bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Transformer Fault Diagnosis Model Based on Improved GOA-SVM
Authors: Li Wannian , Xiao Jinfeng 
Published: March 2023

Abstract
A transformer fault diagnosis model based on the improved grasshopper optimization algorithm-optimized support vector machine (SVM) is proposed to improve the precision of transformer fault diagnosis and avoid the issues that the traditional grasshopper optimization algorithm (GOA) is prone to falling into local optimal solution and slow convergence. Firstly, the grasshopper population is initialized using the elite backward learning strategy to improve the initial population quality and search efficiency. Then, the Sigmoid function is introduced to improve the linear weight decreasing of the grasshopper algorithm into nonlinear weight decreasing to strike a balance between the algorithm’s capacity for both local and global exploration. Finally, the kernel function parameters and penalty coefficients of the SVM are optimized with the improved grasshopper optimization algorithm (IGOA) to establish a model based on dissolved gas analysis (DGA) in oil-based IGOA algorithm-optimized SVM for transformer fault diagnosis model and verify the effectiveness and superiority of IGOA-SVM to identify transformer fault states by comparing with PSO-SVM and GOA-SVM.
Multi-level Topology and Dynamic Power Sharing of Household DC Distribution System
Authors: Han Jun , Xie Zhenjian , Cai Chao 
Published: March 2023

Abstract
With the popularity of electronic information products and the gradual adoption of DC speed control in electric household appliances, more and more household appliances are equipped with rectifiers or inverters. Moreover, household rooftop PV, wind turbines and energy storage devices also output electric energy in the form of DC. This paper presents a topology of household DC distribution system, which not only improves the reliability of power supply from the power consumption mode, reduces the loss in the process of power form conversion, but also provides users with safer voltage level and more reasonable fault protection. On this basis, this paper proposes an instantaneous power sharing scheme based on droop control, which enables each power module of the system to achieve steady-state and dynamic power sharing.
Calculation Method of Hosting Capacity for Distributed Grid-connected Photovoltaic Based on IGWO
Authors: Xie Jicheng , Tang Yi 
Published: March 2023

Abstract
In recent years, the distribution grid has been taking more and more risks due to the large-scale access of distributed photovoltaics (DPV), including potential problems such as voltage overrun and tidal current reversal, which seriously threaten grid security. Therefore, studying the maximum access capacity of distributed photovoltaics in the distribution grid is a research need nowadays. In this paper, we first establish a distributed PV grid-connected optimization operation model for distribution networks, taking into account multi-dimensional constraints such as voltage, load capacity, and active power, and then propose a grey wolf optimization based on particle swarm and Bernoulli chaos mapping, using chaos mapping initialization population, nonlinear convergence factor, and position update idea in the particle swarm algorithm to increase the initial population diversity and solution accuracy. Then, we use the improved grey wolf optimization algorithm (IGWO) as the basis for solving the maximum access capacity of distributed PV for distribution networks. Finally, simulations are conducted on the IEEE-33 node system to exemplify the previously developed model and algorithm.
Two-layer Optimization of Energy Efficiency Based on Provincial Smart Energy Service Platform
Authors: Cheng Baohua , Zhang Hualu , Deng Boya , Shi Jie , Zhou Xiaofei , Su Huiling , Ren Yucheng , Ji Ruilin 
Published: March 2023

Abstract
The study relies on the provincial smart energy service platform of Jiangsu Province, optimizes its accurate prediction module of energy consumption and the energy efficiency improvement module, and proposes an efficiency improvement strategy based on the two modules of the platform. The accurate prediction module adopts the data processing and feature analysis method based on STL-MIC and builds a deep learning framework based on CNN-BiLSTM. The projected predicted data is then input to the energy efficiency improvement module, which employs the method of flexible load scheduling to achieve the best configuration of demand-side resources.
A Reinforcement Learning-based Approach for Active Optimization of High Proportional Distributed Power Supply Access to Rural Distribution Networks
Authors: Li Rui , Yan Tao , Zhao Yang , Zhang Jinming , Zhang Lu 
Published: March 2023

