Jhon Francined Herrera-Cubides, Paulo Alonso Gaona-García, Carlos Enrique Montenegro-Marin, Salvador Sánchez-Alonso
Open data has been improving both publishing platforms and the consumers-oriented process over the years, providing better openness policies and transparency. Although organizations have tried to open their data, the enrichment of their resources through the Web of Data has been decreasing. Linked data has been suffering from notable difficulties in different stages of its life cycle, becoming over the years less attractive to users. According to that, we decided to explore how the lack of some opening requirements affects the decline of the Web of Data. This paper presents the Web of Data radiography, analyzing the governmental domain as a case study. The results indicate that it is necessary to strengthen the data opening process to improve resource enrichment on the Web and have better datasets. These improvements describe that open data must be public, accessible (in machine-readable formats), described (use of robust, granular metadata), reusable (made available under an open license), complete (published in primary forms), and timely (preserve the value of the data). The implementation of these characteristics would enhance the availability and reuse of datasets. Besides, organizations must understand that opening and enriching their data require a completely new approach, and they have to pay special attention and control to this project, generally by putting money, the commitment by management at all levels, and lots of time. On the contrary, given the magnitude of availability and reuse problems identified in the opening and enrichment data process, it is believed that the Web of Data model would inevitably lose the interest it aroused at the beginning if not addressed immediately by data quality, openness, and enrichment issues. Besides, its use would be restricted to a few particular niches or would even disappear altogether.
多年来，开放数据一直在改善出版平台和以消费者为导向的过程，提供更好的开放政策和透明度。尽管组织已经尝试开放他们的数据，但是通过Web of data丰富他们的资源却一直在减少。关联数据在其生命周期的不同阶段一直遭受着明显的困难，多年来对用户的吸引力越来越小。基于此，我们决定探讨一些开放要求的缺失是如何影响Web of Data的衰落的。本文介绍了数据网络放射学，并以政府领域为例进行了分析。结果表明，要提高Web资源的丰富性，获得更好的数据集，必须加强数据开放过程。这些改进描述了开放数据必须是公开的、可访问的(以机器可读的格式)、可描述的(使用健壮的、细粒度的元数据)、可重用的(在开放许可下可用)、完整的(以主要形式发布)和及时的(保留数据的价值)。这些特征的实现将增强数据集的可用性和重用性。此外，组织必须明白，开放和丰富他们的数据需要一种全新的方法，他们必须特别关注和控制这个项目，通常是通过投入资金、各级管理层的承诺和大量的时间。相反，考虑到开放和丰富数据过程中发现的可用性和重用问题的严重性，人们认为，如果不立即解决数据质量、开放性和丰富问题，数据Web模型将不可避免地失去最初引起的兴趣。此外，它的使用将被限制在少数特定的利基，甚至完全消失。
{"title":"The Relevance of Open Data Principles for the Web of Data","authors":"Jhon Francined Herrera-Cubides, Paulo Alonso Gaona-García, Carlos Enrique Montenegro-Marin, Salvador Sánchez-Alonso","doi":"10.1155/2023/4854965","DOIUrl":"https://doi.org/10.1155/2023/4854965","url":null,"abstract":"Open data has been improving both publishing platforms and the consumers-oriented process over the years, providing better openness policies and transparency. Although organizations have tried to open their data, the enrichment of their resources through the Web of Data has been decreasing. Linked data has been suffering from notable difficulties in different stages of its life cycle, becoming over the years less attractive to users. According to that, we decided to explore how the lack of some opening requirements affects the decline of the Web of Data. This paper presents the Web of Data radiography, analyzing the governmental domain as a case study. The results indicate that it is necessary to strengthen the data opening process to improve resource enrichment on the Web and have better datasets. These improvements describe that open data must be public, accessible (in machine-readable formats), described (use of robust, granular metadata), reusable (made available under an open license), complete (published in primary forms), and timely (preserve the value of the data). The implementation of these characteristics would enhance the availability and reuse of datasets. Besides, organizations must understand that opening and enriching their data require a completely new approach, and they have to pay special attention and control to this project, generally by putting money, the commitment by management at all levels, and lots of time. On the contrary, given the magnitude of availability and reuse problems identified in the opening and enrichment data process, it is believed that the Web of Data model would inevitably lose the interest it aroused at the beginning if not addressed immediately by data quality, openness, and enrichment issues. Besides, its use would be restricted to a few particular niches or would even disappear altogether.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135552547","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}
