Electrical Energy Research Articles

The increase in the temperature of photovoltaic (PV) cells is a critical factor that negatively affects the efficiency of converting solar radiation into electrical energy. This phenomenon not only reduces energy conversion efficiency but also causes damage to PV components, thereby preventing the achievement of the intended energy production goals. Moreover, the heating of PV modules has two significant impacts: first, a reduction in energy efficiency, and second, a decrease in the lifespan of the solar cells. Therefore, projects aimed at producing clean electrical energy using PV solar panels must consider the study of installation sites for PV solar plants and the impact of environmental conditions on panel performance. Given that an increase in PV cell temperature reduces their productivity, this study examines the impact of ambient temperature on the maximum temperature reached by a PV solar panel and analyzes the results. The results show that installing solar panels in harsh environments characterized by high temperatures, such as Ouarzazate in Morocco, can cause these panels to reach critical temperature thresholds of up to 115°C under high solar flux, which can lead to solar system failure and thus the failure of the entire project. In addition, the heating of photovoltaic modules has two major impacts: firstly, energy efficiency is reduced by around 0.44% for every 1°C increase, and overall efficiency is reduced from 16% to less than 10% under extreme conditions; secondly, solar cell life is shortened. Finally, this study highlights the importance of carrying out thorough climatic and environmental assessments before establishing solar photovoltaic power plants. It also highlights the importance of employing high-performance cooling systems or innovative technologies to reduce the impact of heat on photovoltaic panels. This approach is essential to ensure the longevity and efficiency of solar photovoltaic installations, and to achieve our ambitions for sustainable, green energy production.

The telecommunications sector is experiencing rapid growth, driven by the exponential rise in data transmission volumes. This demand has led to significant innovation in the Front-end-module (FEM), and particularly in the power amplifiers (PAs), requiring III-V group-based compound semiconductor materials, instead of traditional silicon-based technologies. ICT hardware manufacturing raises multiple sustainability concerns, including the intensive use of natural resources, significant waste generation, and the high consumption of electrical energy during production. These issues are further exacerbated by the rapid growth of the ICT market and the increasing shift toward non-silicon-based technologies. We address these issues in this paper through a comparative Life Cycle Assessment (LCA) of the environmental impacts associated with the fabrication of PAs based on different semiconductor technologies suited for user equipment applications (45RFSOI, GaN-on-Si HEMT, GaAs HBT). We show a substantially higher impact per cm² in terms of climate change (~1.6x higher) and resource depletion (~470x higher) for the market-dominant GaAs power amplifier compared to RFSOI and GaN-on-Si technologies. It is due to the GaAs wafer manufacturing and the usage of gold. In addition to LCA considerations, the integration of compound semiconductor materials introduces broader sustainability concerns, particularly with respect to resource scarcity, economic viability, and potential social implications. We explore these dimensions and highlight concerns related to gold usage in GaAs PA as well as different critical materials used in these RF technologies.

Abstract - The traditional power system's structure is rapidly evolving due to the shift towards electric vehicles (EVs) and renewable energy sources. With more electric vehicles on the road and solar and wind power plants joining the grid, it is getting increasingly challenging to predict the level of electrical usage due to the unpredictability of these technologies. Keep in mind that precise electric demand forecasting is essential for energy dispatch scheduling, grid stability, and the development of an efficient smart grid and EV model. The chaotic behaviour of today's electricity system and its non-linearity are beyond the scope of traditional statistical models and approaches. The ability to work with large volumes of data, exploit hidden data, and generate precise short-term (from minutes to weeks) and long-term (from months to years) load estimates has always been a strength of machine learning (ML) models. This research introduces a machine-learning technique to load forecasting in power systems combining renewable energy and EV. The approach has included a feature engineering process, a preparation phase, and the use of many machine learning algorithms, such as Random Forest, Support Vector Regression, and LSTM. According to the study, machine learning techniques improve forecasting accuracy when compared to conventional techniques. The study concludes by outlining the difficulties, restrictions, and potential avenues for further research in intelligent energy management. KeyWords: Machine learning, Load forecasting, Electric Vehicles, Renewable Energy, Smart Grid.