Abstract
In the process of actively implementing the rural revitalization strategy and the “double carbon” goal, distributed power sources are connected to the rural distribution network on a large scale, resulting in a gradual transition to a new type of active distribution network, which has a greater impact on the distribution network in terms of voltage, network loss, and protection, thus posing greater demands on the distribution network in terms of planning and control, power quality management, and operation. This significantly impacts the voltage, network loss, and protection of the distribution network, thus putting higher requirements on the planning and control, power quality management, operation, and maintenance of distribution networks. Since the traditional OPF algorithm has great defects in solving large-scale decentralized, time-series, and stochastic nonlinear problems, in order to realize real-time control of distribution networks under more complex network conditions, this paper proposes an optimization algorithm based on reinforcement learning and applies it to real-time control of active distribution networks, taking the optimal network loss as the objective function and considering network voltage, line load factor, and distributed power supply. As a de-modeling artificial intelligence method, reinforcement learning has great advantages in solving large problems with complex mathematical models. The method’s control effect and convergence time can be improved by introducing imitation learning and migration learning, expanding the knowledge matrix, and introducing risk assessment mechanisms. Based on MATLAB R2017a simulation platform for the IEEE 33-node improvement model, the simulation results show that the reinforcement learning method has a better control effect in solving the real-time control problem of active distribution network, significantly alleviates the voltage crossing limit, effectively reduces the network loss, and has good real-time characteristics.
An Intelligent System with Multiple Power Supply Modes
Authors: Yan Dong , Yang Wanyu 
Published: March 2023

Abstract
A low-cost and intelligent power supply system with an STC15 single-chip microcomputer as the main controller is designed. The single chip monitors the mains voltage and controls the relay to switch between the mains and battery power supply. Battery constant current, constant voltage, and floating charge intelligent charging management are achieved through the battery voltage execution. Through the ESP8266WIFI module networking, we can access weather information, and weather judgment, and choose whether to enter the battery mode, which can better protect the power system. The experimental results show that the system can operate reliably and complete the switch between mains supply mode and battery supply mode quickly.
A hybrid energy storage power system dispatch strategy for demand response
Authors: Chen Renhui , Guo Minghao , Chen Nan , Guo Xianting 
Published: March 2023

Abstract
In recent years, with the deepening global energy crisis and greenhouse effect, the trend of the power industry towards low-carbon and clean development has gradually increased. This is manifested in the power supply side and the load side, i.e., the power imbalance brought about by the uncertainty and volatility of both. Therefore, based on the above background, this paper first proposes a new power system consisting of renewable energy, hybrid electric-hydrogen energy storage, and fuel cells. Secondly, this paper proposes a commercial load dispatching strategy with a time-of-use tariff, which is solved by complex optimization to verify its economic advantages and feasibility.
Lightweight Design of Differential Thickness-Carbon Fiber Reinforced Plastic Car Seat Backrest
Authors: Wu Chao , Long Jiangqi , Ni Jimin 
Published: March 2023

Abstract
To realize the light weight of the seat back of a new energy vehicle, this study uses the idea of differential thickness to remove the reinforcing ribs of the seat back while meeting the requirements of performance and assembly of the carbon fiber seat back and then carries out the structural design and layer optimization of the seat back to minimize the overall quality of the seat back. The finite element model of the car seat is established by finite element analysis software, and the definition visualization of carbon fiber composite is realized in Hypermesh software. Finally, the light effect of the carbon fiber backrest of automobile seats is 22.1%, which meets the design purpose and requirement of the differential thickness of the backrest.
Research on the innovative design of the turning mechanism of high-power diesel engines
Authors: Gu Ding , Ren Kaifeng , Liu Yongqiang , Shi Jiaxin , Wang Liang 
Published: March 2023

