also proposed. Overall, the understanding and development of widely adopted alkali-fluoride post-deposition treatments (PDTs) are still underway, and together with newly updated research, it will likely enable the CIGS technology to make the conversion efficiency closer to its theoretical limit.

Lead free and environment friendly, light absorbing material is in high demand for the photovoltaic perovskite solar cell devices. The double perovskite La2NiMnO6 have the centre of attention for this demand. The present review is focused to discuss briefly the progress and challenges in the structural and magnetic properties of La2NiMnO6 in bulk, nano and thin film phases. The structural changes of La2NiMnO6 are highly interesting and have the direct correlation with the magnetic properties. On the basis of these transformations in the structure, efforts have been made to discuss several scientific progresses into technical novelties. This short review article is critically dedicated on reviewing the progresses, openings, and upcoming challenges in perovskite solar cell devices.

A few simple structures are formed by incorporating high gain cells to the conventional boost converter. The cells such as passive switched inductors, switched capacitor, switched inductor/capacitors are inserted in the traditional boost converter to boost up the voltage gain of the converter. The suggested high gain cells can be added to any conventional topologies like buck-boost, sepic, cuk, zeta, luo converters to enhance the gain and other key features of the converters. The operating principle and theoretical analysis of all the proposed converters are discussed. Design of good feedback controller is essential for fast dynamic response and good regulation. Hence, the mathematical model of the topologies is presented. Finally, the step-up topologies are compared to highlights their significant features. In addition to that, Life cycle analysis of the Photovoltaic (PV) system is studied in this paper. The results from the theoretical study are validated by simulating the circuit with MATLAB software. Simulation model is developed for 500 W, 200 V which is most suitable for rooftop PV application

In order to meet the world's future energy demand, alternative renewable green energy supplies must be widely promoted. Among all DERs, the most prevalent is Solar PV for a number of important reasons. In this study, the authors analyze several elements of the Single-Phase Solar Photovoltaic Rooftop System with MATLAB. In order to analyze the characteristics of the output current, a new grid synchronization methodology has been devised. For maximum power tracking, the INC control technique has been adopted. The output of the solar DC power system has been synchronized with the grid through hysteresis current loop control. Extensive testing verifies the practicality of the proposed power grid model and promising outcomes and results.

The age of modernization comes with its own set of flaws, which has to be mitigated as sooner as possible for a sustainable future. It is a well-established fact that the need for energy in this age of technology is at stake due to the incessant use of carbon based fossil fuels. Fossil fuels in themselves are not enough. They are very much likely to be exhausted sooner than expected. Therefore, a new clean and renewable alternative has to be adopted which could be able to meet the energy demand. Hydrogen Energy may be one of the most viable and suitable alternative ways to mitigate the energy demand, without affecting the environment. The project work is focused on the optimization of the key operating parameters of the electrolyser coupled with a solar photovoltaic (PV) system for hydrogen production using the Taguchi technique. In this work ten operating parameters have been selected using an L27 (310) orthogonal array for optimization. Based on the 27 orthogonal arrays, it was found that the maximum hydrogen production is 319.35 Ncm3/hr. After applying the Taguchi technique, found that the maximum hydrogen production was 645.89 Ncm3/hr., which gives 50.56% increment as compared to the highest value of production obtained from orthogonal array.

Single-component organic solar cells (SCOSCs) with high stability and simplified fabrication process are supposed to accelerate the commercialization of organic photovoltaics. However, the types of photo-active materials and photovoltaic performance of SCOSCs are still far lagging behind the bulk-heterojunction type organic solar cells (BHJ OSCs). It is still an arduous task to introduce new photo-active materials into SCOSCs, aiming to improve the efficiencies of SCOSCs. One feasible way is to construct double-cable polymers with new structures and tune conformation, morphology and mobility for the improvement in power conversion efficiencies (PCEs). Hence, in this work, we constructed a new double-cable polymer PBTT-BPTI by introducing fused core 5,7-dibromo-2,3-bis(2-ethylhexyl)benzo[此处b,c斜体么? 正文中斜了]dithiophene-4,8-dione (TTDO) into the main backbone and benzo[ghi]-perylene triimide (BPTI) unit into the side chain. Both of the two units show strong electron-withdrawing property, which are expected to broaden absorption spectra and enhance intermolecular interaction. The double-cable polymer exhibited a broad absorption in the range of 300-700 nm with an optical band gap (Eg) of 1.79 eV. The PCE of PBTT-BPTI-based SCOSCs was 2.15%, which may be limited by the unconstructed efficient electron transporting channels.

