Use Of Power Research Articles

Blockchain-based anonymous authentication and data aggregation for advanced metering infrastructure in smart grid

This paper proposes a blockchain-based scheme, focusing on anonymous identity authentication and data aggregation, for safer and more reliable bidirectional communication between the utility company and power consumers based on Advanced Metering Infrastructure (AMI). Firstly, to cope with the mutual identity authentication between resource-constrained Smart Meters, a lightweight anonymous authentication strategy is designed using Elliptic Curve Cryptography. Meanwhile, a reputation-based consensus protocol is developed to accomplish data aggregation in AMI by using decentralization and non-tampering features of the blockchain. During the communication, in each time slot, the proposed scheme only needs to select a trusted user randomly to undertake the mining node rather than to introduce a third-party in a centralized manner to summarize and record the user-side data into the blockchain. Such scheme can effectively prevent data tampering and also be effective to decrease the processing complexity. The AVISPA tool is adopted to formally evaluate its security. The simulation results show promising performance. The proposed scheme not only can guarantee secure communication but also effectively decrease the computational cost in AMI.

Advancement of Bioenergy Technology in South Africa

South Africa has been experiencing an energy crisis since 2007 and continues to the present. This has resulted in load-shedding (action to interrupt electricity supply to avoid excessive load on the generating plant). One way to address this problem is to further explore the potential and contribution of bioenergy through research conducted and implementing energy reports. Therefore, the study aims to provide the state of bioenergy and its contribution to the country’s economic sector and to enhance the replacement of fossil fuels with bioenergy resources and technology. A total blackout of 15,913 h has been experienced since 2014, according to the weekly system status report released by ESKOM. The power utility (Eskom) responsible for power generation and utility has attributed this problem to insufficient generation and capacity. Based on this, the country is embarking on solving this problem. Although the country is dominated by coal (fossil fuel), constituting 73.8% of the total energy supply, this poses a serious environmental risk and health hazard. Renewable energy is considered an alternative energy source, and its introduction and implementation look promising in reducing and solving the current energy crisis. With abundant renewable energy potential, representing 8.7% of the total energy supply, around 85% is bioenergy. This review’s findings revealed that bioenergy contributed mainly towards heat, and fuels admit other energy sources, which is recommended. Therefore, its deployment on a large scale is promising and possible. This study will guide and further encourage the deployment of bioenergy projects in South Africa.

Construction of a Risk Prediction Model for the Occurrence of Acute Skin Failure in Critically Ill Patients: A Prospective Study.

The risk factors for acute skin failure (ASF), a serious complication of the skin, are not fully understood. This study was designed to explore the risk factors for ASF in critically ill patients and construct a clinical prediction model. Intensive care unit patients were prospectively observed and assigned into two groups: with and without ASF. A logistic regression model was constructed, and its predictive power and clinical utility were evaluated. Of the 204 eligible patients enrolled as participants, 58 (28.43%) developed ASF. Sepsis, vasoactive drugs, and age were shown to be risk factors for ASF, whereas peripheral perfusion index ratio and albumin level were shown to be protective factors. The area under the receiver operating characteristic curve was 0.83. The maximum Youden index of the model was 0.39 (specificity: 0.87, sensitivity: 0.77). The Hosmer-Lemeshow test (p = .20) and calibration curve showed good fitness and predictive utility with respect to the model. The developed model effectively predicts ASF risk, allowing for the early identification of high-risk patients. Identifying risk factors such as sepsis, vasoactive drugs, and age and considering protective factors such as peripheral perfusion index and albumin levels may help optimize care plans. Clinical staff should pay special attention to these factors and their impact on skin health in critically ill patients.