Abstract In the last few years, hybrid photovoltaic-thermal (PVT) collectors have become an attractive subject of research because of their ability to convert solar radiation into both electrical and thermal energies. Nonlinear relationships among their control variables, such as design parameters, climatic conditions, heat transfer fluid type, and electrical and thermal performances, require advanced modeling methodologies. This review examines the application of machine learning, especially artificial neural networks (ANNs), in photovoltaic-thermal systems. The paper begins with the state of the art in PVT systems, covering types, applications, recent developments, and more. It then presents a detailed analysis of ANN models, including the General Regression Neural Network (GRNN), Elman Neural Network (ENN), Radial Basis Function Network (RBFN), Multilayer Perceptron (MLP), and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). Furthermore, the review highlights the roles that these models have played in enhancing PVT system performance in previous studies and includes a literature analysis to identify research gaps in this field. According to the literature, ANNs are valuable tools for predicting and optimizing the performance of PVT collectors; however, further exploration of alternative ANN models in novel PVT designs, combined with optimization algorithms, is necessary.

Aiming to address the insulation and power supply challenges faced by electrical measurement in ultra-high voltage (UHV) environments, this study proposes and implements a nitrogen-vacancy (NV) center magnetic sensing system based on Power over Fiber (PoF) technology. The system adopts a high-voltage and low-voltage separation design, realizing the isolated transmission of electrical energy and the reliable recovery of measurement signals through an optical fiber link. The sensing unit on the high-voltage side is composed of NV center sensors, microwave excitation modules, and signal processing modules. Its power supply is provided by an independently developed high-power laser power converter (LPC) assembly via 830 nm optical fiber laser transmission. Under an optical input of 10 W, this assembly can achieve an electrical output of 4.88 W with a conversion efficiency of 48.9%. The experimental results show that the system can operate stably in a simulated UHV environment; by optimizing modulation parameters, the optimal magnetic measurement sensitivity reaches 6.1 nT/Hz1/2. This research provides a safe and reliable solution for the power supply and precise sensing of high-potential side equipment in UHV scenarios, and demonstrates the application potential of PoF technology in advanced sensing for power systems.

Introduction The valorization of agrifood residues into phenolic-rich extracts represents a promising approach to reduce residues and recover resources within a circular economy framework. Methods In this study, a comparative Life Cycle Assessment (LCA) of three extraction processes from agrifood by-products was conducted, namely date pits powder, citrus by-products, and cherry press-cake, producing phenolic-rich extracts to be applied in packaging, food, and cosmetic products. Using the ReCiPe 2016 method and a functional unit of 1 kg of total phenolic compounds (TPC), environmental impacts across 18 categories were assessed from a gate-to-gate perspective. Results and discussion The extracts from date pits powder, citrus by-products, and cherry press-cake showed TPC of 243 ± 5.6 mg GAE/g extract, 33.57 ± 0.07 mg GAE/g extract, and 445 ± 5 mg GAE/g extract, respectively. Results identified electrical energy consumption as the dominant contributor to environmental burdens in all scenarios, due to the energy-intensive steps of freeze-drying and chemical treatments. The citrus by-products scenario exhibited the lowest environmental impacts due to simplified processing and effective ethanol recovery, despite the total biomass valorization not being considered. In contrast, the cherry press-cake upcycling pathway showed the highest environmental footprint, primarily due to the cascade extraction method implemented. Date pits powder valorization presented an intermediate trend, where the high resource usage was balanced with the total valorization of the biomass to obtain cellulose nanocrystals (CNC). The findings highlight a critical trade-off between environmental performance and resource efficient use, emphasizing the need for the individuation of alternative unit operations, focusing particularly on the reduction of energy usage, to enhance the sustainability of biomass valorization processes in view of their industrial application.