The aim of this paper is to further deepen the use of a very robust mathematical technique in the analysis of data. The Principal Component Analysis (PCA) method is used to analyze the performance of three PV systems and to determine the correlation between performance parameters and meteorological variables. The three systems are based on Silicon monocrystalline (2 kWp), polycrystalline (1.82 kWp) and amorphous (1.55 kWp) PV modules. The performance indicators used are the parameters described in the international standard IEC 61724. The evaluation of parameters such as performance ratio, final yield and capacity factor were found to be 79.08%, 1876.48kWh/kWp/year and 38.46% for polycrystalline, 71.13%, 1688.97kWh/kWp/year and 38.99% for monocrystalline and 78.89%, 1866.42kWh/kWp/year and 33.02% for amorphous, respectively. The projection of the data showed that more than 87% of the information is retained and presented in 2D space. The correlation between temperature and performance of mc-Si, pc-Si, and a-Si systems is −21%, −12.5% and −42.8%, respectively.

Small-scale PV generation has become popular with residential customers in several jurisdictions with high solar radiation, as an alternative to improve their carbon footprint and reduce their electricity bills. However, massive deployment of such distributed generation is creating a particular and undesirable shape in the net demand, which deepens at hours of peak solar PV injections at noon and suddenly rises towards the evening, known as the “duck curve". Hence, this paper investigates the use of pre-cooling strategies in residential households to mitigate the duck-curve effects. To this aim, appropriate thermal models and simulations of houses are first developed and carried out to demonstrate the technical feasibility of pre-cooling in a house with a typical configuration, based on the Smart Residential Load Simulator (SRLS) developed at the University of Waterloo. Then, an aggregation technique is proposed to evaluate the effects on a large grid of different penetration levels of PV, and pre-cooling approaches to manage the duck-curve in California and Texas, concluding that such techniques are capable of substantially flattening the system net demand curve.

The main contribution of this paper is proposing a new approach for retrieving the five parameters of the single diode equivalent model (SDM) of photovoltaic cells/modules including the series and shunt resistances. The least square method is used as an error minimization technique for fitting the non-linear transcendental model equation of the solar panel to the measured I–V characteristics. Newton Raphson method is applied to solve the system of five non-linear equations which represent the error of each parameter. Initial guess values are calculated with an optimised algorithm depending on information extracted from the same measured data. MATLAB programming script was used in all implementation steps. This approach is useful for a wide variety of applications where the five SDM parameters have to be determined from the measured curves, particularly, for self-fabricated cells/modules or in case of no available datasheet. One of the strengths of this method is the higher level of accuracy because of the absence of mathematical simplifications and physical assumptions. The method was validated on different types of PV devices, including a crystalline silicon cell, a polycrystalline module, and an amorphous module by using measurement data obtained at a wide range of solar irradiance conditions and temperatures.

Accurate estimation of residential solar photovoltaic (PV) generation is crucial for the power distribution and demand response program implementation. Currently, most distributed PVs are installed behind-the-meters (BTMs), and are thus invisi-ble to the utilities. The existing methods separate the BTM solar generation from the available net load in a centralized manner as-suming that all data are accessible to utilities. However, this can cause privacy issues, since the data are owned by different utilities and they may be unwilling to share their data. To this end, a novel method is proposed for disaggregating community-level BTM so-lar generation using a federated learning-based Bayesian neural network (FL-BNN), which can preserve the privacy of utilities. Specifically, a Bayesian neural network (BNN) is designed as the probabilistic energy disaggregation model with the ability to cap-ture uncertainties. The BNN training process is extended into a decentralized manner based on the federated learning framework. To enable the model customized for each community, the layers of BNN are categorized into shallow and deep layers, and a layerwise parameter aggregation strategy is proposed to update the model. Both community-specific features and community-invariant fea-tures can be learned. The effectiveness of the proposed method is validated on a publicly available dataset.

In the present study, Pure and (1 wt% and 4 wt%) Gadolinium (Gd3+) doped TiO2 nanoparticles were developed with a hydrothermal method, and dye sensitized solar cells were fabricated using them as an electron transfer material. The anatase phase and structural property of pure and Gd3+ doped TiO2 nanoparticles were examined using XRD analysis. Energy Dispersive X-ray analysis (EDAX) confirmed the presence of titania nanoparticles and UV–Vis absorption spectroscopy was used for the investigation of the optical properties of synthesized photocatalysts. The photovoltaic performance of Gd3+:TiO2 based solar cells is improved compared to un-doped TiO2 based solar cell. The power conversion efficiency of the solar cells on Gd3+:TiO2 increased to 4.88%, which is higher than that of the solar cells based on un-doped TiO2.