The precise estimation of the state of health (SOH) for lithium-ion batteries (LIBs) is one of the core problems for battery management systems. To address the problem that it is difficult to accurately evaluate SOH because of the LIB capacity regeneration phenomenon, this paper proposes an approach for LIB SOH estimation using isobaric energy analysis and improved long short-term memory neural network (LSTM NN). Specifically, at first, the isobaric energy curve is plotted by analyzing the battery energy variation during the constant current charging stage. Then, the mean peak value of the isobaric energy curve is extracted as a health factor to characterize the battery SOH aging. Eventually, the LIB SOH estimation model is developed using the improved LSTM NN. In this regard, the improved LSTM NN refers to the selection of the number of hidden layers and the learning rate of the LSTM NN using the particle swarm algorithm (PSO). To verify the precision of the proposed method, validation experiments are performed based on four battery aging data with different charging multipliers. The experimental results indicate that the proposed method can effectively estimate the LIB SOH. Meanwhile, the proposed method is compared with other conventional machine learning algorithms, which demonstrates that the proposed method has better estimation performance.
{"title":"Lithium-Ion Battery State-of-Health Estimation Method Using Isobaric Energy Analysis and PSO-LSTM","authors":"Shaishai Zhao, Laijin Luo, Shanhe Jiang, Chaolong Zhang","doi":"10.1155/2023/5566965","DOIUrl":"https://doi.org/10.1155/2023/5566965","url":null,"abstract":"The precise estimation of the state of health (SOH) for lithium-ion batteries (LIBs) is one of the core problems for battery management systems. To address the problem that it is difficult to accurately evaluate SOH because of the LIB capacity regeneration phenomenon, this paper proposes an approach for LIB SOH estimation using isobaric energy analysis and improved long short-term memory neural network (LSTM NN). Specifically, at first, the isobaric energy curve is plotted by analyzing the battery energy variation during the constant current charging stage. Then, the mean peak value of the isobaric energy curve is extracted as a health factor to characterize the battery SOH aging. Eventually, the LIB SOH estimation model is developed using the improved LSTM NN. In this regard, the improved LSTM NN refers to the selection of the number of hidden layers and the learning rate of the LSTM NN using the particle swarm algorithm (PSO). To verify the precision of the proposed method, validation experiments are performed based on four battery aging data with different charging multipliers. The experimental results indicate that the proposed method can effectively estimate the LIB SOH. Meanwhile, the proposed method is compared with other conventional machine learning algorithms, which demonstrates that the proposed method has better estimation performance.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135937817","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}
The management of clean energy is usually the key for environmental, economic, and sustainable developments. In the meantime, the energy management system (EMS) ensures the clean energy which includes many sources grouped in a small power plant such as microgrid (MG). In this case, the forecasting methods are used for helping the EMS and allow the high efficiency to the clean energy. The aim of this review paper is providing the necessary data about the basic principles and standards of photovoltaic (PV) power forecasting by stating numerous research studies carried out on the PV power forecasting topic specifically in the short-term time horizon which is advantageous for the EMS and grid operator. At the same time, this contribution can offer a state of the art in different methods and approaches used for PV power forecasting along with a careful study of different time and spatial horizons. Furthermore, this current review paper can support the tenders in the PV power forecasting.
