Pub Date : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548275
Nico Schütte, Alexander Neufeld, L. Hofmann, R. Dommerque, M. Nazemi
Increased installation of power cables and the intensified roll-out of power electronic equipment in the extra high voltage level pose challenges for network operators to assess network perturbations and power quality issues. In order to regulate harmonic levels in electric networks, grid operators are required to assign harmonic emission limits to the grid connection users. This ensures the compliance with the compatibility levels of the transmission grid. In this paper, the allocation procedure of harmonic current limits according to the novel German application rule VDE AR-N 4130 is compared with the approach from technical guideline IEC TR 61000-3-6. Key differences between both approaches are detected and presented on the basis of a case study. A restrictive component formulated in IEC method is elaborated, which is decisive for the differences occurring. Based on this finding, an adaptation of the allocation principle according to VDE is proposed. This adaptation enhances the allocation of comparable harmonic current emission limits.
{"title":"Harmonic Emission Limit Allocation Using VDE AR-N 4130: Application and Adaptation of Experiences from IEC TR 61000-3-6","authors":"Nico Schütte, Alexander Neufeld, L. Hofmann, R. Dommerque, M. Nazemi","doi":"10.1109/UPEC50034.2021.9548275","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548275","url":null,"abstract":"Increased installation of power cables and the intensified roll-out of power electronic equipment in the extra high voltage level pose challenges for network operators to assess network perturbations and power quality issues. In order to regulate harmonic levels in electric networks, grid operators are required to assign harmonic emission limits to the grid connection users. This ensures the compliance with the compatibility levels of the transmission grid. In this paper, the allocation procedure of harmonic current limits according to the novel German application rule VDE AR-N 4130 is compared with the approach from technical guideline IEC TR 61000-3-6. Key differences between both approaches are detected and presented on the basis of a case study. A restrictive component formulated in IEC method is elaborated, which is decisive for the differences occurring. Based on this finding, an adaptation of the allocation principle according to VDE is proposed. This adaptation enhances the allocation of comparable harmonic current emission limits.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126772623","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548182
Ammar AlYafai, Malik Salim Al-Shabibi, C. Rao
Due to the COVID-19 pandemic, the governments around the world were compelled to reduce business activity and took measures in response to minimize the impact of coronavirus. Under this condition the people lifestyle has been changed due to lockdown restrictions and other measures. Hence the electricity sector significantly affected under circumstance of COVID-19. The system demand and total energy consumptions in network is impacted by COVID-19.The main aim this paper is to review, analyze the weak links in the system during the COVID-19 time by comparing the load profiles at different load schedules with respect to different costumers. The analysis on the system load is as considered for the year 2019 of April and May months and compare with the same period of year 2020. However, there could be a difference in ambient weather conditions, which also will reflect on system load, the long period load and analyze the overall effect to minimize such weather-related variations effect. Therefore, this study reviews the impact of COVID-19 on one of the power systems loads in Oman. The results show that the peak load reduction, effective utilization of the operation and control on power system.
{"title":"Impact of COVID-19 on Power System Load: The case from Oman","authors":"Ammar AlYafai, Malik Salim Al-Shabibi, C. Rao","doi":"10.1109/UPEC50034.2021.9548182","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548182","url":null,"abstract":"Due to the COVID-19 pandemic, the governments around the world were compelled to reduce business activity and took measures in response to minimize the impact of coronavirus. Under this condition the people lifestyle has been changed due to lockdown restrictions and other measures. Hence the electricity sector significantly affected under circumstance of COVID-19. The system demand and total energy consumptions in network is impacted by COVID-19.The main aim this paper is to review, analyze the weak links in the system during the COVID-19 time by comparing the load profiles at different load schedules with respect to different costumers. The analysis on the system load is as considered for the year 2019 of April and May months and compare with the same period of year 2020. However, there could be a difference in ambient weather conditions, which also will reflect on system load, the long period load and analyze the overall effect to minimize such weather-related variations effect. Therefore, this study reviews the impact of COVID-19 on one of the power systems loads in Oman. The results show that the peak load reduction, effective utilization of the operation and control on power system.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124163574","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548156
F. Norouzi, L. Elizondo, T. Hoppe, P. Bauer
The dynamic behaviour - steady-state and transient - of the DC Microgrids during power disturbance can affect the system’s general performance. A hybrid combination of energy storage devices with slow frequency response, like a Fuel Cell, and with a fast dynamic response, like a Super-Capacitor, provides an improved dynamic response to stabilise DC bus voltage. However, control parameters should be designed based on the preferences of the system. This paper proposes a fuzzy-based controller to determine the Virtual Capacitor Droop controller to achieve the desired transient response. The proposed dynamic control method is validated through MATLAB/Simulink.