In this study, a thermodynamic and economic analysis of a synthetic fuel production facility by utilizing the hydrogenation of CO2 captured from biogas is carried out. It is aimed to produce methanol, a synthetic fuel by hydrogenation of carbon dioxide. A PEM electrolyzer driven by grid-tie solar PV modules is used to supply the hydrogen need of methanol. The CO2 is captured from biogas produced in an actual wastewater treatment plant by a water washing unit which is a method of biogas purification. The required power which is generated by PV panels, in order to produce methanol, is found to be 2923 kW. Herein, the electricity consumption of 2875 kW, which is the main part of the total electricity generation, belongs to the PEM system. As a result of the study, the daily methanol production is found to be as 1674 kg. The electricity, hydrogen and methanol production costs are found to be $ 0.043 kWh−1, $ 3.156 kg−1, and $ 0.693 kg−1, respectively. Solar availability, methanol yield from the reactor, and PEM overpotentials are significant factors effecting the product cost. The results of the study presents feasible methanol production costs with reasonable investment requirements. Moreover, the efficiency of the cogeneration plant could be increased via enriching the biogas while emissions are reduced.

Charging the electric vehicles through the use of solar PV systems is a major hurdle in today's era. In the present work, a system is designed for charging Electric bikes at workplaces like schools, colleges, offices, etc. To ensure a reliable charging system, a standalone solar PV system with a battery bank based energy storage unit is employed. It can be seen from the present work that the electric bike at different voltage configurations i.e., 12 V, 24 V, and 36 V, can be charged efficiently. The irradiance level is varied in a way to show a real-life effect that occurs during a summer day. To depict this, irradiance level is assumed to rises from 300 W/m2 to 1000 W/m2 and decline again to 300 W/m2 during the process. The DC bus voltage is successfully maintained constant at a level of 48 V in all three cases. The contribution of the study is the application of a robust solar PV based off-grid design for charging electric bike at the workplaces.

In the present work, a decision-making framework in the form of TOmada de Decisao Interativa Multicriterio (TODIM) has been employed to identify the best microgrid scenario for a given location. The study has considered a total of eight microgrid scenarios that have been appraised with due consideration to economic and environmental metrics. Net project cost and cost of energy have been considered as the economic metrics while renewable energy fraction and greenhouse gas emissions as environmental metrics. HOMER has been used to carry out the optimization analysis and hence the aforementioned metrics. TODIM methodology is then applied to rank the considered microgrid scenarios. An inclusive evaluation shows that the hybrid renewable energy based microgrid system encompassing photovoltaic (PV), diesel generator (DiG), battery (BAT), fuel cell (FC), wind turbine (WT) and convertor (CONV) turns out to be the best scenario for the considered area.

A novel photovoltaic thermal air (PVTa) system with semi length fins in the downstream portion of the air channel was tested experimentally for its performance capability for the generation of hydrogen in the present work. Fins are passive devices used to overcome the main detrimental effect of reduced power output due to photovoltaic panel heating. For this purpose, 2 semi length fin configurations namely longitudinal fin and wavy fin were placed in second half length of the channel in the direction of air flow. To compare the impact of PVTa systems with semi lengthened fins in hydrogen generation, the performance study of PV and PVTa system assisted hydrogen generation were also conducted. The experiments were conducted at the site of Tiruchirappalli district, Tamilnadu state, India having latitude and longitude of 10.82 and 78.70 respectively during March–June 2019 from 9 a.m. to 4 p.m. on clear and sunny days. The results indicated PVTa system with semi length wavy fins yielded maximum generation of hydrogen among the 4 cases of PV assisted hydrogen generation techniques considered. It was observed that downstream located longitudinal and wavy fins provided enhanced PV panel cooling which increased the current supply to the electrolyzer unit. The hydrogen generation rate was 13.5, 12.1, 9.5 and 7.8 ml/min for PVT with wavy fins, longitudinal fins, PVT and PV respectively. Keywords: Solar PV, fins, hydrogen, heat transfer.