This study investigates the synergistic interaction of CuO and SnO 2 in a heterostructure catalyst (CuO@SnO 2 ) for the conversion of C1 carbon dioxide (CO 2 ) reduction products to C2 products and its application in high‐performance aqueous Zn‐CO 2 batteries. This synergistic combination enhances the Faradaic efficiency (FE) for ethanol production from 12.5% to 41.8%, shifting the selectivity from C1 to C2 products. The flow‐type aqueous Zn‐CO 2 battery exhibits an ultrahigh power density of 6.5 mW cm −2 , demonstrates a high discharge voltage of 0.9 V, and maintains stable operation over 140 cycles, underscoring the catalyst's exceptional reversibility and durability. During battery discharge, the system achieves a FE of 36.86% for ethanol production. These results highlight the pivotal role of the CuO@SnO 2 synergy in optimizing CO 2 conversion efficiency while generating electrical energy. The findings advance the development of dual‐function energy storage systems that integrate renewable electricity generation with sustainable CO 2 utilization, paving the way for industrial‐scale applications.

ABSTRACT Although Sustainable Development Goals (SDGs) give significance to alleviating energy poverty (EP), the former literature is considerably silent on how renewable energy investments (REI), which are vital in providing clean and reliable energy and ensuring a sustainable development path, impact EP in China, one of the most prominent countries in renewable energy. Therefore, the primary objective of this study is to uncover time‐, frequency‐ and quantile‐based interactions between REI and EP in China from 2004 M1 to 2020 M6 using various EP indicators by utilising Wavelet Transform Coherence (WTC) and Quantile‐on‐Quantile Regression (QQR) as a baseline estimator, while Quantile Regression (QR) is utilised as robustness checks. The empirical results denote that (i) there is a time‐ and frequency‐dependent interaction between REI and EP. (ii) REI can alleviate EP by fostering access to primary energy, electricity and clean energy technologies. (iii) The EP‐alleviating impact of REI through increasing access to electricity is more dominant. (iv) Robustness checks denote that empirical findings are robust. Chinese policymakers could prevalently use REI as an effective tool for alleviating EP and achieving SDG‐7.

Abstract A hybrid piezoelectric-triboelectric vibration energy harvester for the intelligent bearing self-powered system is proposed. To address the problems of limited applications of battery-powered condition monitoring devices in the intelligent bearing's radially slotted outer ring structure. By collecting the bearing elastic vibration energy, converting it into electrical energy, and supplying it to the condition monitoring equipment, the self-powering of the intelligent bearing condition monitoring equipment can be realized. The energy harvester is based on a triangular single-crystal piezoelectric cantilever beam with double mass blocks, and two nanogenerators with limiting functions are organically integrated with the vibration direction of the cantilever beam. The composite co-generation of piezoelectric and triboelectric modes during vibration and limit collisions is realized. The space is effectively utilized and the output performance is improved. Meanwhile, the electromechanical coupling dynamic model of the energy harvester is established by using the centralized parameter method. The effects of different structures and dimensions on the intrinsic frequency and output voltage of the piezoelectric cantilever beam are analyzed by simulation. The accuracy of the electromechanical coupling dynamics model and simulation analysis is also verified through experiments. The experimental results show that the proposed hybrid piezoelectric-triboelectric vibration energy harvester can work effectively within the normal operating vibration acceleration range of 0~28.2 m/s2 of the intelligent bearing. At an acceleration of 2 m/s2, the maximum peak-to-peak values of the open-circuit output voltages of the piezoelectric and triboelectric units of the harvester are 1.28 V and 1.05 V respectively. At an acceleration of 20 m/s2, the maximum peak-to-peak values of the open-circuit output voltages of the piezoelectric and triboelectric units of the harvester are 2.85 V and 1.18 V respectively. As the vibration acceleration of the intelligent bearing increases, the response voltage amplitude also increases. However, no matter how the response voltage amplitude changes, the output voltage fluctuates around 3 V after the energy harvesting circuit.

