Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2791/1/012058
Peng Shen, Yan Zhang
Due to the lack of elevation information, the traditional airport design system based on the AutoCAD 2D platform is often unable to make a comprehensive and objective analysis and judgment when the designer evaluates the advantages and disadvantages of the design scheme. Therefore, this paper focuses on the development of airport 3D dynamic design and decision systems based on the Cesium framework. Firstly, based on the 3D geographic information platform, a multi-type 3D digital map loading and display module will be developed to realize the combination of 3D geographic information and the airfield model. Then, according to the 3D model data and the characteristics of the platform development, the method of calculating the earth volume of clearance processing, the evaluation algorithm of airport clearance obstacle limit surface, the optimization analysis method of tower position, and the analysis method of navigation station and flight track visibility are constructed.
{"title":"Research on three-dimensional dynamic design and decision system of airport","authors":"Peng Shen, Yan Zhang","doi":"10.1088/1742-6596/2791/1/012058","DOIUrl":"https://doi.org/10.1088/1742-6596/2791/1/012058","url":null,"abstract":"\u0000 Due to the lack of elevation information, the traditional airport design system based on the AutoCAD 2D platform is often unable to make a comprehensive and objective analysis and judgment when the designer evaluates the advantages and disadvantages of the design scheme. Therefore, this paper focuses on the development of airport 3D dynamic design and decision systems based on the Cesium framework. Firstly, based on the 3D geographic information platform, a multi-type 3D digital map loading and display module will be developed to realize the combination of 3D geographic information and the airfield model. Then, according to the 3D model data and the characteristics of the platform development, the method of calculating the earth volume of clearance processing, the evaluation algorithm of airport clearance obstacle limit surface, the optimization analysis method of tower position, and the analysis method of navigation station and flight track visibility are constructed.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"81 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141701584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2774/1/012033
Hongxi Yu, Liang Xu, Lu Yang, Dongqi Li, Ke Xu, Li Li
This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.
{"title":"Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots","authors":"Hongxi Yu, Liang Xu, Lu Yang, Dongqi Li, Ke Xu, Li Li","doi":"10.1088/1742-6596/2774/1/012033","DOIUrl":"https://doi.org/10.1088/1742-6596/2774/1/012033","url":null,"abstract":"\u0000 This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"299 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2806/1/012003
Gao Jing, Zhongxiao Du, Shuxiang Yang, Yingqi Xu, Xu Sibo
This article focuses on the intelligent heating platform driven by digital twins, analyzing the overall framework of the system according to the sensor layer, application layer, and network layer, and building an information service platform for intelligent heating networks. The data of the entire heating system, including heat sources, primary networks, heating stations, secondary networks, and heat users, is remotely collected, analyzed, and diagnosed. Subsequently, statistical analysis is conducted on the energy consumption of each heat source and heating station, achieving data sharing and data mining among various business systems. This article conducts research on several key technologies for optimizing decision-making methods of heating system operation scheduling based on simulation models and develops software systems to support the intelligent upgrading of heating systems. The results show that intelligent heating system based on digital twins can better meet the balance between supply and demand in urban heating systems, and optimize the overall operating costs and environmental benefits of the system under multiple constraints.
{"title":"Research on Intelligent Heating for Urban Systems Based on Digital Twin","authors":"Gao Jing, Zhongxiao Du, Shuxiang Yang, Yingqi Xu, Xu Sibo","doi":"10.1088/1742-6596/2806/1/012003","DOIUrl":"https://doi.org/10.1088/1742-6596/2806/1/012003","url":null,"abstract":"\u0000 This article focuses on the intelligent heating platform driven by digital twins, analyzing the overall framework of the system according to the sensor layer, application layer, and network layer, and building an information service platform for intelligent heating networks. The data of the entire heating system, including heat sources, primary networks, heating stations, secondary networks, and heat users, is remotely collected, analyzed, and diagnosed. Subsequently, statistical analysis is conducted on the energy consumption of each heat source and heating station, achieving data sharing and data mining among various business systems. This article conducts research on several key technologies for optimizing decision-making methods of heating system operation scheduling based on simulation models and develops software systems to support the intelligent upgrading of heating systems. The results show that intelligent heating system based on digital twins can better meet the balance between supply and demand in urban heating systems, and optimize the overall operating costs and environmental benefits of the system under multiple constraints.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"261 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2774/1/012085
Yutong Wang, Chenyong Zhao, Heping Jia
As a country rich in hydropower resources, the transmission of Southwest hydropower through HVDC system can achieve a large range of optimal allocation of resources, but the traditional HVDC transmission plan is often operated in high and low binary value, which is difficult to give full play to the flexibility of HVDC transmission, and increase the carbon emission and operation cost of the power system. In order to fully explore the flexibility of HVDC transmission mode to reduce system carbon emissions, this paper builds a mixed integer programming model based on the scenario of hydropower being sent to the receiving system through the HVDC system, taking into account such factors as low operating costs and carbon dioxide emissions of thermal power units at the receiving end, overload capacity of the HVDC system, and reactive power compensation cost of the HVDC system. A low carbon scheduling method for cascade hydropower HVDC flexible delivery system is proposed. Finally, taking the cross-regional transmission system of cascade hydropower station as an example, the model proposed in this paper is compared with the high-low binary transmission of traditional HVDC system. The results show that the dispatch mode proposed in this paper and the flexible operation of the HVDC system can promote the consumption of new energy, reduce the CO2 emissions of the system and achieve the dispatch goal of both low carbon and economic operation.