{"title":"An Adaptive Control Strategy for Dynamic Response of an Autonomous DC system","authors":"F. Norouzi, L. Elizondo, T. Hoppe, P. Bauer","doi":"10.1109/UPEC50034.2021.9548156","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548156","url":null,"abstract":"The dynamic behaviour - steady-state and transient - of the DC Microgrids during power disturbance can affect the system’s general performance. A hybrid combination of energy storage devices with slow frequency response, like a Fuel Cell, and with a fast dynamic response, like a Super-Capacitor, provides an improved dynamic response to stabilise DC bus voltage. However, control parameters should be designed based on the preferences of the system. This paper proposes a fuzzy-based controller to determine the Virtual Capacitor Droop controller to achieve the desired transient response. The proposed dynamic control method is validated through MATLAB/Simulink.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124353006","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548216
C. Hahn, Johannis Porst, M. Luther
This paper provides a comprehensive approach for mathematical modeling of Multiterminal VSC HVDC systems. The mathematical models are developed in the Laplace Domain as it offers appropriate opportunities regarding implementation in dynamic system analysis tools and the subsequent control design process. Models for the AC and DC side of the MMC as well as for the DC network are determined. The DC network model is based on the concatenation of pi-sections and is easily extendable to Multiterminal systems. Regarding the MMC, a model for the energy storage of the submodules in the converter arms is introduced. This aims in a detailed mathematical HVDC model and applies a connection via the energy storage of submodules within the converter arms. Based on the mathematical modeling, two control strategies are provided. The first strategy controls the active power via a subordinated AC grid controller in the dq-frame and the converter energy via the DC current controller on the DC side. The second strategy controls the converter energy via an AC grid controller and the active power via a DC current controller.
{"title":"Comprehensive Mathematical Modeling of Multilevel VSC HVDC Systems for Power System Stability Studies and Controller System Design","authors":"C. Hahn, Johannis Porst, M. Luther","doi":"10.1109/UPEC50034.2021.9548216","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548216","url":null,"abstract":"This paper provides a comprehensive approach for mathematical modeling of Multiterminal VSC HVDC systems. The mathematical models are developed in the Laplace Domain as it offers appropriate opportunities regarding implementation in dynamic system analysis tools and the subsequent control design process. Models for the AC and DC side of the MMC as well as for the DC network are determined. The DC network model is based on the concatenation of pi-sections and is easily extendable to Multiterminal systems. Regarding the MMC, a model for the energy storage of the submodules in the converter arms is introduced. This aims in a detailed mathematical HVDC model and applies a connection via the energy storage of submodules within the converter arms. Based on the mathematical modeling, two control strategies are provided. The first strategy controls the active power via a subordinated AC grid controller in the dq-frame and the converter energy via the DC current controller on the DC side. The second strategy controls the converter energy via an AC grid controller and the active power via a DC current controller.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130352428","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548251
Sascha Gritzbach, H. Çakmak, Pascal Mehnert, T. Ueckerdt, V. Hagenmeyer
The task of the Wind Farm Cable Layout Problem is to design a cable system between turbines and substations such that all turbine output can be transmitted to the substations. This problem can be modelled with different levels of complexity. While a higher level of complexity yields solutions that can be implemented in a real-world setting more readily, problem instances also become more difficult to solve or even remain intractable. More simplistic models are easier to solve but their usability could be inhibited. One such more simplistic model for installation cost minimization contains a network flow and a suitable minimum-cost flow algorithm provides good cable layouts on instances with up to 500 turbines within tens of seconds. The question remains whether those cable layouts are suitable for electrical implementation as well. We propose a workflow to evaluate the cable layouts generated from such algorithms under electrical aspects. This workflow converts the output of cable layout optimization algorithms to power flow models. The power flow models are simulated using the simulation framework eASiMOV. The evaluation of the power flow simulations under electrical metrics shows that output from the minimum-cost flow algorithm and from an approach solving a Mixed-Integer Linear Program perform very well under electrical aspects on a vast majority of input instances. For the remaining minority we are able to identify structures in the solutions that result in a worse performance. These observations can be used by the algorithm engineers as possible directions for future improvements.
