bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal scheduling of energy routers based on distributed CAES systems
Authors: Xie Yuguang , Ma Wei , Zheng Tianwen , Li Jinzhong , Zhang Hong , Xu Bin 
Published: June 2024

Abstract
With the rise of renewable energy, distributed energy, and other different forms of energy, the architecture and function of the energy router are relatively perfect, for the topology of the energy router itself, different forms of energy in the energy router flow, conversion to realize the large-scale use of distributed energy equipment has also gradually become a hot spot of research. However, there are fewer studies on the energy router with a distributed CAES system to participate in the optimal scheduling of energy for integrated energy systems. Therefore, this paper is based on the operational domain model of an energy router with a distributed CAES system and analyzes the physical characteristics and coupling relationship of non-energy storage components, takes air pressure, temperature, and oil volume as state variables, takes charging, power generation, and heating power as external interfaces, and utilizes internal interface variables such as air quality and flow rate to realize energy storage, flow, and other internal interface variables to realize the communication between energy storage and non-energy storage elements, and finally determine the operation domain of the system. Secondly, the feasible domain of the energy router based on the distributed CAES system is portrayed, and the optimization of the system parameters is guided with the help of the relative distance by establishing the electric and thermal power constraints and the storage state constraints. Finally, the effectiveness of the feasible domain analysis method in the energy router of a distributed CAES system is verified by taking a northern region as an example.
Energy storage capacity optimization of optical storage microgrid considering customer satisfaction and depth of energy storage discharge
Authors: He Qianshuai , Zhou Renjun , Li Bicheng , Yue Qi 
Published: June 2024

Abstract
The influence of the depth of battery discharge (DOD) and user satisfaction on the capacity configuration of the optical storage microgrid cannot be ignored. In this paper, the minimum comprehensive cost of an optical storage microgrid is taken as the objective function, and the model is established by considering the SOC after DOD, user satisfaction with electricity consumption, power balance, and other constraints. The numerical examples show that the proposed method can allocate suitable energy storage capacity for optical microgrids and ensure user satisfaction.
Photovoltaic grid-connected monitoring technology considering power quality
Authors: Yao Qiang , Liu Yongmei , Song Xiaozhe , Hu Lijuan , Zheng Qiangren , Liu Jun , Zhang Xiaohua 
Published: June 2024

Abstract
With the continuous expansion of grid-connected photovoltaic power generation, monitoring the power quality fluctuations in intelligent photovoltaic grid-connected systems has become a key research direction. Addressing the issues of low accuracy in voltage and current monitoring, as well as insufficient monitoring of SOE events, a comprehensive power quality-oriented detection technology for photovoltaic grid integration is proposed. This technology enables automatic monitoring of power quality fluctuations by collecting signals such as voltage deviation and frequency deviation. The study compares techniques involving a determination of input voltage and current amplitudes, power, phase difference, and SOE event design. The results demonstrate that the power quality monitoring technology for photovoltaic grid integration proposed in this study exhibits high accuracy in monitoring the imbalance of three-phase voltage and current.
Electromagnetic transient simulation of power system based on PSCAD calling ADPSS
Authors: Chen Deyang , Miao Lu , Wang Feng , Mu Qing , Gao Minli 
Published: June 2024

Abstract
As the power system gradually expands into a massive scale, time-varying complex system, the requirements for simulation analysis software are constantly improving, and electromagnetic transient analysis plays a crucial role in the power system. Therefore, to solve the possible limitations of this traditional simulation method, this paper proposes an electromagnetic transient simulation of power systems using PSCAD, called ADPSS. Firstly, according to the basic overview and advantages of the electromagnetic transient analysis program PSCAD/EMTDC and the mathematical model software package ADPSS, the interconnection principle and implementation method between PSCAD/EMTDC and ADPSS are studied, and a simple power system power supply model is established in PSCAD. Then, the principle of PSCAD-ADPSS interface technology is studied. The electromagnetic transient simulation is carried out in the interface environment, and the interface custom components are designed. Finally, by conducting a comparative analysis of the simulation outcomes, it is found that the simulation waveforms obtained in the two simulation environments are almost the same, which shows the effectiveness of PSCAD-ADPSS interface simulation technology in electromagnetic transient analysis and has the potential to enhance the precision and dependability of electromagnetic transient simulation.
A resilience evaluation index system and evaluation method for regional distribution networks facing typhoon disasters
Authors: Zhang Yi , Wang Dengzheng , Xu Qing , Li Qingxi , Liu Zhongjian , Jiang Shigong , Zhao Dong 
Published: June 2024