{"title":"A Low-carbon Dispatching Method for Cascade Hydropower via HVDC Flexible Delivery","authors":"Yutong Wang, Chenyong Zhao, Heping Jia","doi":"10.1088/1742-6596/2774/1/012085","DOIUrl":"https://doi.org/10.1088/1742-6596/2774/1/012085","url":null,"abstract":"\u0000 As a country rich in hydropower resources, the transmission of Southwest hydropower through HVDC system can achieve a large range of optimal allocation of resources, but the traditional HVDC transmission plan is often operated in high and low binary value, which is difficult to give full play to the flexibility of HVDC transmission, and increase the carbon emission and operation cost of the power system. In order to fully explore the flexibility of HVDC transmission mode to reduce system carbon emissions, this paper builds a mixed integer programming model based on the scenario of hydropower being sent to the receiving system through the HVDC system, taking into account such factors as low operating costs and carbon dioxide emissions of thermal power units at the receiving end, overload capacity of the HVDC system, and reactive power compensation cost of the HVDC system. A low carbon scheduling method for cascade hydropower HVDC flexible delivery system is proposed. Finally, taking the cross-regional transmission system of cascade hydropower station as an example, the model proposed in this paper is compared with the high-low binary transmission of traditional HVDC system. The results show that the dispatch mode proposed in this paper and the flexible operation of the HVDC system can promote the consumption of new energy, reduce the CO2 emissions of the system and achieve the dispatch goal of both low carbon and economic operation.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"16 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141841473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Routine urine tests play a vital role in the diagnosis of kidney and urinary system diseases, with test outcomes directly affecting disease diagnosis. However, if urine is exposed to room temperature for extended periods, it may lead to rapid degradation of the sample, thus affecting the accuracy of the test. Therefore, for urine that requires long-term storage for testing, it is necessary to control the temperature within an appropriate range during the collection process to effectively preserve the activity of urinary proteins and ensure the reliability of the test. To address this issue, a cryogenic urine storage system was developed, and a fuzzy LADRC temperature control algorithm combined with a Smith predictor was proposed, specifically designed for optimizing the temperature stability during urine collection and storage processes. Initially, the characteristics of the cryogenic storage system were analyzed. A simulation model combining the fuzzy LADRC with a Smith predictor was built using the MATLAB/Simulink simulation toolkit, and a comparative simulation was conducted. The simulation results showed that the proposed algorithm significantly improved the time-domain response performance compared to PID control, verifying the superiority of the algorithm over PID control. The final experimental results demonstrated that the fuzzy LADRC temperature control algorithm with the Smith predictor essentially eliminated overshoot, with improvements in speed and stability compared to PID control.