Algorithm for detecting abnormal electricity usage by customers based on electricity big data and deep learning

Abstract In order to optimize the effect of individuals’ aberrant power utilization detection and reinforce the recognition rate and accuracy of abnormal power consumption detection of electricity use, an aberrant power utilization identification algorithm based on electric power big data and deep learning is proposed. Taking the two-way dialogue between power users and the power company as the basic perspective, real-time monitoring and collection of power consumption dynamics of users is carried out, and the power big data collection framework is designed. The retrieval of aberrant power utilization detection indexes is completed. Based on the deep learning algorithm, the artificial neural network base operation medium is combined to quantitatively solve the aberrant power utilization indexes, completing the design of a user aberrant power utilization detection algorithm. Experimental results show that the accuracy of the designed algorithm is 0.963, the F1 value is 0.985, and the AUC value is 0.942, which can effectively identify the aberrant power utilization and has a better performance of abnormal power consumption identification and detection.

A coordinated operation method of wind-PV-hydrogen- storage multi-agent energy system

Wind-photovoltaic (PV)-hydrogen-storage multi-agent energy systems are expected to play an important role in promoting renewable power utilization and decarbonization. In this study, a coordinated operation method was proposed for a wind-PV- hydrogen-storage multi-agent energy system. First, a coordinated operation model was formulated for each agent considering peer-to-peer power trading. Second, a coordinated operation interactive framework for a multi-agent energy system was proposed based on the theory of the alternating direction method of multipliers. Third, a distributed interactive algorithm was proposed to protect the privacy of each agent and solve coordinated operation strategies. Finally, the effectiveness of the proposed coordinated operation method was tested on multi-agent energy systems with different structures, and the operational revenues of the wind power, PV, hydrogen, and energy storage agents of the proposed coordinated operation model were improved by approximately 59.19%, 233.28%, 16.75%, and 145.56%, respectively, compared with the independent operation model.

Bioinspired AlFeO3 Memristor with Sensing, Storage, and Synaptic Functionalities

AbstractIn conventional designs, sensory systems are segregated from memory and computing units. The conversion and transmission of data from analog sensing domains to digital storage result in inefficient power utilization and increased latency. Here, a multifunctional memristor capable of detecting gamma radiation while also serving as a data storage device and an artificial synapse is reported. Large‐scale integration of oxide‐based memristors for artificial neural networks faces major challenges due to the sneak‐path current issue in crossbar arrays. Consequently, material combinations and fabrication variables significantly shape nanoscale processes, which are essential in determining resistive switching properties and functionalities. Resistive switching in AlFeO3 is studied using different electrode materials (silver (Ag), gold (Au), chromium (Cr), fluorine‐doped tin oxide, and silicon), embedding metal (Ag, Au) nanocrystals to engineer a class of tunable memories capable of functioning as selector, memory, artificial synapse, and dosimeter. Techniques like electrode engineering, nanocrystal seeding, and temperature‐dependent thin film deposition are employed to tune resistive and threshold switching functionalities. Accessing different functionalities requires changing the electrode materials or changing the synthesis conditions of the AlFeO3 resistive switching layer and are not interconvertible in the same device simultaneously. The devices emulate critical neural functions and demonstrate interconversion dynamics between short‐term and long‐term plasticity.

Utilization of Solar Power for Semi-Automatic Portals at The At-Tajdid Islamic Boarding School Kedungtuban-Blora

