Pub Date : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571753
Jérôme Buire, F. Colas, J. Dieulot, Léticia De Alvaro, X. Guillaud
The insertion of stochastic renewable energies in distribution grids generates important voltage fluctuations. However, the influence of the On Load Tap Changer and Distributed Generators (DGs) controllers, and specifically the existence of dead-bands in the control laws, has been seldom evaluated. Under the assumptions of Gaussian inputs and a linear model of the grid, it is shown that node voltages can be approximated either by Gaussian variables or sums of truncated Gaussian variables. A procedure is necessary to select the Probability Density Function (PDF) which fits best each node voltage. A signal based method and another algorithm relying on the grid topology are presented and compared when the modeling is applied to a real distribution grid. The model is accurate and can be used for confidence level or chance-constrained optimization of control parameters.
{"title":"Stochastic power flow of distribution networks including dispersed generation system","authors":"Jérôme Buire, F. Colas, J. Dieulot, Léticia De Alvaro, X. Guillaud","doi":"10.1109/ISGTEurope.2018.8571753","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571753","url":null,"abstract":"The insertion of stochastic renewable energies in distribution grids generates important voltage fluctuations. However, the influence of the On Load Tap Changer and Distributed Generators (DGs) controllers, and specifically the existence of dead-bands in the control laws, has been seldom evaluated. Under the assumptions of Gaussian inputs and a linear model of the grid, it is shown that node voltages can be approximated either by Gaussian variables or sums of truncated Gaussian variables. A procedure is necessary to select the Probability Density Function (PDF) which fits best each node voltage. A signal based method and another algorithm relying on the grid topology are presented and compared when the modeling is applied to a real distribution grid. The model is accurate and can be used for confidence level or chance-constrained optimization of control parameters.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122536587","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571524
Patrick S. Sauter, Philipp Karg, Mathias Kluwe, S. Hohmann
In this paper we present a new approach for load forecasting in distribution grids with high renewable energy penetration. The method is based on multiple neural networks and the application focuses on predictive energy management systems which use a model predictive control (MPC) approach. These control algorithms need predictions of demand profiles from 15 minutes up to several days. The short-term forecast values are more important than the long-term prediction values beyond six or 24 hours. Thus, the new method takes instantaneous measurements into account in order to provide a high accuracy for the first prediction values. In addition, weather forecast data is included as input variables of the neural networks for the purpose of mapping the influence of renewable energy generation on the load profiles. With this approach, the method improves the Root-Mean-Squared Error up to 80 % compared to a reference model based on a weekly persistence.
{"title":"Load Forecasting in Distribution Grids with High Renewable Energy Penetration for Predictive Energy Management Systems","authors":"Patrick S. Sauter, Philipp Karg, Mathias Kluwe, S. Hohmann","doi":"10.1109/ISGTEurope.2018.8571524","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571524","url":null,"abstract":"In this paper we present a new approach for load forecasting in distribution grids with high renewable energy penetration. The method is based on multiple neural networks and the application focuses on predictive energy management systems which use a model predictive control (MPC) approach. These control algorithms need predictions of demand profiles from 15 minutes up to several days. The short-term forecast values are more important than the long-term prediction values beyond six or 24 hours. Thus, the new method takes instantaneous measurements into account in order to provide a high accuracy for the first prediction values. In addition, weather forecast data is included as input variables of the neural networks for the purpose of mapping the influence of renewable energy generation on the load profiles. With this approach, the method improves the Root-Mean-Squared Error up to 80 % compared to a reference model based on a weekly persistence.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122751176","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571504
A. Secic, K. Jambrošić, I. Kuzle
Audio-based machinery fault diagnostics has a lot of particularities when compared to similar (non-invasive) diagnostic methods. These particularities are most evident in the unavoidable influence of the machine environment which is reflected through a mixture of the useful diagnostic material with surrounding sounds. On the other hand, there are several obvious advantages of this approach. For instance, a recording microphone can be installed at a certain distance from the tested object, ensuring the complete non-invasiveness of the measuring process. This paper analyses the influence of the surrounding environment in audio-based On-Load Tap Changer transformer diagnostics as well as the ability to apply statistical methods for the purpose of extracting useful diagnostic material that can be used for its condition assessment.