The design of battery modules for Electric Vehicles (EVs) and stationary Energy Storage Systems (ESSs) plays a pivotal role in advancing sustainable energy technologies. This paper presents a comprehensive overview of the critical considerations in battery module design, including system requirements, cell selection, mechanical integration, thermal management, and safety components such as the Battery Disconnect Unit (BDU) and Battery Management System (BMS). We discuss the distinct demands of EV and ESS applications, highlighting trade-offs in cell chemistry, form factor, and architectural configurations to optimize performance, safety, and cost. Integrating advanced cooling strategies and robust electrical connections ensures thermal stability and operational reliability. Additionally, the paper describes a prototype battery module, a BDU, and the hardware and software architectures of a prototype BMS designed for a Hardware/Model-in-the-Loop framework for the real-time monitoring, protection, and control of battery packs. This work aims to provide a detailed framework and practical insights to support the development of high-performance, safe, and scalable battery systems essential for transportation electrification and grid energy storage.

Smart sensor networks play important roles in structural monitoring, health diagnosis, and data transmission. Given their extensive distributed energy requirements, piezoelectric energy harvesting, which aims to convert mechanical vibrational energy into electrical power, can serve as a viable alternative or supplement to power supplies owing to its compact size, high power density, and excellent stability. Piezoelectric energy harvesting involves three key components: piezoelectric materials responsible for mechanical-to-electrical energy conversion, mechanical structures enabling mechanical-to-mechanical energy transmission, and power-management systems used to efficiently extract electrical energy. For electromechanical conversion, state-of-the-art piezoelectric materials, including crystals, ceramics, polymers, and composites, are analyzed. Regarding mechanical energy transmission, the focus is on methodologies to achieve high power output, wide bandwidth, and multi-directional vibration capability. Several widely adopted electrical circuits are comprehensively reviewed in terms of power management. From an application perspective, practical energy harvesters are categorized into magneto-mechano-electric, fluid-based, biomechanical, and ultrasound-induced types. Additionally, future theoretical and practical challenges in piezoelectric energy harvesting are discussed.

Graphene has attracted growing interest as a platform for directly converting interfacial charge dynamics into electrical energy. While previous studies have demonstrated voltage generation from forced droplet motion on graphene, the electricity produced during spontaneous droplet condensation and evaporation remains largely unexplored. Furthermore, how microscale three-phase contact line dynamics influences variations in electricity generation has yet to be elucidated. Here, we explore an electricity generation mechanism driven by the spontaneous formation and disappearance of liquid–solid interfaces during microdroplet condensation and evaporation on monolayer graphene. Using in situ environmental scanning electron microscopy, we directly visualized the dynamic phase-change processes of water microdroplets on graphene and simultaneously measured the corresponding transient voltage signals in real time. Our measurements of advancing and receding contact angles reveal strong pinning effects that prevent the contact line from moving freely and significantly reduce voltage generation. We reveal an electricity generation mechanism driven by instantaneous charge redistribution during electric double layer (EDL) formation at the onset of condensation and EDL collapse during evaporation. This process occurs independently of the directional droplet movement, with measured peak voltages reaching 15 μV during condensation and 80 μV during evaporation. The observed voltage variation directly correlates with dynamic changes in the three-phase contact line. Through coupled analysis of microscale phase-change dynamics and transient electrical measurements, we reveal microscopic electricity generation mechanisms that fundamentally differ from macroscale directional droplet motion. Our work offers new guidelines for developing ultra-thin, high-efficiency hydrovoltaic devices that harness energy from spontaneous phase-change processes.