Cu2O is a promising p-type semiconductor for low-cost photovoltaics and transparent optoelectronics. However, low-cost and low-temperature fabrication of Cu2O films with good transport properties remains challenging, thus limiting their widespread adoption in devices. Here, we report Cu2O thin films of 20–80 nm thickness with hole mobility up to 92 cm2V−1s−1 using atmospheric-pressure spatial atomic layer deposition at temperatures below 260 °C, from a copper (I) hexafluoro-2,4-pentanedionate cyclooctadiene precursor. Raman spectroscopy indicates the presence of copper split vacancies and shows that the high hole mobility can be correlated to a low concentration of shallow acceptor defects. The optical bandgap of deposited films can be tuned between 2.08 eV and 2.5 eV, depending on the deposition temperature. All-oxide semitransparent Cu2O/ZnO solar harvesters are fabricated, showing efficiency values comparable to devices that incorporate much thicker Cu2O layers. Our work provides a promising approach towards cost-efficient, all-oxide solar harvesters, and for other (opto)electronic devices. Semiconducting Cu2O is attractive for photovoltaic and optoelectronic devices, though balancing high hole mobility with low-cost fabrication is challenging. Here, Cu2O thin films with high hole mobility of 92 cm²V−1s−1 are deposited in air, and applied in a semi-transparent solar harvester.

The morphology development of polymer-based blends, such as those used in organic photovoltaic (OPV) systems, typically arrests in a state away from equilibrium-how far from equilibrium this is will depend on the materials chemistry and the selected assembly parameters/environment. As a consequence, small changes during the blend assembly alter the solid-structure development from solution and, in turn, the final device performance. Comparing an open-cage ketolactam fullerene with the prototypical[6,6]-phenyl-C61-butyric acid methyl ester in blends with poly[2,5-bis(3-hexadecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT), we demonstrate that experimentally established, non-equilibrium temperature/composition phase diagrams can be useful beyond rationalization of optimum blend composition for OPV device performance. Indeed, they can be exploited as tools for rapid, qualitative structure-property mapping, providing insights into why apparent similar donor:acceptor blends display different optoelectronic processes resulting from changes in the phase-morphology formation induced by the different chemistries of the fullerenes.

Many cities across the world are committing to deep decarbonisation efforts. While solar photovoltaics (PV) will play a critical role in this pursuit, the role of rooftop and facade-integrated PVs within the urban landscape is yet to be fully understood. This work presents an analysis into the solar energy harvesting potential of PVs integrated as building rooftops, walls, and windows at various spatial resolutions that range from city to building scale within the City of Melbourne, Australia, as a contemporary case study. It further investigates the relationship between calculated electricity production from such PVs with the urban morphology, seasonal variation and the measured electricity consumption by the local distribution network service providers. The results indicate that PV rooftops are responsible for the largest share of the city’s solar energy potential. However, for individual blocks with high densities of high-rise and glazed buildings, it is shown that the PV potential from windows becomes more prominent. The technical workflow presented here will enable different cities to facilitate decision-making on the PV implementation in urban environments.

To study the internal flow characteristics of the photovoltaic pump under the transient change of solar radiation, the simulation algorithm of the photovoltaic pump system was established by MATLAB/Simulink and CFD for the first time and the results were validated by the test. Firstly, the change rule of pump flow rate and rotation speed under transient solar radiation was obtained by Simulink. Then the results of the change rule were transformed into the boundary condition of CFD by CEL function and the transient flow field in the photovoltaic pump was obtained. The internal flow characteristics and pressure pulsation in the pump were analyzed when the solar radiation increases or decreases transiently. The results demonstrate that the numerical calculation can provide accurate prediction for the characteristics of internal flow in the pump. The numerical results are closed to the experimental results, the minimum error of pressure is 0.93% and the maximum error is 1.78%. When the solar radiation increases transiently, the low pressure area at the impeller inlet gets larger obviously and the jet-wake at the impeller outlet becomes more obvious. The pressure pulsation in the impeller gradually increases and becomes stable after 0.6 s. The pressure from the impeller outlet to the guide vane outlet is stable at 123 kPa. When the solar radiation decreases transiently, the pressure in the impeller takes 1.6 s to be stable. Larger pressure pulsation occurs from the impeller outlet to the guide vane inlet and the maximum differential pressure is 10 kPa. Compared with the transient increase of solar radiation, the pressure in the impeller takes over 0.2 s to stabilize when the solar radiation transient decreases. Meanwhile, the results in this paper can provide references for other transient characteristics research. Highlight First, the relation between pump flow rate and rotation speed under transient solar radiation was obtained by Simulink. Then the results from Simulink were transformed to be the boundary condition of CFD by CEL function. The internal flow characteristics and pressure pulsation in the pump were analyzed under the instantaneous increase or decrease of the solar radiation.