At-Tajdid salah satu pondok pesantren (ponpes) modern yang menyiapkan Muslim Berkemajuan sebagai kader persyarikatan maupun kader bangsa yang berintegritas, sebagai penyelenggara pendidikan di dalam pondok pesantren tentunya terdapat fasilitas pendukung proses belajar mengajar santri/santriwati yang saat ini berjumlah 215 orang. Untuk akses masuk-keluar lingkungan ponpes terdapat gerbang terbuka karena belum/tidak ada pintu yang membatasi akses ke dan dari lingkungan pondok pesantren. Selama ini, siapapun bebas masuk/keluar lingkungan ponpes, baik siang maupun malam. Dengan kondisi seperti itu, maka permasalahan yang dihadapi mitra adalah kerawanan lingkungan terhadap terjadinya kejahatan, utamanya kasus pencurian di lingkungan pondok pesantren. Hal ini disebabkan tidak adanya kendali akses di pintu gerbang. Berdasarkan situasi dan kondisi yang dihadapi mitra tersebut, maka solusi dan target luaran yang ditawarkan dalam program PkM ini yaitu Mitra dibuatkan pintu atau portal yang dipasang pada gerbang pondok dengan sistem buka-tutup pintu atau portal dibuat semi-otomatis bertenaga surya guna membatasi akses masuk/keluar lingkungan pondok pesantren. Dengan adanya pembatasan tersebut, dapat memberikan rasa aman dan nyaman bagi seluruh penghuni di lingkungan pondok pesantren, sehingga konsentrasi proses belajar mengajar meningkat.

Money illusion in retirement savings with a minimum guarantee

We investigate the impact of money illusion on the investment strategy and retirement outcomes of pre-retirees. Money illusion refers to the tendency of individuals to overlook the effects of inflation and focus on nominal rather than real terms. We solve and compare the optimal investment strategies for a pre-retiree who exhibits money illusion and aims to maximize the expected power utility of wealth at retirement, subject to a minimum guarantee constraint. While money illusion leads to welfare losses, implementing a minimum guarantee helps suppress these losses. However, guarantee constraints set under money illusion are ineffective in meeting inflation-adjusted constraints. Our findings emphasize the significant impact of money illusion on pre-retirees' investment strategy and retirement outcomes in the form of utility loss and the risk of falling short of the minimum guarantee.

Interpretable feature-temporal transformer for short-term wind power forecasting with multivariate time series

The inherent randomness and volatility of wind power generation present significant challenges to the reliable and secure operation of the power system. Therefore, it is crucial to have interpretable wind power forecasting (WPF) to ensure seamless grid integration and effective risk assessment. Existing forecasting models often focus on improving WPF performance and ignore the interpretability of the model, resulting in ambiguous forecasting. In this paper, the interpretable feature-temporal transformer (IFTT) for short-term wind power forecasting with multivariate time series is presented. The model uses an encoder-decoder architecture to effectively integrate historical information and future prior information from multiple variables. The designed decoupled feature-temporal self-attention (DFTA) module and variable attention network (VAN) effectively realize the interpretability of temporal information and multi-variable inputs while extracting important features. The Auxiliary Forecasting Network (AFN) plays a key role in providing pseudo-future wind speed predictions, which serve as an essential input for the model's decoder, and enhancing forecasting accuracy through multi-task learning. Experimental results on multiple datasets in different geographical locations show that the proposed algorithm is superior to various advanced methods. Besides, the interpretability of the IFTT model offers valuable insights for ensuring the safety of wind power utilization and supporting informed risk decision-making.

Scenario analysis of the Indonesia carbon tax impact on carbon emissions using system dynamics modeling and STIRPAT model

This study aims to develop a system dynamic (SD) forecasting model based on the STIRPAT model to forecast the effect of an IDR 30 per kg CO2e carbon tax on carbon emissions, estimate future carbon emissions under ten scenarios, without and with the carbon tax, and estimate the environmental Kuznets curve (EKC) to predict Indonesia’s carbon emission peak. Carbon emission drivers in this study are decomposed into several factors, namely energy structure, energy intensity, industrial structure, GDP per capita, population, and fixed-asset investment. This study included nuclear power utilization starting in 2038. The research gaps addressed by this study compared to previous research are (1) use of the ex-ante approach, (2) inclusion of nuclear power plants, (3) testing the EKC hypothesis, and (4) contribution to government policy. The simulation results show that under the carbon tax, carbon emissions can be reduced by improving renewable energy structures, adjusting industrial structures to green businesses, and emphasizing fixed asset investment more environmentally friendly. Moreover, the result approved the EKC hypothesis. It shows an inverse U-shaped curve between GDP per capita and CO2 emissions in Indonesia. Indonesia’s fastest carbon emission peak is under scenario seven and is expected in 2040. Although an IDR 30 per kg CO2e carbon tax and nuclear power will take decades to reduce carbon emissions, the carbon tax can still be a reference and has advantages to implement. This result can be a good beginning step for Indonesia, which has yet to gain experience with a carbon tax that can be implemented immediately and is helpful to decision-makers in putting into practice sensible measures to attain Indonesia’s carbon emission peaking. This research provides actionable insights internationally on carbon tax policies, nuclear energy adoption, EKC dynamics, global policy implications, and fostering international cooperation for carbon emission reductions.