尿液常规检测在诊断肾脏和泌尿系统疾病方面发挥着重要作用，检测结果直接影响疾病诊断。然而，如果尿液长期暴露在室温下，可能会导致样本迅速降解，从而影响检验的准确性。因此，对于需要长期储存检测的尿液，有必要在采集过程中将温度控制在适当的范围内，以有效保存尿蛋白的活性，确保检测的可靠性。针对这一问题，我们开发了一种低温尿液储存系统，并提出了一种结合史密斯预测器的模糊 LADRC 温度控制算法，专门用于优化尿液采集和储存过程中的温度稳定性。首先，对低温储存系统的特性进行了分析。使用 MATLAB/Simulink 仿真工具包建立了模糊 LADRC 与 Smith 预测器相结合的仿真模型，并进行了对比仿真。仿真结果表明，与 PID 控制相比，所提出的算法显著改善了时域响应性能，验证了该算法优于 PID 控制。最终的实验结果表明，与 PID 控制相比，采用 Smith 预测器的模糊 LADRC 温度控制算法基本上消除了超调，并提高了速度和稳定性。
{"title":"Research on the temperature control of a cryogenic urine storage system based on improved adaptive LADRC","authors":"Changjian Zhu, Yu Jiang, Donghua Shen, Youpeng Zhao","doi":"10.1088/1742-6596/2806/1/012023","DOIUrl":"https://doi.org/10.1088/1742-6596/2806/1/012023","url":null,"abstract":"\u0000 Routine urine tests play a vital role in the diagnosis of kidney and urinary system diseases, with test outcomes directly affecting disease diagnosis. However, if urine is exposed to room temperature for extended periods, it may lead to rapid degradation of the sample, thus affecting the accuracy of the test. Therefore, for urine that requires long-term storage for testing, it is necessary to control the temperature within an appropriate range during the collection process to effectively preserve the activity of urinary proteins and ensure the reliability of the test. To address this issue, a cryogenic urine storage system was developed, and a fuzzy LADRC temperature control algorithm combined with a Smith predictor was proposed, specifically designed for optimizing the temperature stability during urine collection and storage processes. Initially, the characteristics of the cryogenic storage system were analyzed. A simulation model combining the fuzzy LADRC with a Smith predictor was built using the MATLAB/Simulink simulation toolkit, and a comparative simulation was conducted. The simulation results showed that the proposed algorithm significantly improved the time-domain response performance compared to PID control, verifying the superiority of the algorithm over PID control. The final experimental results demonstrated that the fuzzy LADRC temperature control algorithm with the Smith predictor essentially eliminated overshoot, with improvements in speed and stability compared to PID control.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"105 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141842563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2806/1/012021
Zhiling Qian, Yuan Yuhao
Bone age can be predicted by taking hand X-rays. Prediction of bone age is a labor-intensive and time-consuming radiological clinical task. This paper combined a series of prevailing deep learning methods to address this problem. Stages1~3 of Swin Transformer served as backbone, with the multi-scale neck network and detection head of Yolox connected to it. These formed the first period’s hand bone joints detector. After finishing detector training, the pre-trained Stages1~3 were frozen for the second period’s developmental grades classification of corresponding bone joint. Additionally, a linear classification head was attached to Swin Transformer’s stage4, where it functioned as second period’s classifier for different developmental grades. Therefore, a dual-purpose composite network was created like this. It made the bone age prediction model have high integrated level, and the two periods could be applied fusion training. In addition, different attention mechanisms were introduced at different positions, loss functions and optimization methods were also redesigned to ensure improvement of network performance. In the hand bone joints detection period, compared to the original Yolox-X, there was a 5.27% increase in Ap@50 and a 40.12% increase in Ap@50:95. As for the developmental grade classification period, the validation accuracy surpassed that of EfficientNetV2-L by 5.18%, with one-third the training size.
{"title":"Design of bifunctional composite bone age prediction network based on Swin-Transformer","authors":"Zhiling Qian, Yuan Yuhao","doi":"10.1088/1742-6596/2806/1/012021","DOIUrl":"https://doi.org/10.1088/1742-6596/2806/1/012021","url":null,"abstract":"\u0000 Bone age can be predicted by taking hand X-rays. Prediction of bone age is a labor-intensive and time-consuming radiological clinical task. This paper combined a series of prevailing deep learning methods to address this problem. Stages1~3 of Swin Transformer served as backbone, with the multi-scale neck network and detection head of Yolox connected to it. These formed the first period’s hand bone joints detector. After finishing detector training, the pre-trained Stages1~3 were frozen for the second period’s developmental grades classification of corresponding bone joint. Additionally, a linear classification head was attached to Swin Transformer’s stage4, where it functioned as second period’s classifier for different developmental grades. Therefore, a dual-purpose composite network was created like this. It made the bone age prediction model have high integrated level, and the two periods could be applied fusion training. In addition, different attention mechanisms were introduced at different positions, loss functions and optimization methods were also redesigned to ensure improvement of network performance. In the hand bone joints detection period, compared to the original Yolox-X, there was a 5.27% increase in Ap@50 and a 40.12% increase in Ap@50:95. As for the developmental grade classification period, the validation accuracy surpassed that of EfficientNetV2-L by 5.18%, with one-third the training size.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"16 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141843185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2793/1/012010
C. Lee, Chien-Kuan Liu, Y. Cheng
This work focuses on applying a novel and integrated multi-objective optimization approach to enhance the strength of the railway bogie frame system under both static loads and fatigue tests. The finite element modelling is conducted using ANSYS/Workbench software, and the von Mises stress and fatigue safety factor of the bogie frame are computed through conventional simulations for EN 13749 and EN 15663 testing. After employing the uniform design method, the fatigue safety factor is increased from 1.924 to 2.586, resulting in a 34.41% improvement rate for the bogie frame. Additionally, the von Mises stress is reduced from 56.96 MPa to 42.91 MPa, reflecting a 24.66% improvement rate compared to the original design. Following the implementation of the multi-objective optimum design process, the fatigue safety factor further improves from 1.924 to 2.742, resulting in a 42.51% enhancement for the bogie frame. Simultaneously, the von Mises stress decreases from 56.96 MPa to 40.48 MPa, yielding an improvement rate of 28.92%.