In this study, analysis of photovoltaic (PV) string currents is performed to understand the behavior of the PV array under faults. The whole analysis is summed up in just two simple statements, and an algorithm is devised on the basis of these statements. The proposed algorithm can detect, classify and localize line-to-ground (L-G) & line-to-line (L-L) faults in the PV array. The proposed method can detect faults of any mismatch level and size of the PV array by using only one current sensor per string. It is also capable of working with finite fault-resistance as well as in the presence/absence of blocking diodes. To check the accuracy of the algorithm, it has been thoroughly tested through experimental setup.

Line-Line (LL) and Line-Ground (LG) faults may not be detected by common protection devices in PV arrays due to these faults are not detectable under high fault impedance and low mismatch level. In recent years, many efforts have been devoted to overcome these challenges using intelligent methods. However, these methods could not classify the type of faults and diagnose their severity. This paper proposes a novel and intelligent fault monitoring method to detect and classify LL and LG faults at the DC side of PV systems. For this purpose, the main features of Current-Voltage (I-V) curves under different fault events and normal conditions are extracted. The faults are categorized using the Hierarchical Classification (HC) platform. Later, the LL and LG faults are detected and classified by Machine Learning (ML) methods. The proposed method aims to reduce the amount of dataset which is required for the learning process and also obtain a higher accuracy in detecting and classifying the fault events at low mismatch levels and high fault impedance compared to other fault diagnostic methods. The experimental results verify that the proposed method precisely detects and classifies LL and LG faults on PV systems under the different conditions and severity with the accuracy of 96.66% and 91.66%, respectively.

The increasing number of electric vehicles (EVs) demands management solutions to deal with the impacts of EV charging on the efficiency of distribution grids. Many suggested methods are derived from analysis on laboratory-scale systems with declared data, which cannot be implemented for real networks. In this article, a two-step scheduling model is developed that effectively guides a large-scale EV fleet in microgrids without demanding a dynamic monetary scheme. The first step corresponds to prediction-based day-ahead optimal scheduling for large scale EVs, which minimizes the costs of electricity supply and EVs’ battery degradation. To avoid dimensional problems in calculations, an improved K-means clustering algorithm is presented to divide vehicles into different clusters. In the second step, online coordination is deployed based on an effective scoring system to encourage drivers to follow the first-step provided model. The proposed model is analyzed on a grid-connected microgrid with photovoltaic system integration. The problem (real) data are derived based on an estimate of the development process on the Ontario energy network over the next ten years. Results show that the introduced model can guarantee the accurate deployment of optimal charging/discharging schedules in large-scale systems.

The output power of solar photovoltaic (PV) system is intermittent in nature with a non-linear output voltage. This has peak power points in accordance with varying irradiation and temperature. Hence a Maximum Power Point Tracker (MPPT), which is power extraction technique is essential in PV power systems to ensure maximum power delivery for a given point of time. Thenonlinear power voltage curve gets more intense when shading of PV panels takes place, as the panels receive irregular and different solar irradiation, which alters the profile of power –voltage (P-V) curves. Due to the partial shading, the panels exhibit peculiar multiple power peaks instead of one single peak as in the case of uniform irradiation and as a result the conventional MPPT schemes could attain only local maxima and the global one. This research article proposes a new intelligent, bio inspired Meerkat optimization algorithm (MOA) which is capabale finding the global power peak and ensured maximum power delivery. ThisMOA MPPT technique is employed for a 120 W PV system and the versatility of the said scheme is tested by subjecting the PV panel for three different partially shaded conditions. The results reveal that the MOA exhibits fast tracking speed of with improved efficiencyof 99.8% when compared with particle swarm optimization (PSO) and differential evolution algorithm (DE)MPPT schemes.

Organic photovoltaics (OPVs) suitable for application in indoor lighting environments can power a wide range of internet of things (IoT) related electronic devices. The ternary structure has huge advantages in improving the photovoltaic performance of OPVs, including broadening the light absorption, improving the charge transport, manipulating the energy loss (Eloss) and so on. Herein, we use wide-bandgap photo-active materials, including the benzotriazole-based polymer donor (J52-F), chlorinated polymer donor (PM7) and A2-A1-D-A1-A2-structured acceptor (BTA3), to construct ternary OPVs for indoor light applications. Benefitting from the introduction of PM7 as the third component in J52-F:BTA3-based blend, a gratifying PCE of 20.04% with a high VOC of 1.00 V can be obtained under the test conditions with an illumination of 300 lx from an LED lighting source with a color temperature of 3000 K. The excellent device performance is inseparable from the matched spectrum, enhanced light absorption and the reduced Eloss, while the improved charge transport capability and suppression of carrier recombination also play an indelible role. Our work shows a potential material system to meet the requirement of devices applied under indoor light. Moreover, these findings demonstrate that designing multi-component OPVs is indeed a feasible way to further improve the performances of the photovoltaic energy conversion system for indoor applications.

