Hasil untuk "Production of electric energy or power. Powerplants. Central stations"

Pamela Mukherjee, Papia Ray, Manas Ranjan Mahapatra et al.

Mustafa Cagatay Kocer, Hakan Gultekin, Sahin Albayrak et al.

Zhe Lv, Zhonghao Sun, Lei Wang et al.

With the accelerating global transition toward sustainable energy, the role of battery energy storage systems (ESSs) becomes increasingly prominent. This study employs the isothermal battery calorimetry (IBC) measurement method and computational fluid dynamics (CFD) simulation to develop a multi-domain thermal modeling framework for battery systems, spanning from individual cells to modules, clusters, and ultimately the container level. Experimental validation confirms the model’s accuracy, with the simulated maximum cell temperature of 36.2 °C showing only a 1.8 °C deviation from the measured value of 34.4 °C under real-world operating conditions. Furthermore, by integrating on-site calibrated thermodynamic parameters of the container, a battery system energy efficiency model is established. Combined with the battery aging engineering model, a coupled lifetime–energy efficiency model is constructed. Six different control strategies are simulated and analyzed to quantify the system’s comprehensive lifecycle benefits. The results demonstrate that the optimized control strategy enhances the overall energy storage station revenue by 2.63%, yielding an additional cumulative profit of CNY 13.676 million over the entire lifecycle. This research provides an effective simulation framework and decision-making basis for the thermal management optimization and economic evaluation of battery ESSs.

Wenyang Deng, Dongliang Xiao, Mingli Chen et al.

As distributed photovoltaic and shared energy storage systems expanded on the user side, developing an energy-sharing mechanism across different regions became crucial for fully utilizing local renewable energy resources and maximizing the system’s overall economic performance. This paper established a multi-regional energy operator (MREO) model considering shared energy storage, and a two-layer trading and optimization framework based on a master–slave game was developed. Initially, a trading system was devised to evaluate the interests of the power grid, MREO, and end-users. Next, an optimization model was formulated to capture the dynamic interactions between MREO decisions and user responses. The top-layer model was managed by MREO and focused on energy sharing among regions, which is used to set flexible electricity prices according to regional demand and optimize the use of shared energy storage. Meanwhile, the bottom-layer model addressed user demand response, allowing users to modify their energy consumption and select more advantageous trading areas based on information provided by the MREO. Simulation results confirmed that the proposed model accurately evaluated each party’s income, iteratively balanced their interests, and increased economic returns for both users and MREO. Additionally, the proposed approach supported greater local photovoltaic energy consumption, reduced grid load fluctuations, and fostered mutually beneficial outcomes for all stakeholders.

Jing Xu, Chupeng Xiao, Zhenlan Dou et al.

FU Xiaobiao, HOU Jiaqi, LI Baoju et al.

Weather classification is an indispensable preprocessing step in photovoltaic (PV) power prediction. A new two-modal weather classification methods based on PV power clustering was proposed to finely depict the uncertainty of PV power output. Both PV power data and meteorological data were considered for weather classification, providing a novel and effective path for PV power prediction. In addition, data fusion technology was used to extract relevant information from both numeric weather prediction (NWP) data and measured meteorological data to help for weather classification. This approach reduces the model’s reliance on the accuracy of forecasted meteorological indicators and improve the robustness of the model. Experiments based on data from a PV power station in Jilin demonstrated the rationality of the proposed weather classification method. Combining the PV power probability prediction with the proposed weather classifier resulted in prediction interval coverage probabilities closer to the preassigned confidence level and narrower mean prediction interval width.

Hans H Falk, Stefanie Eckner, Konrad Ritter et al.

