International Journal of Photoenergy
 Journal metrics
Acceptance rate46%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore3.800
Journal Citation Indicator0.430
Impact Factor2.113

Sizing Algorithm for a Photovoltaic System along an Urban Railway Network towards Net Zero Emission

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 Journal profile

International Journal of Photoenergy publishes original research and review articles focused on all areas of photoenergy, including photochemistry and solar energy utilization.

 Editor spotlight

Chief Editor, Giulia Grancini, is based at the University of Pavia, Italy. Her current research work aims at solving the stability and toxicity issues of developing multi-dimensional hybrid interfaces as lego-bricks for a new efficient, stable, and environmentally-friendly solar technology.

 Special Issues

We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

A Short-Term Solar Photovoltaic Power Optimized Prediction Interval Model Based on FOS-ELM Algorithm

Solar energy conversion efficiency has improved by the advancement technology of photovoltaic (PV) and the involvement of administrations worldwide. However, environmental conditions influence PV power output, resulting in randomness and intermittency. These characteristics may be harmful to the power scheme. As a conclusion, precise and timely power forecast information is essential for the power networks to engage solar energy. To lessen the negative impact of PV electricity usage, the offered short-term solar photovoltaic (PV) power estimate design is based on an online sequential extreme learning machine with a forgetting mechanism (FOS-ELM) under this study. This approach can replace existing knowledge with new information on a continuous basis. The variance of model uncertainty is computed in the first stage by using a learning algorithm to provide predictable PV power estimations. Stage two entails creating a one-of-a-kind PI based on cost function to enhance the ELM limitations and quantify noise uncertainty in respect of variance. As per findings, this approach does have the benefits of short training duration and better reliability. This technique can assist the energy dispatching unit list producing strategies while also providing temporal and spatial compensation and integrated power regulation, which are crucial for the stability and security of energy systems and also their continuous optimization.

Research Article

Fabrication of p-NiO/n-TiO2 Solar Device for Photovoltaic Application

Energy demand is increasing globally owing to population growth. Solar cell development has gained considerable attention because of its potential to provide everyone with sustainable, affordable, clean, and globally accessible energy. A heterojunction solar device for photovoltaic applications was developed in this study, using nickel oxide (NiO) as the p-type and titanium oxide (TiO2) as the n-type. The material chosen was motivated by the affordability, availability, and performance compared to existing silicon that is more efficient but less affordable and available. The TiO2 and NiO2 were synthesised and characterised before the deposition and characterisation of the solar cells. The characterisation was carried out using Fourier transform infrared spectroscopy (FTIR), Transmission Electron Microscopy (TEM), scanning electron microscopy (SEM), EDX, X-ray Diffraction (XRD), and a four-point probe. The deposition parameters were fine-tuned to achieve optimum optoelectronic properties for the solar device. The final device exhibited an open-circuit voltage of 370 mV, a current density of 1.7 mA, and solar cells efficiency of 3.7.

Research Article

Epoxy/Silicone Blend Loaded with N-Doped CNT Composites: Study on the Optoelectronic Properties

Thin films of epoxy/silicone loaded with N-CNT were prepared by a method of sol-gel and deposited on ITO glass substrates at room temperature. The properties of the loaded monolayer samples (0.00, 0.07, 0.1, and 0.2 wt% N-CNTs) were analyzed by UV-visible spectroscopy. The transmittance for the unloaded thin films is 88%, and an average transmittance for the loaded thin film is about 42 to 67% in the visible range. The optical properties were studied from UV-visible spectroscopy to examine the transmission spectrum, optical gap, Tauc verified optical gap, and Urbach energy, based on the envelope method proposed by Swanepoel (1983). The results indicate that the adjusted optical gap of the film has a direct optical transition with an optical gap of 3.61 eV for unloaded thin films and 3.55 to 3.19 eV for loaded thin films depending on the loading rate. The optical gap is appropriately adapted to the direct transition model proposed by Tauc et al. (1966); its value was 3.6 eV for unloaded thin films and from 3.38 to 3.1 eV for loaded thin films; then, we determined the Urbach energy which is inversely variable with the optical gap, where Urbach’s energy is 0.19 eV for the unloaded thin films and varies from 0.43 to 1.33 eV for the loaded thin films with increasing rate of N-CNTs. Finally, nanocomposite epoxy/silicone N-CNT films can be developed as electrically conductive materials with specific optical characteristics, giving the possibility to be used in electrooptical applications.