Harnessing Solar Power for Energy Efficiency in Deserted Telecommunications Rooms

The utilization of solar power in telecommunications rooms located in deserted areas presents a sustainable solution for enhancing energy efficiency and reducing operational costs. Desert environments, characterized by their harsh conditions and remote locations, pose unique challenges for maintaining power supply to telecommunications infrastructure. This article examines the advantages of using solar power to address these challenges, highlighting its benefits in improving energy efficiency, reliability, and sustainability.

Maximizing energy transfer of solar-battery charge controller using voltage balancing strategy

Off-grid and grid-connected photovoltaic (PV) systems with battery storage rely heavily on efficient energy transfer to maximize PV power utilization and battery lifespan. However, existing literature often overlooks the crucial role of energy transfer efficiency in these systems. This paper proposes a novel, fundamental-based PV power flow strategy that addresses this gap by employing a concept of source-load voltage matching. The proposed strategy ensures optimal voltage matching between the PV array and the battery bank. This is achieved by configuring the battery bank voltage range (between nominal and fully charged states) to closely align with the variation in PV voltage at its Maximum Power Point (MPP) across different operating temperatures. This systematic approach requires specifying the DC load voltage, configuring the battery bank, and selecting PV modules with compatible Vmp (voltage at maximum power) parameters. The system utilizes a high-current blocking diode and current limiter for safe connection between the PV array and battery bank. Additionally, the strategy protects against battery overcharge by controlling parallel fans used for PV panel cooling. Experimental results with a 1.62 kW PV system employing lead-acid batteries demonstrate improved efficiency compared to traditional methods. This innovative approach has the potential to significantly enhance energy transfer efficiency, contributing to improved energy sustainability in PV systems.

Single-phase online interactive uninterruptible power supply design

The single-phase on-line interactive uninterruptible power supply (UPS) designed in this paper consists of three circuits, namely, a single-phase power factor correction circuit, a single-phase inverter circuit, and a bi-directional DC/DC circuit, each of which contains a main circuit as well as a control circuit. The principle, parameter design and control circuit design of each circuit are briefly described. The simulation model of the UPS is constructed, and the simulation results in normal and abnormal utility power are given to verify the correctness of the design.

MoS2 decorated heteroatoms doped carbon microspheres for efficient separation of uranium from wastewater

Uranium serves as a fundamental element for sustainable nuclear reactor energy. Hence, the extraction and enrichment of uranium from radioactive wastewater is of considerable significance for both nuclear power utilization and environmental protection. In this study, carbon microspheres (TAC) doped with nitrogen, phosphorus and sulfur were derived from ternary polyphosphazene. Subsequently, molybdenum disulfide (MoS2) was integrated using hydrothermal method to fabricate the TAC/MoS2 composite, which is designed for the efficient enrichment and separation of uranyl ions. Owing to the unique two-dimensional structure of MoS2 and its strong affinity towards uranyl ions, the adsorption capacity of the composite was significantly enhanced to 399.6 mg/g within 80 min at pH 5 and 298.15 K. Additionally, the composite exhibited commendable thermal stability and hydrophilicity, declaring that it is an outstanding candidate for the efficient enrichment and separation of uranyl ions. Further mechanism studies through XPS analysis and DFT calculations suggested that the vacancies introduced by MoS2 can generate electrostatic interactions and coordination effects with uranyl ions, thereby improving the adsorption performance of the composite. Due to its straightforward preparation process and exceptional adsorption performance, TAC/MoS2 possesses broad application prospects in the extraction of uranium from wastewater.