{"title":"Blind Source Separation as an Extraction Tool of the Useful Diagnostic Material in on Load Tap Changer Audio Based Diagnostics","authors":"A. Secic, K. Jambrošić, I. Kuzle","doi":"10.1109/ISGTEurope.2018.8571504","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571504","url":null,"abstract":"Audio-based machinery fault diagnostics has a lot of particularities when compared to similar (non-invasive) diagnostic methods. These particularities are most evident in the unavoidable influence of the machine environment which is reflected through a mixture of the useful diagnostic material with surrounding sounds. On the other hand, there are several obvious advantages of this approach. For instance, a recording microphone can be installed at a certain distance from the tested object, ensuring the complete non-invasiveness of the measuring process. This paper analyses the influence of the surrounding environment in audio-based On-Load Tap Changer transformer diagnostics as well as the ability to apply statistical methods for the purpose of extracting useful diagnostic material that can be used for its condition assessment.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124011054","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571673
K. M. Banjar-Nahor, L. Garbuio, V. Debusschere, N. Hadjsaid, T. Pham, N. Sinisuka
This study assesses the impacts of variable renewabIes and the use of flexibility on frequency, voltage, and angle stability in a typical isolated microgrid in Indonesia. The simulations in Power Factory have illustrated the flexibility options and the stability behavior evolution, considering a parametric study on the shares of inverter-based variable renewable energy resources. The 10% limit of variable renewabIes in Indonesian microgrids is also discussed and proven to be rather pessimistic, as this research reaches the instantaneous penetration rate varying from 0% to 31.3% in the considered scenarios.
{"title":"Study on Renewable Penetration Limits in a Typical Indonesian Islanded Microgrid Considering the Impact of Variable Renewables Integration and the Empowering Flexibility on Grid Stability","authors":"K. M. Banjar-Nahor, L. Garbuio, V. Debusschere, N. Hadjsaid, T. Pham, N. Sinisuka","doi":"10.1109/ISGTEurope.2018.8571673","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571673","url":null,"abstract":"This study assesses the impacts of variable renewabIes and the use of flexibility on frequency, voltage, and angle stability in a typical isolated microgrid in Indonesia. The simulations in Power Factory have illustrated the flexibility options and the stability behavior evolution, considering a parametric study on the shares of inverter-based variable renewable energy resources. The 10% limit of variable renewabIes in Indonesian microgrids is also discussed and proven to be rather pessimistic, as this research reaches the instantaneous penetration rate varying from 0% to 31.3% in the considered scenarios.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126269491","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571748
Alireza Esmaeili Karkevandi, Matin Jamaliyan Daryani, Ö. Usta
Intelligent microgrid with different energy sources is considered as the next generation of power grid. For reliable and effective operation of this system, advanced communication and intelligent information processing techniques are required. In such a system, several electronic interfaced Distributed Generations (DGs) with local and global control loops are utilized. At DGs control systems, the primary control level is responsible for voltage and frequency regulation and maintaining microgrid stability. However, primary control may cause voltage and frequency deviation and it cannot guarantee zero voltage or frequency regulation errors. In this paper, to compensate these deviations, improve accuracy, global controllability and also to ensure reactive power sharing in the microgrid, a novel intelligent and distributed secondary control scheme is proposed, which is based on PI controller. To adaptively and optimally adjust PI controller parameters the Adaptive Neuro-Fuzzy Interface System (ANFIS) technique is used, which adjust PI controller coefficients according to microgrid operation conditions. The proposed ANFIS controller shows proper performance and acceptable response to different study cases.