The chalcopyrite alloy (Ag,Cu)(In,Ga)Se _2 is a highly efficient thin film solar cell absorber, reaching record efficiencies above 23%. Recently, a peculiar behavior in the bond length dependence of (Ag,Cu)GaSe _2 was experimentally proven. The common cation bond length, namely Ga–Se, decreases with increasing Ag/(Ag + Cu) ratio even though the crystal lattice expands. This is opposite to the behavior observed for Cu(In,Ga)Se _2 , where all bond lengths increase with increasing lattice size. To better understand this peculiar bond length behavior, element-specific bond lengths of (Ag,Cu)InSe _2 and Ag(In,Ga)Se _2 alloys are determined using extended x-ray absorption fine structure spectroscopy. They show that the peculiar bond length dependence occurs only for (Ag,Cu) alloys, independent of the species of common cation (In or Ga). The bond lengths are used to determine the anion displacements and to estimate their contribution to the bandgap bowing. Again, both behaviors differ significantly depending on the type of alloyed cation. A valence force field approach, relaxing bond lengths and bond angles, is used to describe the structural distortion energy for a comprehensive set of I–III–VI _2 and II–IV–V _2 chalcopyrites. The model reveals bond angle distortions as main driving factor for the tetragonal distortion and reproduces the literature values with less than 10% deviation. In contrast, the peculiar bond length dependence is not reproduced, demonstrating that it originates from electronic effects beyond the scope of this structural model. Thus, a fundamental understanding of bond length behavior and tetragonal distortion is achieved for chalcopyrite materials, benefiting their technological applications such as high efficiency thin film photovoltaics.

Fatemeh Marzbani, Ahmed Osman, Mohamed S. Hassan

Guiqing Feng, Lingfei Zhu, Zheng Pan et al.

Akhtar Hussain, Van-Hai Bui, Hak-Man Kim

Colani T. Fakude, Refiloe P. Modise, Aderemi B. Haruna et al.

Drug abuse has proliferated at an unprecedented rate worldwide, posing significant public health challenges that directly impact society, criminality, and the economy. This review presents the application of nanomaterials for qualitative and quantitative electrocatalytic analysis of drugs of abuse, mostly opioids (such as heroin (HER), morphine (MOR), codeine (COD), fentanyl (FEN), and tramadol (TR)), and addictive stimulants (such as cocaine (COC) and methamphetamine (MAM)) via direct oxidation. Electroanalytical techniques have attracted attention for generating point-of-use sensors because of their low cost, portability, ease of use, and the possibility of miniaturization. Electroanalytical-based devices can assist first responders with tools to identify unknown powders and to treat victims of drug abuse. Based on the drug therapeutic and usage purposes, research advances in drug electroanalysis can be classified and discussed with special emphasis on the electrochemical reaction mechanism of the drug. Therefore, this review discusses sensor enhancement based on the electrocatalytic properties introduced by various strategies, such as surface nanostructuring, the use of conducting polymers, and anodization of electrode surfaces Finally, a critical outlook is presented with recommendations and prospects for future development.

Jiaxing CHEN, Chunling WANG, Chunming LIU

At present, power systems are facing great pressure of carbon reduction. With the development of smart grids, the participation of demand-side resources in power-system scheduling can further reduce carbon emissions of power systems. Therefore, this paper proposes a dynamic low-carbon two-stage optimal scheduling method considering demand response in a day-ahead market. In the first stage, the carbon market transaction cost on the power generation side is calculated based on a metering model of dynamic carbon emission of generation units. On this basis, an optimization model for low-carbon economic scheduling of a power system is established to obtain an initial schedule. In the second stage, based on the improved carbon emission flow theory of power systems, the real-time carbon emission and cost of users are calculated. Moreover, demand response with carbon price as a signal is considered to establish a low-carbon economic optimal dispatch model to optimize load distribution to further reduce carbon emission of the system. On this basis, a final schedule can be obtained. Finally, the improved IEEE 14 node system is used as an example to calculate and analyze carbon emissions and total operating cost of the system. The simulation results show that the proposed model and method can reduce carbon emissions of the system, thus verifying their feasibility and rationality.

Cencen LIU, Tian XIA, Yan LI et al.