{"title":"Solar Photovoltaic Power Forecasting","authors":"Abdelhakim El hendouzi, Abdennaser Bourouhou","doi":"10.1155/2020/8819925","DOIUrl":"https://doi.org/10.1155/2020/8819925","url":null,"abstract":"The management of clean energy is usually the key for environmental, economic, and sustainable developments. In the meantime, the energy management system (EMS) ensures the clean energy which includes many sources grouped in a small power plant such as microgrid (MG). In this case, the forecasting methods are used for helping the EMS and allow the high efficiency to the clean energy. The aim of this review paper is providing the necessary data about the basic principles and standards of photovoltaic (PV) power forecasting by stating numerous research studies carried out on the PV power forecasting topic specifically in the short-term time horizon which is advantageous for the EMS and grid operator. At the same time, this contribution can offer a state of the art in different methods and approaches used for PV power forecasting along with a careful study of different time and spatial horizons. Furthermore, this current review paper can support the tenders in the PV power forecasting.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44782534","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}
Deguang Li, Tianhao Wu, Xiaohui Li, Qiurui He, Zhanyou Cui
Environmental quality is a great concern to everyone, in order to realize the collection, upload, management, and visualization of parameters of atmospheric environment in real time. We propose a cheap, low-power, and fast deployment wireless sensor node for environmental monitoring, consisting of STM32 MCU, ESP8266, light sensor, rain sensor, UV sensor, seven-in-one sensor (including temperature, humidity, PM2.5, PM10, CO2, formaldehyde, and TVOC), and solar automatic tracking module. A customized μC/OS-III runs on the node, which controls the transmission of environment parameters collected by each sensor to the cloud server through the wireless network, and then the server receives, stores, and visualizes the data. In actual test, the node collects data once an hour, and the running power of the node is low and stable. Experimental results show that the node could achieve accurate collection and transmission and display the environmental data, and solar automatic tracking module could meet long-term running of the node in the night and continuous rainy days.
{"title":"A Wireless Multisensor Node for Long-Term Environmental Parameters Monitoring","authors":"Deguang Li, Tianhao Wu, Xiaohui Li, Qiurui He, Zhanyou Cui","doi":"10.1155/2020/8872711","DOIUrl":"https://doi.org/10.1155/2020/8872711","url":null,"abstract":"Environmental quality is a great concern to everyone, in order to realize the collection, upload, management, and visualization of parameters of atmospheric environment in real time. We propose a cheap, low-power, and fast deployment wireless sensor node for environmental monitoring, consisting of STM32 MCU, ESP8266, light sensor, rain sensor, UV sensor, seven-in-one sensor (including temperature, humidity, PM2.5, PM10, CO2, formaldehyde, and TVOC), and solar automatic tracking module. A customized μC/OS-III runs on the node, which controls the transmission of environment parameters collected by each sensor to the cloud server through the wireless network, and then the server receives, stores, and visualizes the data. In actual test, the node collects data once an hour, and the running power of the node is low and stable. Experimental results show that the node could achieve accurate collection and transmission and display the environmental data, and solar automatic tracking module could meet long-term running of the node in the night and continuous rainy days.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2020-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47385843","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}
This paper performs a technoeconomic comparison of two hybrid renewable energy supplies (HRES) for a specific location in Ghana and suggests the optimal solution in terms of cost, energy generation capacity, and emissions. The two HRES considered in this paper were wind/hydrogen/fuel-cell and wind/battery storage, respectively. The necessity of this study was derived from the rise and expansion of hybrid renewable energy supply in a decentralised network. The readiness to embrace these new technologies is apparently high, but the best combination for a selected location that brings optimum benefits is not obvious and demands serious technical knowledge of their technical and economic models. In the methodology, an analytical model of energy generation by the various RE sources was first established, and data were collected about a rural-urban community in Doderkope, Ghana, to test the models. HOMER software was used to design the two hybrid systems based on the same load profiles, and results were compared. It turns out that the HRES 1 (wind/hydrogen/fuel-cell) had the lowest net present cost (NPC) and levelized cost of electricity (COE) over the project life span of 25 years. The energy reserve with the HRES 2 (wind/battery storage) was huge compared to that with the HRES 1, about 270% bigger. Furthermore, with respect to the emissions, the HRES 2 was environmentally friendlier than the HRES 1. Even though the battery storage seems to be more cost-effective than the hydrogen fuel-cell technology, the latter presents some merits regarding system capacity and emission that deserve greater attention as the world looks into more sustainable energy storage systems.