This paper presents a novel DSO support tool with visualisation capability for forecasting network congestion in distribution systems with a high level of renewables. To incorporate the uncertainties in the distribution systems, the probabilistic power flow framework has been utilised. An advanced photovoltaic production forecast based on sky images and a load forecast using an artificial neural network is used as the input to the tool. In addition, advanced load models and operating modes of photovoltaic inverters have been incorporated into the tool. The tool has been applied in case studies to perform congestion forecasts for two real distribution systems to validate its usability and scalability. The results from case studies demonstrated that the tool performs satisfactorily for both small and large networks and is able to visualise the cumulative probabilities of nodes voltage deviation and network components (branches and transformers) congestion for a variety of forecast horizons as desired by the DSO. The results have also shown that explicit inclusion of load‐voltage dependency models would improve the accuracy of the congestion forecast. For demonstrating the applicability of the tool, it has been integrated into an existing distribution management system via the IoT platform of a DMS vendor, Atos Worldgrid.

Future of generation depends on the renewable energy resources due to lack of fuel and the problems of emissions. Photovoltaic (PV) system is a promising type of renewable energy resources. Non uniformity of irradiance, temperature variation, and partial shading conditions are the main disturbances associated with PV systems. Most of literatures focus on enhancing the PV performance and to achieve Maximum Power Point Tracing (MPPT) based on offline Optimization techniques. These techniques suffer from complicated mathematical burden, long computing time, and should be repeated for any change in the operating conditions/system parameters. This paper proposed a hybrid adaptive controller to improve the system performances under several disturbances, as well as to stabilize the operation of the MPPT. Thus, the proposed controller affords tight and accurate MPPT. The gains of the proposed controller are updated automatically with the variation in the operating conditions. The initialization of the proposed a hybrid adaptive controller is carried out utilizing the Sine-Cosine Algorithm (SCA). Finally, the proposed system is evaluated through comparison with one of the newly presented techniques that achieve accurate MPPT.

With the recent focus marked on energy efficiency and solar energy development, much research is being dedicated to the development of enhanced maximum power point tracking (MPPT) algorithms for photovoltaic applications. However, the main criteria with regard to tracking performances and circuit implementation are still considered as a major challenge under rapid varying weather conditions. In this paper, a T-S Fuzzy–integral backstepping-based hybrid MPPT technique is proposed for rapid, accurate and efficient tracking. The proposed technique enables reliable and stable operation under fast dynamic environmental changes. Besides, it is simple as it does not require extra atmospheric sensors. The theoretical analysis addressed in this study is verified through simulations via Matlab/Simulink and experimental outdoor tests. A comparison with different other MPPT techniques is provided to highlight the performances of the developed MPPT method.

It is critical to investigate the charge carrier gradient generation in semiconductor junctions with an asymmetric configuration, which can open a new platform for developing lateral photovoltaic and self-powered devices. This paper reports the generation of a charge carrier gradient in a 3C-SiC/Si heterojunction with an asymmetric electrode configuration. 3C-SiC/Si heterojunction devices with different electrode widths were illuminated by laser beams (wavelengths of 405, 521, and 637 nm) and a halogen bulb. The charge carrier distribution along the heterojunction was investigated by measuring the lateral photovoltage generated when the laser spot scans across the 3C-SiC surface between the two electrodes. The highest lateral photovoltage generated is 130.58 mV, measured in the device with an electrode width ratio of 5 and under 637 nm wavelength and 1000 μW illumination. Interestingly, the lateral photovoltage was generated even under uniform illumination at zero bias, which is unusual for the lateral photovoltage, as it can only be generated when unevenly distributed photogenerated charge carriers exist. In addition, the working mechanism and uncovered behavior of the lateral photovoltaic effect are explained based on the generation and separation of electron-hole pairs under light illumination and charge carrier diffusion theory. The finding further elaborates the underlying physics of the lateral photovoltaic effect in nano-heterojunctions and explores its potential in developing optoelectronic sensors.