{"title":"Multi-objective optimal design for the railway bogie frame system under stress and fatigue analysis","authors":"C. Lee, Chien-Kuan Liu, Y. Cheng","doi":"10.1088/1742-6596/2793/1/012010","DOIUrl":"https://doi.org/10.1088/1742-6596/2793/1/012010","url":null,"abstract":"\u0000 This work focuses on applying a novel and integrated multi-objective optimization approach to enhance the strength of the railway bogie frame system under both static loads and fatigue tests. The finite element modelling is conducted using ANSYS/Workbench software, and the von Mises stress and fatigue safety factor of the bogie frame are computed through conventional simulations for EN 13749 and EN 15663 testing. After employing the uniform design method, the fatigue safety factor is increased from 1.924 to 2.586, resulting in a 34.41% improvement rate for the bogie frame. Additionally, the von Mises stress is reduced from 56.96 MPa to 42.91 MPa, reflecting a 24.66% improvement rate compared to the original design. Following the implementation of the multi-objective optimum design process, the fatigue safety factor further improves from 1.924 to 2.742, resulting in a 42.51% enhancement for the bogie frame. Simultaneously, the von Mises stress decreases from 56.96 MPa to 40.48 MPa, yielding an improvement rate of 28.92%.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"120 S7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141843718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Insulator strings are important components in power systems to support and isolate transmission lines. Due to long-term exposure to the natural environment, insulator strings are susceptible to damage, such as self-explosion, broken umbrella skirts, and galvanic corrosion, which is one of the most common failures. Once damaged, it can lead to widespread power outage, which affects people’s life and industrial production, so it is necessary to inspect and replace the damaged insulator strings regularly. This thesis proposes a quadratic sampling based approach to assess the quality of insulator string sample banks. Through simple random sampling, estimation and interval estimation of the sample pool, the pass rate and average number of labels of the original sample pool are initially assessed and compared with the usage requirements to decide whether to carry out a second sampling or not; the second sampling used SADS as an evaluation metric to assess the performance of the insulator string sample bank.
{"title":"Quality Assessment Method for Insulator Sample Bank Based on Sampling Theory","authors":"Jie Wei, Xing He, Zhihan Yi, Xizhe Li, Rui Song, Jian Chen","doi":"10.1088/1742-6596/2774/1/012057","DOIUrl":"https://doi.org/10.1088/1742-6596/2774/1/012057","url":null,"abstract":"\u0000 Insulator strings are important components in power systems to support and isolate transmission lines. Due to long-term exposure to the natural environment, insulator strings are susceptible to damage, such as self-explosion, broken umbrella skirts, and galvanic corrosion, which is one of the most common failures. Once damaged, it can lead to widespread power outage, which affects people’s life and industrial production, so it is necessary to inspect and replace the damaged insulator strings regularly. This thesis proposes a quadratic sampling based approach to assess the quality of insulator string sample banks. Through simple random sampling, estimation and interval estimation of the sample pool, the pass rate and average number of labels of the original sample pool are initially assessed and compared with the usage requirements to decide whether to carry out a second sampling or not; the second sampling used SADS as an evaluation metric to assess the performance of the insulator string sample bank.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"98 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141843876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2795/1/012009
Pengcheng Duan
The energy sector is undergoing a significant transformation, driven by the urgent need to address climate change, enhance energy security, and cater to the growing demand for electricity. In the context of escalating global energy demands and environmental concerns, this study investigates the integration and application of smart grid and microgrid technologies within the Western Pipeline Company’s operations. Addressing the critical need for sustainable energy solutions, our research focuses on enhancing system efficiency, reliability, and user satisfaction while reducing environmental impacts. Our findings reveal significant improvements in peak load reduction (15.3%), total energy reduction (20.46%), and carbon emission reduction (30.01%) compared to conventional methods. Moreover, the study demonstrates a marked increase in system reliability (95.35%) and a substantial decrease in response times (2.6 seconds), highlighting the efficiency of our integrated energy management strategies. The research also underscores notable advancements in customer satisfaction (90.13%), maintenance cost reduction (50.4%), and renewable energy utilization (75.80%), affirming the effectiveness and economic viability of implementing advanced grid technologies.