Research on Electricity Balance and Measurement Optimization of New Energy Power System Considering Renewable Energy Consumption Mechanism

With the rapid development of renewable energy, the new energy power system is facing the challenge of large-scale grid connection and consumption of renewable energy. In order to achieve efficient utilization and stable power supply of renewable energy, this study proposes a renewable energy consumption mechanism based on optimization methods. By establishing a power and electricity balance model, consider the relationship between different types of renewable energy generation and electricity demand. Various optimization strategies have been proposed for energy consumption issues in different scenarios, including power generation scheduling, energy storage optimization, and flexible load management. Validate the effectiveness of the proposed mechanism in terms of electricity balance and metering optimization through a model. The experimental results indicate that this mechanism can effectively enhance the renewable energy consumption capacity of the new energy power system, reduce energy waste, promote energy cleanliness and sustainable development, and has certain theoretical and practical significance for promoting the sustainable development of the new energy power system and responding to energy transformation.

THE FINANCIAL IMPACT OF CARBON EMISSIONS ON POWER UTILITIES UNDER CLIMATE SCENARIOS

Power utilities, especially those that generate electricity by burning fossil fuels, produce significant amounts of carbon emissions. Mitigation of [Formula: see text]-equivalent ([Formula: see text]) emissions can be achieved by replacing power plants with renewable power installations and by adopting carbon-sequestration technologies. Physical upgrades are expensive, but carbon taxes, or the purchase of certificates and allowances on a voluntary carbon market, can be costly, too. Carbon costs may increasingly become a threatening liability for power utilities, eating into profits and undermining the financial viability of emission-intensive electricity generation. Thus, we consider an asset-and-liability, structural firm model to investigate the creditworthiness of a generic power utility. The utility’s assets dynamics are driven by the financial returns generated from the sold electricity for a set tariff which is modeled by a simple stochastic process. The liabilities not only depend on fuel, running, and depreciation costs, but also on the costs of [Formula: see text] emissions. As a case study, we consider Eskom, the South African power utility. We show the evolution of Eskom’s default probability under various fuel mix plans and technologies (as per SA’s Integrated Resources Plan (IRP) 2019), and under the Network for Greening the Financial System (NGFS) carbon price scenarios. The obtained results and insights present a trying path ahead, especially for carbon-intensive power utilities.

Molecular insights into thermal conductivity enhancement and interfacial heat transfer of molten salt/porous ceramic skeleton composite phase change materials

Molten salt has been considered as one of the most promising candidate materials for thermal energy storage (TES) systems owing to its remarkable energy density and consistent thermal performance. These properties render it particularly advantageous for the applications in concentrated solar power (CSP) and industrial process heat utilization. Nonetheless, their practical applications still face nonnegligible challenges such as the low thermal conductivity and risk of leakage. Packing molten salts into porous skeletons could be an effective way for addressing these issues. In the present work, the heat transfer characteristics of a composite phase change material (CPCM) consisting of binary chloride salt and a porous ceramic skeleton, are investigated at the microscale level using molecular dynamics (MD) simulations. Simulation results indicate that the integration of a porous SiC skeleton can substantially enhance the thermal conductivity of binary molten salt NaCl/KCl. At the temperature of 1000 K, a notable enhancement of 625.74 % in thermal conductivity has been observed. Moreover, the underlying mechanism of heat conduction enhancement has been revealed from the microscopic perspective. The results demonstrate that auxiliary thermal conductivity paths and interfacial heat transfer play primary roles in determining the thermal conductivity of CPCMs. The method of surface charge modification can effectively improve the interfacial heat transfer and the reason can be attributed to the additional thermal conductivity paths and the large number of particles involved in the interfacial heat transfer. The results gained in this work may provide insights into the heat transfer mechanism of composite molten salt/porous skeleton as well as practical guidance for designing CPCM for thermal storage applications.