Abstract
The occurrence of natural climate disasters such as typhoons may lead to large-scale power outages in the distribution network, and a quantitative assessment of the resilience of the power grid is a key step in preventing and resisting the harm caused by natural disasters to the power grid. This article establishes a regional distribution network resilience evaluation index system for typhoon disasters from the perspectives of reliability, safety, and economic resilience of the power grid after a typhoon occurs. Based on the above indicator system, the fuzzy comprehensive evaluation technology is adopted to evaluate the resilience level of the power grid under typhoon disasters. Taking a regional distribution network in Guangzhou, China, as an example, a numerical analysis was conducted, and the results showed that the proposed resilience evaluation indicators and methods can reasonably and quantitatively evaluate the resilience level of urban distribution networks under typhoon disasters.
A study on the resource scheduling strategy in substations with high penetration of photovoltaic electricity
Authors: Zhan Juchao , Du Jiao , Zhang Haichuan 
Published: June 2024

Abstract
In 2020, China introduced the strategic objectives of reaching the peak of carbon emissions and achieving carbon neutrality. However, due to the limited self-regulation capabilities of the power grid and increasingly prominent issues such as insufficient consumption of photovoltaic electricity generation, there are challenges. Therefore, in this paper, a coordinated interaction model of source-load-storage is established with the aim of optimizing the on-site utilization of photovoltaic electricity. Rolling scheduling of substation resources is conducted at three temporal scales: pre-scheduled, interim, and actual-time, and the effectiveness of the proposed approach is verified using actual case studies. The data suggests that compared with single-time-scale scheduling schemes, the on-site consumption rate of photovoltaic electricity increases by 0.32% in the case study substations, validating that the scheduling approach can improve the photovoltaic electricity consumption rate in the substations.
State of charge estimation for lithium batteries based on multi-timescale FFRLS-UKF
Authors: Wei Ying 
Published: June 2024

Abstract
State of charge (SOC) can represent the remaining battery capacity, and accurately estimating SOC is very useful for the drivers of electric vehicles. This study proposes a lithium battery SOC estimation technique based on multi-timescale forgetting factor recursive least squares as well as an unscented Kalman filter (MTS-FFRLS-UKF). The MTS-FFRLS-UKF uses a circuit with a 2-RC network as the battery model, whose parameters are continuously updated at a timescale that is different from SOC estimation. The experimental results under a dynamic test prove the availability and accuracy of MTS-FFRLS-UKF. Continuous parameter update enhances the accuracy of battery modelling and furthermore the SOC estimation accuracy. The mean absolute error (MAE) and root-mean square error (RMSE) of SOC estimation decrease to 0.58% and 0.62%, respectively.
Wind power prediction based on NGO-LSTM
Authors: Chen Panlei , Li Jianguo 
Published: June 2024

Abstract
At present, wind energy is mainly utilized through wind power grid connections. However, because of the uncertainty of wind energy, the grid connection will inevitably have an impact on the system. In order to adjust the grid dispatching plan in real time and improve the grid’s capacity to absorb wind power, a short-term wind speed prediction method based on NGO-LSTM was proposed. Taking the measured data of wind farms as an example, the prediction accuracy of the proposed method is compared with that of existing algorithms. Experimental results show that the R2 of the NGO-LSTM coupling model is closest to 1, and the RMSE, MAE, and MAPE are all smaller than the other two models, verifying the effectiveness and advanced nature of the proposed method.
The wind turbine nacelle oil-level detection algorithm based on improved YOLOv5n-Seg
Authors: Zhao Yong , Hu Chunsheng , Li Hao , Mu Guojun 
Published: June 2024