{"title":"Optimal Hybrid Renewable Energy System: A Comparative Study of Wind/Hydrogen/Fuel-Cell and Wind/Battery Storage","authors":"A. Acakpovi, P. Adjei, N. Nwulu, Nana Yaw Asabere","doi":"10.1155/2020/1756503","DOIUrl":"https://doi.org/10.1155/2020/1756503","url":null,"abstract":"This paper performs a technoeconomic comparison of two hybrid renewable energy supplies (HRES) for a specific location in Ghana and suggests the optimal solution in terms of cost, energy generation capacity, and emissions. The two HRES considered in this paper were wind/hydrogen/fuel-cell and wind/battery storage, respectively. The necessity of this study was derived from the rise and expansion of hybrid renewable energy supply in a decentralised network. The readiness to embrace these new technologies is apparently high, but the best combination for a selected location that brings optimum benefits is not obvious and demands serious technical knowledge of their technical and economic models. In the methodology, an analytical model of energy generation by the various RE sources was first established, and data were collected about a rural-urban community in Doderkope, Ghana, to test the models. HOMER software was used to design the two hybrid systems based on the same load profiles, and results were compared. It turns out that the HRES 1 (wind/hydrogen/fuel-cell) had the lowest net present cost (NPC) and levelized cost of electricity (COE) over the project life span of 25 years. The energy reserve with the HRES 2 (wind/battery storage) was huge compared to that with the HRES 1, about 270% bigger. Furthermore, with respect to the emissions, the HRES 2 was environmentally friendlier than the HRES 1. Even though the battery storage seems to be more cost-effective than the hydrogen fuel-cell technology, the latter presents some merits regarding system capacity and emission that deserve greater attention as the world looks into more sustainable energy storage systems.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46503838","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}
The preliminary atom set exits redundant atoms in the stochastic gradient matching pursuit algorithm, which affects the accuracy of the signal reconstruction and increases the computational complexity. To overcome the problem, an improved method is proposed. Firstly, a limited soft-threshold selection strategy is used to select the new atoms from the preliminary atom set, to reduce the redundancy of the preliminary atom set. Secondly, before finding the least squares solution of the residual, it is determined whether the number of columns of the measurement matrix is smaller than the number of rows. If the condition is satisfied, the least squares solution is calculated; otherwise, the loop is exited. Finally, if the length of the candidate atomic index set is less than the sparsity level, the current candidate atom index set is the support atom set. If the condition is not satisfied, the support atom index set is determined by the least squares solution. Simulation results indicate that the proposed method is better than other methods in terms of the reconstruction probability and shorter running time than the stochastic gradient matching pursuit algorithm.
{"title":"Improved Stochastic Gradient Matching Pursuit Algorithm Based on the Soft-Thresholds Selection","authors":"Liquan Zhao, Yunfeng Hu","doi":"10.1155/2018/9130531","DOIUrl":"https://doi.org/10.1155/2018/9130531","url":null,"abstract":"The preliminary atom set exits redundant atoms in the stochastic gradient matching pursuit algorithm, which affects the accuracy of the signal reconstruction and increases the computational complexity. To overcome the problem, an improved method is proposed. Firstly, a limited soft-threshold selection strategy is used to select the new atoms from the preliminary atom set, to reduce the redundancy of the preliminary atom set. Secondly, before finding the least squares solution of the residual, it is determined whether the number of columns of the measurement matrix is smaller than the number of rows. If the condition is satisfied, the least squares solution is calculated; otherwise, the loop is exited. Finally, if the length of the candidate atomic index set is less than the sparsity level, the current candidate atom index set is the support atom set. If the condition is not satisfied, the support atom index set is determined by the least squares solution. Simulation results indicate that the proposed method is better than other methods in terms of the reconstruction probability and shorter running time than the stochastic gradient matching pursuit algorithm.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2018-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/9130531","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64739370","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}
The feature fusion from separate source is the current technical difficulties of cross-corpus speech emotion recognition. The purpose of this paper is to, based on Deep Belief Nets DBN in Deep Learning, use the emotional information hiding in speech spectrum diagram spectrogram as image features and then implement feature fusion with the traditional emotion features. First, based on the spectrogram analysis by STB/Itti model, the new spectrogram features are extracted from the color, the brightness, and the orientation, respectively; then using two alternative DBN models they fuse the traditional and the spectrogram features, which increase the scale of the feature subset and the characterization ability of emotion. Through the experiment on ABC database and Chinese corpora, the new feature subset compared with traditional speech emotion features, the recognition result on cross-corpus, distinctly advances by 8.8%. The method proposed provides a new idea for feature fusion of emotion recognition.