Fuel cells are highly efficient electrochemical devices that convert the chemical energy of fuel directly into electrical energy, while generating minimal pollutant emissions. In recent decades, they have established themselves as a key technology for sustainable energy supply in the transport sector, stationary systems, and portable applications. In order to assess their real contribution to environmental protection and energy efficiency, a comprehensive analysis of their life cycle, Life Cycle Assessment (LCA) is necessary, covering all stages, from the extraction of raw materials and the production of components, through operation and maintenance, to decommissioning and recycling. Particular attention is paid to the environmental challenges associated with the extraction of platinum catalysts, the production of membranes, and waste management. Economic aspects, such as capital costs, the price of hydrogen, and maintenance costs, also have a significant impact on their widespread implementation. This manuscript presents detailed mathematical models that describe the electrochemical characteristics, energy and mass balances, degradation dynamics, and cost structures over the life cycle of fuel cells. The models focus on proton exchange membrane fuel cells (PEMFCs), with possible extensions to other types. LCA is applied to quantify environmental impacts, such as global warming potential (GWP), while the levelized cost of electricity (LCOE) is used to assess economic viability. Particular attention is paid to the sustainability challenges of platinum catalyst extraction, membrane production, and end-of-life material recovery. By integrating technical, environmental, and economic modeling, the paper provides a systematic perspective for optimizing fuel cell deployment within a circular economy.

The present study aims to experimentally investigate pool boiling heat transfer characteristics, such as critical heat flux (CHF) and boiling heat transfer coefficient (BHTC), of pure distilled water (d-H2O) and functionalised graphene nanoplatelet (f-GnPs)–d-H2O nanofluids using a nichrome (Ni-Cr) test wire as the heating element. The distilled water (dH2O) and GnP (5–10 nm and 15 µm, Cheap Tubes, USA) were chosen as the base fluid and nanomaterial, respectively. The GnP was chemically functionalized and dispersed in dH2O using a probe sonicator. The nanofluids were characterized by measuring the zeta potential distribution and pH to ensure stability on day 1 and day 10 following preparation. The results show that the zeta potential values range from −31.6 mV to −30.6 mV, while the pH values range from 7.076 to 7.021 on day 1 and day 10, respectively. The novelty of the present study lies in the use of f-GnPs with a controlled size and stable nanofluid, confirmed through zeta potential and pH analysis, to determine the heat transfer behaviour of a Ni-Cr test wire under pool boiling conditions. The pool boiling heat transfer characteristics, such as CHF and BHTC, were observed using the fabricated pool boiling heat transfer test facility. Initially, the dH2O and f-GnP–dH2O nanofluids were separately placed in a glass container and heated using a pre-heater to reach their saturation point of 100 °C. The electrical energy was gradually increased until it reached the critical point of the Ni-Cr test wire, i.e., the burnout point, at which it became reddish-yellow hot. The CHF and BHTC were predicted from the experimental outputs of voltage and current. The results showed an enhancement of ~15% in the CHF at 0.1 vol% of f-GnPs. The present study offers a method for enhancing two-phase flow characteristics for heat pipe applications.

Controlling low-frequency noise and achieving multi-band sound insulation remain significant challenges and have long been hot topics in industrial research. This study introduces a novel multifunctional device based on the principles of acoustic metamaterials, which not only offers high-performance sound insulation but also converts low-frequency acoustic energy into electrical energy. Through an innovative design featuring multiple local resonance design, the proposed device effectively mitigates the impact of pre-tension on the membrane, while enabling efficient multi-band sound insulation that can be finely tuned by adjusting structural parameters. Experimental results demonstrate that the device achieves a maximum sound insulation of 40 dB and an average sound insulation exceeding 25 dB within the 1000 Hz frequency range. Moreover, by utilizing its local resonance property, a triboelectric nanogenerator (TENG) is specifically designed for low-frequency acoustic–electric conversion, maintaining high performance low-frequency sound insulation while simultaneously powering small scale electronic devices. This work provides a promising approach for multi-band sound insulation and low-frequency acoustic–electric conversion, offering broad potential for industrial applications.