Abstract
To enable the detection of oil-level information within the oil pot in wind turbine nacelles by inspection robots and address the issues of large model parameters and slow inference speed in the original YOLOv5n-Seg model, this study improved the Backbone and Neck of the YOLOv5n-Seg model using the improved RepVGG module and depthwise separable convolution, respectively. It reduced the number of output channels of each layer network in the improved YOLOv5n-Seg model’s Backbone and Neck to half of its original size. Compared to the original YOLOv5n-Seg model, the improved YOLOv5n-Seg model has significantly optimized parameters and inference speed. These improvements are of significant importance for enhancing the operational efficiency of inspection robots. Additionally, the study designed an oil-level detection algorithm based on the improved YOLOv5n-Seg model. The error between the oil level information detected by the algorithm and the manually detected oil level information does not exceed 7%, which can effectively replace manual oil level detection.
The application of state feedback principle in turbine adjustment system with Python control library
Authors: Gong Chongquan 
Published: June 2024

Abstract
This study investigates the utilization of the Python-Control library in contemporary control theory. The Python-Control package, comprising a collection of Python classes and functions, facilitates the comprehensive analysis and design of feedback control systems. Pole placement, a widely utilized method in the automatic control domain for control system design, is particularly emphasized. This paper explores the application of Python-Control in pole assignment, aiming to enhance control system performance. Additionally, the pole assignment method is successfully implemented in a hydro governor model, demonstrating the efficacy of the Python-Control library in practical control system applications.
Dam control system based on DDPG algorithm
Authors: Zhang Zifei , Liu Lei , Wang Zichun 
Published: June 2024

Abstract
Dams, regarded as a form of hydraulic engineering, are purposed to intercept river or canal flow to either elevate water levels or regulate discharge rates. The discharge of a dam is subject to influence by various factors, including precipitation, temperature, and regulatory policies. Nevertheless, in real-world scenarios, the precise value of the expected dam flow rate is challenging to ascertain through simple arithmetic operations. In this study, a novel dam flow model has been formulated. Through the utilization of the DDPG algorithm and deep learning techniques applied to data from the current month, the parameters of the dam control differential equations have been determined, and the transfer function after Laplace transformation has been established. Consequently, only the current month’s fluctuations in the water level of Lake Huron need to be determined to derive the corresponding dam flow rate for that month.
Study on kinetics of biomass energy conversion and utilization between wheat straw and rice husk
Authors: Ao Hu , Xie Haiwei , Zhang Tianle , Guo Jiaming 
Published: June 2024

Abstract
The environmental problems caused by fossil energy make people pay more and more attention to biomass energy, and pyrolytic biomass has great potential. To make the conversion and utilization of biomass energy more effective, the principle of pyrolysis between different biomass was studied. This study conducted co-pyrolysis of rice husk (DK) and wheat straw (MG) under different mixing ratios (DK: MG= 1:1, DK: MG= 2:1, DK: MG= 1:2, DK: MG= 3:1, DK: MG= 1:3). Based on TG and DTG, the temperature characteristic value and the weightlessness rate are analyzed, and the activation energy (E) was using the FWO method. The results showed that the trend of different blending ratios of biomass pyrolysis are the same, and can be divided into three stages. With the addition of MG, the two biomass react more fully during pyrolysis. When DK:MG=1: 3, the weight loss rate is as high as 98.26%, and the peak temperature Tmax is 317.4°C. Under these conditions, the synergistic effect between the two biomass is more obvious, and the difference between the actual activation energy and the theoretical activation energy is the largest, up to 5.6 kJ/mol.
Reinforcement learning-based energy management for hybrid electric vehicle enhanced by velocity prediction
Authors: Luo Shaohua , Bai Qin , Wang Yi , Liu Ning , Ou Yang 
Published: June 2024