{"title":"A Novel DBN Feature Fusion Model for Cross-Corpus Speech Emotion Recognition","authors":"Zou Cairong, Zhang Xinran, Zha Cheng, Zhao Li","doi":"10.1155/2016/7437860","DOIUrl":"https://doi.org/10.1155/2016/7437860","url":null,"abstract":"The feature fusion from separate source is the current technical difficulties of cross-corpus speech emotion recognition. The purpose of this paper is to, based on Deep Belief Nets DBN in Deep Learning, use the emotional information hiding in speech spectrum diagram spectrogram as image features and then implement feature fusion with the traditional emotion features. First, based on the spectrogram analysis by STB/Itti model, the new spectrogram features are extracted from the color, the brightness, and the orientation, respectively; then using two alternative DBN models they fuse the traditional and the spectrogram features, which increase the scale of the feature subset and the characterization ability of emotion. Through the experiment on ABC database and Chinese corpora, the new feature subset compared with traditional speech emotion features, the recognition result on cross-corpus, distinctly advances by 8.8%. The method proposed provides a new idea for feature fusion of emotion recognition.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/7437860","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64521152","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}
Influenced by many uncertain and random factors, nonstationary, nonlinearity, and time-variety appear in power load series, which is difficult to forecast accurately. Aiming at locating these issues of power load forecasting, an innovative hybrid method is proposed to forecast power load in this paper. Firstly, ensemble empirical mode decomposition (EEMD) is used to decompose the power load series into a series of independent intrinsic mode functions (IMFs) and a residual term. Secondly, genetic algorithm (GA) is then applied to determine the best weights of each IMF and the residual term named ensemble empirical mode decomposition based on weight (WEEMD). Thirdly, least square support vector machine (LSSVM) and nonparametric generalized autoregressive conditional heteroscedasticity (NPGARCH) are employed to forecast the subseries, respectively, based on the characteristics of power load series. Finally, the forecasted power load of each component is summed as the final forecasted result of power load. Compared with other methods, the forecasting results of this proposed model applied to the electricity market of Pennsylvania-New Jersey-Maryland (PJM) indicate that the proposed model outperforms other models.
{"title":"A Novel Hybrid Method for Short-Term Power Load Forecasting","authors":"Huang Yuan-sheng, Huang Shen-hai, Song Jia-yin","doi":"10.1155/2016/2165324","DOIUrl":"https://doi.org/10.1155/2016/2165324","url":null,"abstract":"Influenced by many uncertain and random factors, nonstationary, nonlinearity, and time-variety appear in power load series, which is difficult to forecast accurately. Aiming at locating these issues of power load forecasting, an innovative hybrid method is proposed to forecast power load in this paper. Firstly, ensemble empirical mode decomposition (EEMD) is used to decompose the power load series into a series of independent intrinsic mode functions (IMFs) and a residual term. Secondly, genetic algorithm (GA) is then applied to determine the best weights of each IMF and the residual term named ensemble empirical mode decomposition based on weight (WEEMD). Thirdly, least square support vector machine (LSSVM) and nonparametric generalized autoregressive conditional heteroscedasticity (NPGARCH) are employed to forecast the subseries, respectively, based on the characteristics of power load series. Finally, the forecasted power load of each component is summed as the final forecasted result of power load. Compared with other methods, the forecasting results of this proposed model applied to the electricity market of Pennsylvania-New Jersey-Maryland (PJM) indicate that the proposed model outperforms other models.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/2165324","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64264263","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}
The voltage-source-converter- (VSC-) based multiterminal VSC-HVDC power transmission system (VSC-MTDC) is an ideal approach to connectwind farmwith power grid. Analyzing the characteristics of doubly fed induction generators aswell as the basic principle and the control strategy of VSC-MTDC, a multiterminal DC voltage control strategy suitable for wind farm connected with VSC-MTDC is proposed. By use of PSCAD/EMTDC, the proposed control strategy is simulated, and simulation results show that using the proposed control strategy the conversion between constant power control mode and constant DC voltage control mode can be automatically implemented; thus the DC voltage stability control and reliable power output of wind farm can be ensured after the fault-caused outage of converter station controlled by constant DC voltage and under other faults. The simulation result shows that the model can fulfill multiterminal power transmission and fast response control.