Abstract
In response to the problems of excessive wear of the worm, complex overall structure, and cumbersome operation and maintenance procedures of the turning mechanism of high-power diesel engines, conflict areas are established to find the root cause. In this regard, the technical conflict model is established by analyzing the backlash between teeth. The design optimization is carried out by the invention principle to form a new structural design. And the reliability test verification is carried out to ensure good working performance in the maintenance cycle, thus reducing the application risk. Innovative design methods can be widely popularized in various working conditions such as assembly, debugging, and maintenance of high-power diesel engines, further promoting the innovation ability of high-power diesel engines in the field of research & development and application.
Simulation of Switched Reluctance Motor with an optimized Direct Torque Control minimizing Torque Ripple
Authors: Xia Hongji , Diao Han , Zhu Xiaoxiao , Cao Qixin 
Published: March 2023

Abstract
Switched reluctance motor (SRM) is paid more attention in industrial usage because of its simple structure and low cost. But the inherent torque vibration situation and noise caused by vibration limited its application in electrified vehicles, which requests sooth torque output. To meet the demand of minimizing torque ripple, this article presents a new direct torque control (DTC) method with a changeable reference flux and a more steady switching table to lower the torque ripple and power consumption. This new method is carried out by MATLAB simulations which show that the new DTC method enhances the response of the focused 4-phase SRM to reach the given speed faster and meanwhile minimizing the torque ripple compared to the traditional DTC method.
Finite element analysis on the propagation characteristics of laser-generated surface acoustic wave in V-groove weld
Authors: Li Ziming 
Published: March 2023

Abstract
Thick-walled structures, such as marine engineering and rail transportation, are widely used in modern society. V-groove welding is a common welding method in thick structures. At the same time, the V-groove weld is also the area of a thick-walled structure in which defects are most easily formed. Laser-generated surface acoustic waves are a promising non-destructive testing method in most fields. This study examined the propagation characteristics of laser-generated surface acoustic waves in a V-groove weld. A two-dimensional finite element model with Q345 steel was constructed. A thermoelastic mechanism was adopted to generate the wave. The temperature and displacement fields were analyzed in detail. The results showed that wave transmission, reflection, and mode conversion are generated with an R wave at the junction, and the dispersion phenomenon of the R wave occurred in the welded area.
Die level thinning after bonding on the substrate in 3D packaging
Authors: Wang Yao , Hu Chuan , Xiang Xun , Zheng Wei , Cui Yinhua 
Published: March 2023

Abstract
This paper aims to realize heterogeneous integrated packaging technology for high integration by applying a thinning process technology for controlling the thickness of chipsets used in packaging, i.e., A technology for processing silicon dies with a thickness of 100 um or less and a technology for handling thinning ultrasmall dies. We combine wet etching with dry etching to fit an effective and practical experimental plan. Anisotropic etching in KOH solutions and ICP etching of silicon die bonding on a glass substrate are investigated. Die with copper wiring is fabricated and pasted on the substrate to achieve selective etching of the whole device. The topography of the die surface and corner is analyzed to prevent the influence on the second layer stacking process.
Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations
Authors: Labe Zachary M , Barnes Elizabeth A , Hurrell James W 
Published: March 2023