Modern distribution networks are often constructed in grid and operated in a radial manner to improve the transfer capacity under fault conditions. The traditional distribution network planning method generally adopts the two-stage iterative calculation method of planning design and reliability evaluation, which can only obtain an extensive planning scheme; the resulting planning scheme is either over invested or unable to meet specific reliability requirements. Therefore, a multi-stage distribution network expansion planning method considering reliability constraints is proposed. The reliability index calculation process is analyzed and embedded into the planning model, which can accurately consider the fault isolation, load transfer and recovery strategies. Based on the linearized power flow, the planning model is a typical mixed integer linear optimization problem, which can be effectively solved. The performance of the proposed method is verified in the Portugal 54-node system. The simulation result proves the effectiveness and flexibility of this method.

Xiaowei He, Sifei Zhuo, Lidong Tian et al.

Abstract To follow up on the performance of lithium‐ion batteries (LIBs), transition metal sulfides (TMSs) have been developed as promising carbon alternatives for sodium‐ion batteries (SIBs). Although attractive, it is still a great challenge to fulfill their capacity utilization with high cycling performance. Herein, a nanoemulsion‐directed method has been developed to control the spherical arrangement of ZnS@C units with both penetrating macropores from the center to the surface and inner mesopores distributed among the bulks. With respect to ion diffusion, the penetrating macropores could serve as the built‐in ion‐buffer reservoirs to keep a steady flow of electrolyte, while the inner mesopores facilitate the ion diffusion across the whole bulks. In terms of stability, the radical porous structure could work as self‐supported vertical bones to accommodate the volume change from both lateral and vertical sides. Besides, the localized carbon distributed among the ZnS nanoparticles not only acts as binding agents to join the numerous ZnS nanoparticles but also endows the radical bones with effective electron transmission capability. As a proof of concept, such hydrangea‐like ZnS@C nanospheres deliver sodium storage performance with high‐rate and long‐cycling capability. This nanoemulsion‐directed approach is anticipated for other TMSs with penetrating pores for post‐lithium‐ion batteries applications.

Saeed Akbari, Hamed Hashemi-Dezaki, Seyed Saeed Fazel

Vineet P. Chandran, Bhim Singh

Abstract This work presents the operation and control of a pico‐hydro‐solar photovoltaic (PV)‐battery energy storage (BES)‐based isolated renewable energy system (RES) feeding 3‐phase 4‐wire loads. For voltage regulation, to maintain frequency, and power quality improvement in this system, a 4‐leg VSC is used. The BES is connected to the DC‐link of the voltage source converter (VSC) through a bidirectional converter (BDC), which regulates the DC‐link voltage and controls the charging and discharging current of the battery. An advanced perturb and observe (AP&O)‐based MPPT control technique with drift free operation and capability to operate in the derated mode is adapted in this work. The VSC connected to PCC, injects or absorbs power from this system based on the difference of power between generation and the load. The modified complex co‐efficient filter (MCCF)‐based control technique monitors the power quality of this RES system and 4 leg VSC provides the source neutral current compensation. This control algorithm is used to extract the amplitude of the fundamental load current component with improved dynamic response, DC offset elimination and higher order harmonics removal capability. The ability of the presented control strategy for power quality improvement, power management, load balancing and neutral current compensation is reported in this work.

Marie-Eve Yvenat, Benoit Chavillon, Eric Mayousse et al.

Hybrid supercapacitors have been developed in the pursuit of increasing the energy density of conventional supercapacitors without affecting the power density or the lifespan. Potassium-ion hybrid supercapacitors (KIC) consist of an activated carbon capacitor-type positive electrode and a graphitic battery-type negative one working in an electrolyte based on potassium salt. Overcoming the inherent potassium problems (irreversible capacity, extensive volume expansion, dendrites formation), the non-reproducibility of the results was a major obstacle to the development of this KIC technology. To remedy this, the development of an adequate formation protocol was necessary. However, this revealed a cell-swelling phenomenon, a well-known issue whether for supercapacitors or Li-ion batteries. This phenomenon in the case of the KIC technology has been investigated through constant voltage (CV) tests and volume measurements. The responsible phenomena seem to be the solid electrolyte interphase (SEI) formation at the negative electrode during the first use of the system and the perpetual decomposition of the electrolyte solvent at high voltage. Thanks to these results, a proper formation protocol for KICs, which offers good energy density (14 Wh·kg_{electrochemical core}⁻¹) with an excellent stability at fast charging rate, was developed.