{"title":"Application of multipoint DC voltage control in VSC-MTDC system","authors":"Yang Xi, Ai Qian, Huang Jiantao, An Yiran","doi":"10.1155/2013/257387","DOIUrl":"https://doi.org/10.1155/2013/257387","url":null,"abstract":"The voltage-source-converter- (VSC-) based multiterminal VSC-HVDC power transmission system (VSC-MTDC) is an ideal approach to connectwind farmwith power grid. Analyzing the characteristics of doubly fed induction generators aswell as the basic principle and the control strategy of VSC-MTDC, a multiterminal DC voltage control strategy suitable for wind farm connected with VSC-MTDC is proposed. By use of PSCAD/EMTDC, the proposed control strategy is simulated, and simulation results show that using the proposed control strategy the conversion between constant power control mode and constant DC voltage control mode can be automatically implemented; thus the DC voltage stability control and reliable power output of wind farm can be ensured after the fault-caused outage of converter station controlled by constant DC voltage and under other faults. The simulation result shows that the model can fulfill multiterminal power transmission and fast response control.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2013/257387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64396950","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}
T. Gigl, F. Troesch, J. Preishuber-Pflügl, K. Witrisal
The IEEE 802.15.4a standard for wireless sensor networks is designed for high-accuracy ranging using ultra-wideband (UWB) signals. It supports coherent and noncoherent (energy detector) receivers, thus the performance-complexity-tradeoff can be decided by the implementer. In this paper, the maximum operating range and the maximum allowed pathloss are analyzed for ranging and both receiver types, under FCC/CEPT regulations. The analysis is based on the receiver working points and a link budget calculation assuming a frees-pace pathloss model. It takes into consideration the parameters of the preamble, which influence the transmit power allowed by the regulators. The best performance is achieved with the code sequences having the longest pulse spacing. Coherent receivers can achieve a maximum operating range up to several thousand meters and energy detectors up to several hundred meters.
{"title":"An Analysis of Coherent and Non-Coherent Receivers for Ranging in IEEE 802.15.4a","authors":"T. Gigl, F. Troesch, J. Preishuber-Pflügl, K. Witrisal","doi":"10.1155/2012/218930","DOIUrl":"https://doi.org/10.1155/2012/218930","url":null,"abstract":"The IEEE 802.15.4a standard for wireless sensor networks is designed for high-accuracy ranging using ultra-wideband (UWB) signals. It supports coherent and noncoherent (energy detector) receivers, thus the performance-complexity-tradeoff can be decided by the implementer. In this paper, the maximum operating range and the maximum allowed pathloss are analyzed for ranging and both receiver types, under FCC/CEPT regulations. The analysis is based on the receiver working points and a link budget calculation assuming a frees-pace pathloss model. It takes into consideration the parameters of the preamble, which influence the transmit power allowed by the regulators. The best performance is achieved with the code sequences having the longest pulse spacing. Coherent receivers can achieve a maximum operating range up to several thousand meters and energy detectors up to several hundred meters.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2012/218930","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64303919","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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