Abstract
This paper proposes a novel approach for optimal energy management of engine-battery hybrid electric systems. It addresses two limitations in existing research, namely inaccurate speed prediction and low control accuracy. The proposed method integrates Markov theory and clustering theory to achieve high-precision prediction of future velocity under diverse driving styles. Furthermore, a learning-based energy management strategy is developed using a deep deterministic strategy gradient algorithm. This strategy considers the predicted velocity and aims to minimize engine fuel consumption, battery state fluctuations, and engine start-stop occurrences. Simulation results demonstrate that the proposed algorithm achieves near-optimal performance under specific operating conditions.
Energy sharing mechanisms for multi prosumers considering privacy protection
Authors: Qi Lei , Ai Qian , Ji Wenlu , Li Jiamei , Wang Di , Pan Xiaohui 
Published: June 2024

Abstract
With the rapid development of new renewable energy sources, microgrids, smart buildings and other forms of prosumers have emerged on a large scale. Energy sharing among multi prosumers can improve the overall economic efficiency. Based on taking into account the data privacy of each prosumer, a collaborative operation mechanism for energy sharing among multi prosumers is proposed. First, an internal scheduling model of prosumers with multiple distributed resources is constructed. Then, an iterative mechanism for multi prosumers tariffs is proposed to guide the tariff update by using the supply-demand relationship. Meanwhile, considering the privacy security of the prosumers, a electricity data aggregation method is designed based on Paillier homomorphic encryption algorithm and the secret sharing principle, which is capable of obtaining the system supply and demand information under the premise of protecting the privacy of all parties. Finally, the effectiveness and reasonableness of the proposed mechanism is verified through examples.
Adaptive reactive power control strategy for grid-forming inverter under symmetrical fault
Authors: Mu Longfei 
Published: June 2024

Abstract
Due to the inability of the grid-type control method to compensate for the comprehensive reduction in system inertia, strength, and short-circuit capacity caused by the proportional decrease of synchronous machines, the power grid exhibits insufficient resistance to disturbances, leading to severe stability risks in terms of rotor angle, frequency, and voltage. In response to these challenges, grid-forming inverters have emerged. Under symmetrical faults, the low-voltage ride-through of grid-forming inverters is often accompanied by a frozen reactive power environment, resulting in a direct output of increased voltage and reactive current. However, an elevated reactive power command can cause a sharp increase in the potential amplitude within grid-forming inverters. After the grid fault is cleared, the excessively high internal potential can cause a short-term and rapid increase in terminal voltage, potentially leading to overvoltage, which is detrimental to the operation of grid-connected devices. To address this issue, this paper first employs a grid-forming inverter controlled by a virtual synchronous machine control method. Using the grid positive-sequence voltage as a reference value, it identifies whether a voltage drop fault has occurred. Based on this, an adaptive reactive power control strategy is proposed, which can promptly achieve the same effect as the frozen reactive power environment during faults, while also promptly restoring the reactive power environment after fault clearance, thereby avoiding overvoltage issues. The feasibility of the proposed method is verified through the establishment of a simulation system.
Evaluation of the Nearest and The Longest Shipping Routes in MT. Perla
Authors: Rohman M A , Achmad F 
Published: June 2024

Abstract
Shipping routes are sea transportation from one port to another. There are loading and unloading activities in shipping routes. Loading and unloading activities are the activity of moving cargo from land to ship at the loading port, and moving cargo from ship to land at the unloading port. On ships with irregular routes, loading and unloading activities are random in terms of shipping route, amount of cargo, and length of time required. Evaluation is a process of collecting information to improve and determine quality and performance based on certain considerations and criteria (value and meaning) in implementing a program. This study will discuss the shipping route, amount of cargo, length of shipping time, loading and unloading. The research aimed to evaluate the nearest and the longest shipping routes in MT. Perla. The authors used a quantitative analysis research method where the data was processed and calculated by using Ms. Excel and SPSS was then used to evaluate shipping routes. The research results show that the evaluation of shipping routes for 12 months. Some factors hinder shipping routes, loading, and unloading activities. The researcher’s advice is for all parties to pay attention to the evaluation results and the factors causing those to avoid company losses and to improve the quality of shipping routes.
Biodegradation of bioplastic straws compared to conventional plastic straws
Authors: Limpiteeprakan Pawena , Ratchawong Jirikanya , Kittichaimongkol Natthanida , Tubtimhin Sanga 
Published: June 2024