Abstract
Stratospheric aerosol injection is a proposed form of solar climate invention (SCI) that could potentially reduce the amount of future warming from externally-forced climate change. However, more research is needed, as there are significant uncertainties surrounding the possible impacts of SCI, including unforeseen effects on regional climate patterns. In this study, we consider a climate model simulation of the deployment of stratospheric aerosols to maintain the global mean surface temperature at 1.5 ∘C above pre-industrial levels (ARISE-SAI-1.5). Leveraging two different machine learning methods, we evaluate when the effects of SCI would be detectable at regional scales. Specifically, we train a logistic regression model to classify whether an annual mean map of near-surface temperature or total precipitation is from future climate change under the influence of SCI or not. We then design an artificial neural network to predict how many years it has been since the deployment of SCI by inputting the regional maps from the climate intervention scenario. In both detection methods, we use feature attribution methods to spatially understand the forced climate patterns that are important for the machine learning model predictions. The differences in regional temperature signals are detectable in under a decade for most regions in the SCI scenario compared to greenhouse gas warming. However, the influence of SCI on regional precipitation patterns is more difficult to distinguish due to the presence of internal climate variability.
The preliminary study on the historical governing law of the frozen estates in Kampong Bharu, Malaysia
Authors: Salleh R M , Malek N A A , Yusoff R M , Wahab N , Atan S M , Sainan Z 
Published: March 2023

Abstract
Kampong Bharu is situated in Kuala Lumpur, Malaysia and is categorised as a high commercial land located in the ‘Golden Triangle.’ However, this place is still left behind in terms of development as it is reported that there are more than RM60 billion in frozen estates. The existing legal framework is still considered inadequate as the planning development has been pending until today. Hence, this paper aims to analyse the legal history and the constraints preventing the development of Kampong Bharu. The discussion adopts the content analysis based on the qualitative research methods through the statutory provisions and other legal and non-legal literature. The research found that the Kampong Bharu Development Corporation Act 2011 was passed, and the Kampong Bharu Development Master Plan 2040 has been launched to carry out the development. Hence, it is proposed that the Kampong Bharu Development Corporation (KBDC) may have to wield the Land Acquisition Act 1960 so that the productive elements in Kampong Bharu can be activated. The impact of this research is in line with the benefit addressed by the Sustainable Development Goals (SDG) Plan (2030) in terms of making cities and human settlements inclusive, safe, resilient and sustainable.
Green roof installation as a living lab for outdoor learning in higher education
Authors: Amir A F , Akhir N M 
Published: March 2023

Abstract
Technology and construction knowledge are harder to understand among higher education students if the teaching and learning process is only conducted inside the classroom. Learning should be versatile, and the subject will be more interested in experiencing the students with materials and processes outside the classroom. It also boosts site awareness, especially when the students must collaborate on the design and construction technology for the site. Thus, a living lab approach was introduced to prepare students with sound designer and construction technical knowledge. The research aims to expose students and the community to extensive green roof installation as part of teaching and learning activities. The green roof subject was selected as it was an example of engaging design students with current technology. The participation from various student backgrounds are from Master of Science in Green Architecture, Bachelor of Science in Architecture, Bachelor of Science in Building Surveying, Diploma in Landscape Architecture and other communities from the nearby campus. The results show the materials and process of building an extensive green roof on campus and significant to the design and build consultant/contractor, academicians, students, and nearby community to understand the process involved in site. The discussion part elaborated on the issues of green roofs, such as managing green roofs and biodiversity.
Public perception and acceptance of tricycle as an option of transportation mode in Malaysia
Authors: Ishak S Z , Shabadin A , Mohd Maidin M A , Nemmang M S , Susilawati  , Kamaluddin N A 
Published: March 2023

Abstract
Transportation is important for the movement of people and goods from one place to another. The parameter of choosing the suitable mode of transport include the cost of service, speed of transport, flexibility, frequency of service, safety & security. Exploring an option for transport modes, this study aims to understand the public perception and acceptance of the usage of tricycles in Malaysia with the objective to benchmark the usage of these tricycles in other countries and measure the perception and acceptance of Malaysian towards tricycles. Public view and their acceptance were collected from 299 respondents via a structured online questionnaire survey. The survey has shown that public acceptance to accept tricycles is 39.3% for public transport, 62% for transporting goods, and the highest percentage for the use of People with Disabilities (PWDs) is 62.8%. Feedback on public perceptions based on six (6) factors was discussed. The advantages and the disadvantages based on the lesson learned from various countries were highlighted to support the findings.
Scenario of reducing carbon emission through shifting consumption of non-renewable energy to renewable energy in asia pacific 2023-2030
Authors: Aimon H , Kurniadi A P , Amar S 
Published: March 2023