Yuantao Gu, Quan Wan, Xiaoxia Li

Low-pressure N 2 adsorption (LPNA) could provide quantitative data for characterizing the pores in gas shale. However, the inconsistencies of outgas temperature have caused significant deviations in LPNA experiments. To explore the effects of outgas temperature on pore characteristics, two shale samples of Lower Cambrian Niutitang formation from Northern Guizhou, China, were collected for LPNA experiments and thermogravimetry-fourier transform infrared (TG-FTIR) spectroscopy. The samples were outgassed at six temperatures: 80°C, 100°C, 150°C, 200°C, 250°C, 300°C. Larger adsorbed volumes were presented in the isotherms at higher outgas temperatures. Similar regularity is obtained from the relationship between specific surface area, micropore volume and outgas temperature. Comprehensive analysis of TG-FTIR and LPNA at different outgas temperature indicated that at lower outgas temperatures (from 80°C to 100°C), the free water was unlikely to be removed completely, and resulted in large amounts of micropores couldn’t be accessed. An excessive outgas temperature might expulse liquid hydrocarbons or decompose organic matter (from 200°C to 300°C), and could lead to the generation of micropores. When the sample were outgassed at 150°C, TG-FTIR analysis indicated that the sample composition unchanged and a better removal of free water happened. Therefore, 150°C should be a suitable outgas temperature for shale in LPNA experiments. The findings in this research not only provide reliable evidence for the selection of outgas procedure in LPNA for shale, but clarify the important effects of free water and volatile materials on pore accessibility in shale.

Yi GAO, Lianfang TIAN, Qiliang DU

Aiming at the problems of large workload and low intelligence of the current infrared image-based overheating defect detection techniques for composite insulators, and the poor accuracy and poor generalization performance of the traditional image segmentation methods in complex backgrounds, an overheating defect detection method is proposed for composite insulators based on instance segmentation network Mask R-CNN. Firstly, in order to improve the accuracy of segmentation, the Mask R-CNN network is improved according to the idea of Cascade R-CNN, and the data augmentation and transfer learning methods are used for model training to improve the network performance. Secondly, the result obtained by deep segmentation network is further optimized by using traditional image processing methods such as skeletonization, so that the final segmentation result only covers the core rod of the composite insulators. Finally, the temperature data in the infrared image is directly read and converted into the actual temperature value, and the grade of overheating defects is judged according to the relevant methods and criteria provided in DL / T664—2016 Infrared Diagnostic Application Specification for Live Equipment. The results show that the algorithm proposed in this paper has a high detection accuracy of 100% for the infrared images of composite insulators with serious and urgent defects, but has false detection occurrence for the infrared images without overheating defects or with general defects. On the whole, the accuracy rate of 93% is achieved in defect detection of test sets.

Xiaoyu Gong, Chih-Chun Kung, Liguo Zhang

Pyrolysis and gasification are considered as a means of producing renewable energy and improving energy sustainability, which has become attractive renewable technologies to many countries. Unlike other studies that are conducted in small scale, this study aims to aggregate the economic and environmental effects such as agricultural benefits, energy sale, and carbon sequestration to provide more detailed information to decision-makers before these projects are widely employed. This study first employs a lifecycle assessment to investigate the feasibility, profitability, and emission reduction of four major pyrolysis and gasification technologies using crop residuals, and then conducts a sensitive analysis to examine the most influential factors. The results indicate that the intermediate pyrolysis with rice straw and slow pyrolysis from corn stover could offset the carbon dioxide the most. However, the pyrolysis value is also sensitive to production of the feedstock used. Value adding of stover-based biochar under fast pyrolysis improves profitability but other technologies do not have such patterns. Additionally, while gasification can generate considerable amount of renewable electricity, it yields almost zero percent of biochar that can be used as a soil amendment, and thus its contribution to agricultural sector is trivial.