Abstract
This experimental study aimed to investigate the biodegradation of commercially available bioplastic straws compared to conventional plastic straws using four types of plastic straws: polypropylene (PP), bio-polybutylene succinate (PSB) mixed with polylactic acid (PLA), PLA alone, and bagasse straws. The tubes were cut into small sizes, buried in soil, watered to simulate natural degradation conditions, and placed in the same environment at the College of Medicine and Public Health, Ubon Ratchathani University. The tubes were excavated, weighed, and analyzed using a microscope and scanning electron microscopy. Results showed that the 1 cm small tubes experienced greater weight loss than the 2 cm tubes. Straws made from PSB mixed with PLA showed the highest weight loss of 46%. Bioplastic straws made from PLA alone showed the least weight loss. SEM images showed noticeable surface changes in straws made from natural materials and bioplastics compared to PP straws, especially in the 2 cm tubes. The findings suggest that using biodegradable straws, especially those made from natural materials, can effectively mitigate plastic pollution and preserve the environment.
Research on a circular economy model for biodegradable organic components treatment in municipal solid waste at a household-scale
Authors: Tuyen Duong Kim , Thanh Dang My 
Published: June 2024

Abstract
Since biodegradable components form a major amount of household municipal solid waste (MSW), this study investigated a model of biodegradable organic waste treatment at home scale in order to recycle them into organic fertilizers. The experimental design was carried out in a perforated plastic bin (capacity = 18L) with 2 different models, with and without Trichoderma microbial product (TMP), in order to evaluate the effect of microbial product on the decomposition process and fertilizer quality. The monitored parameters for both models showed a similar trend of changes during the decomposition, however in the model with TMP, it was found that the decomposition process took place faster. The properties included pH (6.2–7.6), temperature (29–44 °C), and moisture content (47–63%). Two models were well matured within 1 month. Fertilizer products are used to grow mung beans (Vigna Radiata). They help in fast-growing plants (height from 20 to 22cm) with good green leaves (leaves width from 3-5 cm). Overall, the model has the potential to be broadly applied, helping to reduce the amount of MSW to be treated, saving costs, and creating a closed cycle towards a circular economy model.
Assessment of indoor air quality of the furniture manufacturers in Binh Duong industrial parks, Vietnam
Authors: Pham A D , Nguyen T T H , Vu T M H 
Published: June 2024

Abstract
Wood furniture and related products are created from raw wood and or wood products that require cutting, sanding, and other handling activities that generate wood dust. Exposure to indoor factory air pollutants can have significant health consequences for workers and nearby communities. Therefore, it was necessary to implement the assessment of indoor air quality in furniture manufacturers. This study mainly aimed to assess the indoor air quality status of physical and chemical aspects at 3 different furniture factories. Each sample was analysed for eight parameters including TSP, PM10, PM2.5, noise, temperature, humidity, wind, and light. Sampling and sample handling techniques were performed based on the usage test methods of Vietnam standards. The concentrations of TSP (194 – 493 μg/m3), PM10 (106.7 – 153.8 μg/m3), PM2.5 (72.8 – 95.6 μg/m3); and, the variables of noise (70.4 – 80.3 dBA), temperature (29.4 – 32.4 °C), humidity (58.0 – 69.4 %), wind (0.29 – 0.49) and light (327 – 573) these considered at 3 furniture manufacturers were within the allowable thresholds of QCVN 02:2019/BYT (Permissible exposure limit value of dust at the workplace), QCVN24:2016/BYT (Permissible exposure levels of noise in the workplace), QCVN26:2016/BYT (Permissible value of microclimate in the workplace); and, QCVN22:2016/BYT (Permissible levels of lighting in the workplace). However, long-term direct exposure of workers to these pollutants would also result in potential health risks. This study also suggested the management and technical control solutions to contribute to improving air quality for furniture manufacturers.