{"title":"An Evaluation of Graph Algorithms for the Wind Farm Cable Layout Problem under Electrical Aspects","authors":"Sascha Gritzbach, H. Çakmak, Pascal Mehnert, T. Ueckerdt, V. Hagenmeyer","doi":"10.1109/UPEC50034.2021.9548251","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548251","url":null,"abstract":"The task of the Wind Farm Cable Layout Problem is to design a cable system between turbines and substations such that all turbine output can be transmitted to the substations. This problem can be modelled with different levels of complexity. While a higher level of complexity yields solutions that can be implemented in a real-world setting more readily, problem instances also become more difficult to solve or even remain intractable. More simplistic models are easier to solve but their usability could be inhibited. One such more simplistic model for installation cost minimization contains a network flow and a suitable minimum-cost flow algorithm provides good cable layouts on instances with up to 500 turbines within tens of seconds. The question remains whether those cable layouts are suitable for electrical implementation as well. We propose a workflow to evaluate the cable layouts generated from such algorithms under electrical aspects. This workflow converts the output of cable layout optimization algorithms to power flow models. The power flow models are simulated using the simulation framework eASiMOV. The evaluation of the power flow simulations under electrical metrics shows that output from the minimum-cost flow algorithm and from an approach solving a Mixed-Integer Linear Program perform very well under electrical aspects on a vast majority of input instances. For the remaining minority we are able to identify structures in the solutions that result in a worse performance. These observations can be used by the algorithm engineers as possible directions for future improvements.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130444352","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548244
B. Hunter, G. Lacey, Huda Dawood
Constantly increasing uptake of Electric Vehicles (EVs) necessitates a rapidly growing and evolving network of charging stations, including rapid charging systems which attempt to make up for the issue of slow charging. Rapid charging systems, however, can be difficult to implement in larger scale due to the heavy energy supply capacity required and the disruptive nature of the load that they place on the electrical network. This paper examines some of the potential benefits that can be seen by incorporating a Battery Electrical Storage System and directly connected Renewable Energy Systems into EV Rapid charger installations, as well as some of the ways that energy may be managed in such a system.
{"title":"Optimisation of locally connected renewables for high power EV charging station","authors":"B. Hunter, G. Lacey, Huda Dawood","doi":"10.1109/UPEC50034.2021.9548244","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548244","url":null,"abstract":"Constantly increasing uptake of Electric Vehicles (EVs) necessitates a rapidly growing and evolving network of charging stations, including rapid charging systems which attempt to make up for the issue of slow charging. Rapid charging systems, however, can be difficult to implement in larger scale due to the heavy energy supply capacity required and the disruptive nature of the load that they place on the electrical network. This paper examines some of the potential benefits that can be seen by incorporating a Battery Electrical Storage System and directly connected Renewable Energy Systems into EV Rapid charger installations, as well as some of the ways that energy may be managed in such a system.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131730096","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548273
I. Panapakidis, Vasileios Polychronidis, D. Bargiotas
Natural Gas (NG) demand forecasting is a research topic that starts to gather the attention of scholars, research institutions, utilities, retailers and other interested parties. Accurate predictions of future needs for NG can aid on the optimal management of NG resources. This manuscript examines the problem of day-ahead Natural Gas (NG) demand forecasting in hourly resolution. Various models of different type are trained and applied using data that correspond to the demand of a large region including urban, sub-urban and industrial loads. A series of scenarios are formed in order to investigate the influence of input selection on the day-ahead forecasting problem.
{"title":"Day-Ahead Natural Gas Demand Forecasting in Hourly Resolution","authors":"I. Panapakidis, Vasileios Polychronidis, D. Bargiotas","doi":"10.1109/UPEC50034.2021.9548273","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548273","url":null,"abstract":"Natural Gas (NG) demand forecasting is a research topic that starts to gather the attention of scholars, research institutions, utilities, retailers and other interested parties. Accurate predictions of future needs for NG can aid on the optimal management of NG resources. This manuscript examines the problem of day-ahead Natural Gas (NG) demand forecasting in hourly resolution. Various models of different type are trained and applied using data that correspond to the demand of a large region including urban, sub-urban and industrial loads. A series of scenarios are formed in order to investigate the influence of input selection on the day-ahead forecasting problem.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133290682","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548199
H. Cai, Xinya Song, Yuelin Zeng, T. Jiang, S. Schlegel, D. Westermann
The electrical energy system is transforming itself into a sustainable energy supply in response to the decline in fossil fuels. This conversion is driving the expansion of renewable energy facilities such as photovoltaic plants and wind power plants. Except for large hydropower plants and offshore wind farms, the integration of renewable energies takes place predominantly in the medium- and low-voltage distribution networks. This leads to a lack of observability and increasing grid complexity. Consequently, distribution network operators are constantly faced with a challenge in terms of observability. A comprehensive installation of measuring instruments in the medium- and low-voltage networks has proved economically unviable. An alternative approach to network state monitoring within the framework of power grid digital twin (DT) is therefore developed in this paper. The patterns of the electrical energy system are detected and modeled employing an artificial neural network (ANN) in connection with the associated harmonic spectra. Based on this DT model, the active powers of renewable energy facilities are estimated through the measured voltage data. In this regard, this work is first devoted to the modeling of an ANN-based DT estimator. The proposed power state estimation is then validated with the measured data from a field test. The accuracy of the estimation will be investigated according to the different influencing factors.