The article presents the concept of an innovative residential facility designed in accordance with the principles of environmental friendliness, energy efficiency, and sustainable development. An architectural and engineering model is proposed that involves the comprehensive integration of autonomous water, energy, and heat supply systems, including technologies such as heat exchange water supply systems, rainwater collection and multi-stage filtration, a bioreactor for organic waste processing with methane release, a ventilation system with efficient heat recovery, and solar energy collectors for both electricity and thermal energy generation. The spatial arrangement of utilities and engineering networks is based on principles of optimizing natural energy flows, taking into account the orientation of the building relative to the cardinal directions, and aligning with the architectural logic and functionality of the internal layout. The overarching goal is to minimize dependence on external energy sources, reduce operational costs, and demonstrate the practical feasibility of implementing advanced energy-saving and environmentally responsible technologies in a residential setting. The purpose of the article is to develop and validate a model of an ecological individual residential building with a high degree of autonomy and a comprehensive integration of energy-efficient and water-saving systems that ensure long-term sustainability and a significant reduction in the load on centralized infrastructure. Conclusions. During the research, the effectiveness of integrating modern eco-technologies into both the design and practical operation of a residential building was confirmed. The developed eco-house model demonstrates a significant reduction in overall energy consumption, lower levels of harmful emissions, and a more rational use of available natural resources compared to conventional residential construction. The proposed project proves the real-world viability and relevance of eco-housing in Ukraine and confirms the feasibility of its implementation as one of the strategic directions of sustainable development. In the future, it is advisable to expand the scope of research to include the development of similar concepts for multi-storey residential buildings and to conduct a detailed analysis of the socio-economic impacts and potential benefits of a large-scale transition to environmentally sustainable housing solutions.

Abstract To address the challenge of power supply limitations for wireless sensor nodes in shaft lifting systems and to promote the advancement of intelligent and environmentally sustainable coal mining, this study proposes an asymmetric beam piezoelectric–electromagnetic hybrid vibration energy harvester (AB-PEH-VEH). The proposed device is designed to harvest and efficiently convert the vibrational energy from the lifting system into electrical energy. By integrating the principles of the direct piezoelectric effect and electromagnetic induction, a coupled electromechanical model is established through dynamic system analysis. The key parameters, including coil inner diameter, number of turns, and coil-magnet spacing, are optimized through COMSOL Multiphysics simulations combined with experimental validation. Furthermore, the impact of the harvester four-array layout and the parallel rectifier circuit on overall performance is systematically investigated. The experimental results demonstrate that at the first-order natural frequency of 7 Hz, the four-array energy harvester delivers a peak output voltage of 15.6 V and a maximum output power of 8.112 mW. This level of performance is sufficient to meet the auxiliary power requirements of low-power wireless sensing modules, thereby reducing reliance on chemical batteries and providing a viable energy solution for intelligent monitoring systems in coal mining environments.

Combined long-term aerated storage and photo-Fenton process for winery wastewater treatment: operational conditions optimization.

Experimental and numerical investigation of self-heating effects on the through-metal ultrasonic power transfer efficiency.

Biocatalysis is fundamental to biological processes and sustainable chemical productions. Over time, the biocatalysis strategy has been widely researched. Initially, biomanufacturing and catalysis of high-value chemicals were carried out through direct immobilization and application of biocatalysts, including natural enzymes and living cells. With the evolution of green chemistry and environmental concern, hybrid photoelectro-biocatalysis (HPEB) platforms are seen as a new approach to enhance biocatalysis. This strategy greatly expands the domain of natural biocatalysis, especially for bio-based components. The selective valorization of renewable furan derivatives, such as 5-hydroxymethylfurfural (HMF) and furfural, is central to advancing biomass-based chemical production. Biocatalysis offers high chemo-, regio-, and stereo-selectivity under mild conditions compared with traditional chemical catalysis, yet it is often constrained by the costly and inefficient regeneration of redox cofactors like NAD(P)H. Photoelectrocatalysis provides a sustainable means to supply reducing equivalents using solar or electrical energy. In recent years, hybrid systems that integrate biocatalysis with photoelectrocatalysis have emerged as a promising strategy to overcome this limitation. This review focuses on recent advances in such systems, where photoelectrochemical platforms enable in situ cofactor regeneration to drive enzymatic transformations of furan-based substrates. We critically analyze representative coupling strategies, materials and device configurations, and reaction engineering approaches. Finally, we outline future directions for developing efficient, robust, and industrially viable hybrid catalytic platforms for green biomass valorization.