Predictive Factors for Delayed Recovery From Anesthesia in Patients Receiving Free Vascularized Flap Reconstruction for Head and Neck Defects: A Retrospective Cohort Study.

Free flap reconstruction for head and neck defects is currently a common procedure. This study aimed to create and validate a predictive model for identifying patients at risk of delayed recovery from anesthesia after free flap reconstruction for head and neck defect. Electronic medical records from all patients were retrospectively collected. The primary outcome variable was delayed recovery from anesthesia. The least absolute shrinkage and selection operator regression model was employed to identify the most relevant features, followed by the construction of a nomogram model using multivariable logistic regression analysis. The discriminatory power, calibration, and clinical utility of the nomogram model were assessed using receiver operating characteristic curve analysis, calibration curve analysis, and decision curve analysis, respectively. This novel nomogram model incorporated 4 predictors for delayed recovery from anesthesia: preoperative albumin, intraoperative fresh frozen plasma infusion, preoperative platelet-to-lymphocyte ratio, and duration of intraoperative hypotension. The area under the receiver operating characteristic curve (area under the curve) for the nomogram model was determined to be 0.821 (95% CI: 0.803-0.836). After internal validation, the corrected area under the curve was found to be 0.768 (95% CI: 0.639-0.812). In addition, the model exhibited well-fitted calibration curves and demonstrated favorable clinical usability as indicated by the calibration curve and decision curve analysis curve. The authors created and validated a novel predictive model utilizing a limited number of 4 predictors, yet exhibiting commendable predictive performance. This innovative tool holds the potential to mitigate delayed recovery from anesthesia and enhance the efficient allocation of medical resources.

Clean energy technologies and energy systems for industry and power generation: Current state, recent progress and way forward

This vision article accompanies a Special Issue of Applied Thermal Engineering dedicated to the Sustainable Development of Energy, Water and Environment Systems (SDEWES) conference series held during 2022, including the 5th SEE SDEWES Conference Vlore, 3rd LA SDEWES Conference Sao Paulo, and 17th SDEWES Conference Paphos. The article discusses a selection of papers presented at these conferences and selected for publication in Applied Thermal Engineering, all connected by a focus on clean energy technologies and systems for the advancement of sustainable thermal energy systems. This research area covers a wide range of technologies but is primarily focused on the power generation sector, energy storage and utilization, efficiency improvements, sustainable technical solutions, and the facilitation of the robust integration of renewable energy resources into wider energy systems. Additional work on previously established research topics is also present, but new directions have crystallized, especially research into thermal management for power devices and microelectronics. Based on the recent contributions to the research field presented in the included papers, this vision article discusses the development and application of cutting-edge technological solutions and identifies the challenges that require focused attention. Current shortcomings of developing and established technologies will be developed by the underlying fundamental research, reduction of prohibitively high costs, expansion of operating conditions, and the inclusion of advanced control approaches, sophisticated combinations of renewable energy sources, and modeling tools for system investigations. Scientists, researchers, and engineers can benefit from the summary of the topics at the forefront of the research field and find guidelines and ways forward for future research activities.

Digitization of Academic Library Resources: A Case Study of Gautam Budh Central Library of Babasaheb Bhimrao Ambedkar University, Lucknow

This study examine the digitization of academic library resources in Babasaheb Bhimrao Ambedkar University. For this study, three research objectives have been formulated and research design adopted for this study was a descriptive survey. Questionnaire is used a tools for getting primary data. Total 20 library staff was involved in this study. The findings of the study, majority of the library staff is have practical approaches for digitization and most of the library professional are facing various problems during digitization process likewise as standby power generating set, solar power system, utility power systems.