{"title":"A Practical Approach to Construct a Digital Twin of a Power Grid using Harmonic Spectra","authors":"H. Cai, Xinya Song, Yuelin Zeng, T. Jiang, S. Schlegel, D. Westermann","doi":"10.1109/UPEC50034.2021.9548199","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548199","url":null,"abstract":"The electrical energy system is transforming itself into a sustainable energy supply in response to the decline in fossil fuels. This conversion is driving the expansion of renewable energy facilities such as photovoltaic plants and wind power plants. Except for large hydropower plants and offshore wind farms, the integration of renewable energies takes place predominantly in the medium- and low-voltage distribution networks. This leads to a lack of observability and increasing grid complexity. Consequently, distribution network operators are constantly faced with a challenge in terms of observability. A comprehensive installation of measuring instruments in the medium- and low-voltage networks has proved economically unviable. An alternative approach to network state monitoring within the framework of power grid digital twin (DT) is therefore developed in this paper. The patterns of the electrical energy system are detected and modeled employing an artificial neural network (ANN) in connection with the associated harmonic spectra. Based on this DT model, the active powers of renewable energy facilities are estimated through the measured voltage data. In this regard, this work is first devoted to the modeling of an ANN-based DT estimator. The proposed power state estimation is then validated with the measured data from a field test. The accuracy of the estimation will be investigated according to the different influencing factors.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122349492","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 : 2021-08-31DOI: 10.1109/UPEC50034.2021.9548274
Bhavana Burramukku, O. Ceylan, M. Neshat
One of the most important factors in the amount of power generated by a wave farm is the Wave Energy Converters (WECs) arrangement along with the usual wave conditions. Therefore, forming an appropriate arrangement of WECs in an array is a significant parameter in maximizing power absorption. This paper focuses on developing a fully connected neural model in order to predict the total power output of a wave farm based on the placement of the converters, derived from the four real wave scenarios on the southern coast of Australia. The applied converter model is a fully submerged three-tether converter called CETO. Data collected from the test sites is used to design a neural model for predicting the wave farm’s power output produced. A precise analysis of the WEC placement is investigated to reveal the amount of power generated by the wave farms on the test site. We finally proposed a suitable configuration of a fully connected neural model to forecast the power output with high accuracy.
{"title":"Power Output Prediction of Wave Farms Using Fully Connected Networks","authors":"Bhavana Burramukku, O. Ceylan, M. Neshat","doi":"10.1109/UPEC50034.2021.9548274","DOIUrl":"https://doi.org/10.1109/UPEC50034.2021.9548274","url":null,"abstract":"One of the most important factors in the amount of power generated by a wave farm is the Wave Energy Converters (WECs) arrangement along with the usual wave conditions. Therefore, forming an appropriate arrangement of WECs in an array is a significant parameter in maximizing power absorption. This paper focuses on developing a fully connected neural model in order to predict the total power output of a wave farm based on the placement of the converters, derived from the four real wave scenarios on the southern coast of Australia. The applied converter model is a fully submerged three-tether converter called CETO. Data collected from the test sites is used to design a neural model for predicting the wave farm’s power output produced. A precise analysis of the WEC placement is investigated to reveal the amount of power generated by the wave farms on the test site. We finally proposed a suitable configuration of a fully connected neural model to forecast the power output with high accuracy.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116848412","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}
{"title":"List of Papers","authors":"P. Brandt, -. Chris, Klaus Pinho tian Lawonn, P. Andersson, P. Pinho, P. Andersson","doi":"10.1515/9781400849895-014","DOIUrl":"https://doi.org/10.1515/9781400849895-014","url":null,"abstract":"Notation for Publications ML1 – Machine Learning/Data Mining, GA – Graph Algorithms/Network Science, NLP – Natural Language Processing/Text Mining, MS – Multiscale Methods, QC – Quantum Computing, CSC – Combinatorial Scientific Computing, AGT – Agent-based Modeling, BIO – Applications in Biology/Medicine/Healthcare, ENG – Applications in Computational Engineering, VIS – Visualization, COMB – Other Combinatorics","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116980905","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：