{"title":"Integration of Smart Grid and Application of Microgrid Technologies in Western Pipeline Company","authors":"Pengcheng Duan","doi":"10.1088/1742-6596/2795/1/012009","DOIUrl":"https://doi.org/10.1088/1742-6596/2795/1/012009","url":null,"abstract":"\u0000 The energy sector is undergoing a significant transformation, driven by the urgent need to address climate change, enhance energy security, and cater to the growing demand for electricity. In the context of escalating global energy demands and environmental concerns, this study investigates the integration and application of smart grid and microgrid technologies within the Western Pipeline Company’s operations. Addressing the critical need for sustainable energy solutions, our research focuses on enhancing system efficiency, reliability, and user satisfaction while reducing environmental impacts. Our findings reveal significant improvements in peak load reduction (15.3%), total energy reduction (20.46%), and carbon emission reduction (30.01%) compared to conventional methods. Moreover, the study demonstrates a marked increase in system reliability (95.35%) and a substantial decrease in response times (2.6 seconds), highlighting the efficiency of our integrated energy management strategies. The research also underscores notable advancements in customer satisfaction (90.13%), maintenance cost reduction (50.4%), and renewable energy utilization (75.80%), affirming the effectiveness and economic viability of implementing advanced grid technologies.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"76 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141843910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1088/1742-6596/2774/1/012047
Yilong Guo, Siwen Chen, Shiyou Xing, Jinlei Sun, Shiyan Pan
Hybrid Capacitive Battery (HCB) is an emerging electrochemical energy storage device that holds immense potential in the application of future energy storage systems (ESSs). When the ESS composed of HCBs is controlled and scheduled, it is necessary to understand its ability to release or absorb power. Therefore, accurate power prediction of batteries is crucial. This paper introduces a method for estimating the state of power (SOP) in HCB using the particle swarm optimization (PSO) algorithm. The method mainly consists of three parts: first, an equivalent circuit model (ECM) is employed to accurately represent the HCB, then an H-∞ filter algorithm is used to estimate its state of energy (SOE). In the third step, an optimization objective function is established based on the HCB model to describe the terminal voltage changes during its charging and discharging process, and use PSO algorithm to solve and obtain the estimated SOP results. Finally, the reference values of the SOP were obtained through constant power pulse testing experiments, proving that this method can effectively predict SOP under constant power conditions.
{"title":"State of Power Estimation Method for Hybrid Capacitor Battery Based on PSO Algorithm","authors":"Yilong Guo, Siwen Chen, Shiyou Xing, Jinlei Sun, Shiyan Pan","doi":"10.1088/1742-6596/2774/1/012047","DOIUrl":"https://doi.org/10.1088/1742-6596/2774/1/012047","url":null,"abstract":"\u0000 Hybrid Capacitive Battery (HCB) is an emerging electrochemical energy storage device that holds immense potential in the application of future energy storage systems (ESSs). When the ESS composed of HCBs is controlled and scheduled, it is necessary to understand its ability to release or absorb power. Therefore, accurate power prediction of batteries is crucial. This paper introduces a method for estimating the state of power (SOP) in HCB using the particle swarm optimization (PSO) algorithm. The method mainly consists of three parts: first, an equivalent circuit model (ECM) is employed to accurately represent the HCB, then an H-∞ filter algorithm is used to estimate its state of energy (SOE). In the third step, an optimization objective function is established based on the HCB model to describe the terminal voltage changes during its charging and discharging process, and use PSO algorithm to solve and obtain the estimated SOP results. Finally, the reference values of the SOP were obtained through constant power pulse testing experiments, proving that this method can effectively predict SOP under constant power conditions.","PeriodicalId":506941,"journal":{"name":"Journal of Physics: Conference Series","volume":"20 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141844796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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