Research Article

Comprehensive Methodology to Evaluate Parasitic Energy Consumption for Different Types of Dual-Axis Sun Tracking Systems

A dual-axis sun tracking system is an essential strategy to maximize the optical efficiency of harnessing solar energy. However, there is no significant study yet to optimize the net performance of the photovoltaic (PV) or concentrator photovoltaic (CPV) system equipped with a dual-axis sun tracking system. Parasitic energy loss associated with the power consumption of the sun tracking system is one of the major concerns for the solar industrial players. To address this issue, a comprehensive methodology has been developed to evaluate the yearly cumulative range of motion for dual-axis sun tracking systems in the cases of with and without fixed parking positions across the latitudes ranging from 45°N to 45°S. The parasitic energy consumptions have been investigated for three selected types of dual-axis sun tracking systems, i.e., the azimuth-elevation sun tracking system (AE-STS), polar dual-axis sun tracking system (PD-STS), and horizontal dual-axis sun tracking system (HD-STS). The simulated results indicate that the dual-axis sun tracking system with the nonfixed parking (or stow) position has lower yearly cumulative parasitic energy consumption with respect to the sun tracking system with a fixed parking position. Lastly, our simulation result has shown that the parasitic energy consumption of the sun tracking is relatively smaller to that of the electrical energy generated by the concentrator photovoltaic system with the ratio between 0.15% and 0.29% for AE-STS, between 0.15% and 0.30% for PD-STS, and between 0.17% and 0.35% for HD-STS.

Research Article

Research on Online Defect Detection Method of Solar Cell Component Based on Lightweight Convolutional Neural Network

The defects of solar cell component (SCC) will affect the service life and power generation efficiency. In this paper, the defect images of SCC were taken by the photoluminescence (PL) method and processed by an advanced lightweight convolutional neural network (CNN). Firstly, in order to solve the high pixel SCC image detection, each silicon wafer image was segmented based on local difference extremum of edge projection (LDEEP). Secondly, in order to detect the defects with small size or weak edges in the silicon wafer, an improved lightweight CNN model with deep backbone feature extraction network structure was proposed, as the enhancing feature fusion layer and the three-scale feature prediction layer; the model provided more feature detail. The final experimental results showed that the improved model achieves a good balance between the detection accuracy and detection speed, with the mean average precision (mAP) reaching 87.55%, which was 6.78% higher than the original algorithm. Moreover, the detection speed reached 40 frames per second (fps), which meets requirements of precision and real-time detection. The detection method can better complete the defect detection task of SCC, which lays the foundation for automatic detection of SCC defects.

Research Article

Investing in Renewable Energy and Energy Efficiency in Palestinian Territories: Barriers and Opportunities

The main objective of this paper is to identify the renewable energy (RE) and energy efficiency (EE) policy and regulatory risks and barriers in the Palestinian Territories (PT). An accurate insight into the market structure and normative frameworks for RE and EE investments in the PT is performed. For this purpose, a survey has been conducted through two questionnaires and interviews addressed to public decision-makers and local and foreign sectoral companies to study the market confidence in the field of renewable energy sources (RES) and EE. The questionnaire was designed to investigate the attractiveness of RE and EE in the country by directly involving the various market players and to identify what could encourage or hinder investment. RE and EE are, in fact, a valid response to the needs of the PT to guarantee independence and security of supply, ensure access to energy throughout the territory, and reduce emissions. The climate-related issues are listed in the Palestinian political agenda. National subsidies and grants are offered for investment in RES and EE but are still the main barriers. Developments towards further utilization of RES are in progress continually. Marketing campaigns are stimulating the production of RE and EE promotion. RES and EE laws and regulations are continually issued.

International Journal of Photoenergy
 Journal metrics
Acceptance rate46%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore3.800
Journal Citation Indicator0.430
Impact Factor2.113
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.