Abstract
This research is motivated by the high level of carbon emission due to the dominance of non-renewable energy consumption in the use of the energy mix. This study aims to fill the gaps in previous research to support global programs in reducing carbon emission by designing scenario through a shift in consumption of non-renewable energy (fuel oil) to renewable energy (biofuel oil) in the Asia Pacific for future periods, including 2023-2030. The basic foundation of this research is the result of panel regression during the period 2006-2021. Furthermore, non-renewable energy consumption was reduced to three categories (pessimistic, moderate and optimistic), then the decrease was substituted for renewable energy so that the community’s energy needs were still met. The important finding from this research is the consumption of renewable energy and green economic growth can reduce carbon emission, while the consumption of non-renewable energy increases carbon emission. In addition, average carbon emission decreased growth in each scenario, including 15% on the pessimistic, 32% on the moderate and 66% on the optimistic. The policy for reducing carbon emission is to strengthen coordination between domestic institutional structures to develop alternative energy and also implement green economy programs in economic activities.
Effectiveness of deep eutectic solvents for light oil recovery through spontaneous imbibition
Authors: Ganesan D , Hamdi Z , Cheong W C 
Published: March 2023

Abstract
With the rise in demand for energy, comes the need to extract oil from not only primary and secondary stages, but also from tertiary recovery methods to keep up with the current market. Enhanced oil recovery (EOR) has become more prevalent within maturing reservoirs. Ionic liquids (IL) were highly regarded for chemical EOR until researchers raised concerns about their expensive cost, toxicity, and environmental impacts. Recently, deep eutectic solvents (DES) were discovered as a potential replacement for ILs due to their non-toxic nature, being biodegradable, non-flammable, and cheaper. In this study, the effectiveness of DES is investigated by observing its ability to promote oil recovery through wettability alteration. Spontaneous Imbibition tests along with emulsion and thermogravimetric tests (TGA) are used to achieve the objectives. Results indicated that both DESs can recover oil that was not recoverable using brine only. At higher temperatures, the effectiveness of DES was higher, which allowed for more oil to be imbibed out. The effect of concentration suggested that at high concentrations, DESs exhibit self-destructive properties by increasing interfacial tension (IFT), which reduced the imbibition rate and recovery factor. TGA studies indicate that the thermal stability of DESs is highly dependent on the thermal stability of their hydrogen bond donor (HBD).
Financial feasibility study of briquette production from used charcoal and tree branches in Kampung Oase Ondomohen Surabaya
Authors: Zunaidi R A , Deria D D , Amiroh K , Annisa A R 
Published: March 2023

Abstract
Population growth in Indonesia continues to increase from year to year. By 2035, it is predicted that 70% of Indonesia’s population will be urbanites. The potential for sustainable urbanization and regional development has encouraged the Surabaya City Government to turn some of its areas into foster villages, one of which is Kampung Oase Ondomohen. The village was named Kampung Oase because of the village’s high initiative to process waste into high-selling value products, one of which is briquettes that come from the waste from burning Sate Klopo Ondomohen and tree branches around the village area. Using charcoal and tree branches in making briquettes is the main focus of managing organic waste to be used as a renewable energy source. Before the mass production of briquettes, a study on feasibility analysis is needed, especially financial feasibility analysis, aims to assess whether a business can provide optimal financial benefits for its owners. The financial feasibility criteria used in this study are the Internal Rate of Return, Net Present Value, Payback Period, and Net Benefit/Cost Ratio. From the calculation of the four financial feasibility criteria, IRR value is 41,53%, NPV value is IDR 35,732,432.20, PBP is 2.81 years, NBC Ratio is 1.226, so the production of briquettes in Kampung Oase Ondomohen is feasible to run on a larger scale.