{"title":"ANFIS-Based Intelligent PI Controller for Secondary Frequency and Voltage Control of Microgrid","authors":"Alireza Esmaeili Karkevandi, Matin Jamaliyan Daryani, Ö. Usta","doi":"10.1109/ISGTEurope.2018.8571748","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571748","url":null,"abstract":"Intelligent microgrid with different energy sources is considered as the next generation of power grid. For reliable and effective operation of this system, advanced communication and intelligent information processing techniques are required. In such a system, several electronic interfaced Distributed Generations (DGs) with local and global control loops are utilized. At DGs control systems, the primary control level is responsible for voltage and frequency regulation and maintaining microgrid stability. However, primary control may cause voltage and frequency deviation and it cannot guarantee zero voltage or frequency regulation errors. In this paper, to compensate these deviations, improve accuracy, global controllability and also to ensure reactive power sharing in the microgrid, a novel intelligent and distributed secondary control scheme is proposed, which is based on PI controller. To adaptively and optimally adjust PI controller parameters the Adaptive Neuro-Fuzzy Interface System (ANFIS) technique is used, which adjust PI controller coefficients according to microgrid operation conditions. The proposed ANFIS controller shows proper performance and acceptable response to different study cases.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129650362","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571833
S. Naumann, Stefan Klaiber, André Kummerow, P. Bretschneider
Within the venture “REGEES” (REGenerative rEnewable Electricity System) a new approach for a Coordinated Market Grid Operation Management (CMGOM) was developed. This approach is investigated in a simulation considering uncertainties. Therefore, the energy time series generator as a method to generate time series for demand and feed-in is described and used to generate simulation input in the form of forecast-scenarios for load and feed-in. Uncertainties in the form of forecast errors and stochastic time series properties are taken into account. The optimization problem, which represents the mathematical description for the acquisition and balancing process of the Balance Responsible Party (BRP), is introduced. Finally, the energy system simulation is described for a test case in order to evaluate the CMGOM approach with consideration of uncertainty. For this purpose, deterministic optimization and two versions of optimization with uncertainties are compared.
{"title":"Simulation of Coordinated Market Grid Operations considering Uncertainties","authors":"S. Naumann, Stefan Klaiber, André Kummerow, P. Bretschneider","doi":"10.1109/ISGTEurope.2018.8571833","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571833","url":null,"abstract":"Within the venture “REGEES” (REGenerative rEnewable Electricity System) a new approach for a Coordinated Market Grid Operation Management (CMGOM) was developed. This approach is investigated in a simulation considering uncertainties. Therefore, the energy time series generator as a method to generate time series for demand and feed-in is described and used to generate simulation input in the form of forecast-scenarios for load and feed-in. Uncertainties in the form of forecast errors and stochastic time series properties are taken into account. The optimization problem, which represents the mathematical description for the acquisition and balancing process of the Balance Responsible Party (BRP), is introduced. Finally, the energy system simulation is described for a test case in order to evaluate the CMGOM approach with consideration of uncertainty. For this purpose, deterministic optimization and two versions of optimization with uncertainties are compared.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129409371","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571813
S. Janković, B. Ivanovic
This paper describes a permissive load frequency control (LFC) real life model for long-term time domain simulations. The model represents a supplementary control system to governor control systems based on area control error (ACE) calculation. Each forth second, ACE will be checked. If ACE is outside of its dead-band, one signal will be generated and broadcasted to all power plants involved in secondary control. Considering the received signal (positive or negative) and power plant participation factors, each power plant will react in order to reduce ACE. This LFC type is around 20 years in service in the Serbian power system with minimum maintenance. The advantage of this LFC is that it is simple, reliable, it can follow strict ENTSO- E rules, and it could be implemented to all generation types including renewable sources. The paper does not bring a new LFC methodology. However, it provides a contribution to modelling existing LFCs.
{"title":"Real Life Permissive LFC Model Description","authors":"S. Janković, B. Ivanovic","doi":"10.1109/ISGTEurope.2018.8571813","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571813","url":null,"abstract":"This paper describes a permissive load frequency control (LFC) real life model for long-term time domain simulations. The model represents a supplementary control system to governor control systems based on area control error (ACE) calculation. Each forth second, ACE will be checked. If ACE is outside of its dead-band, one signal will be generated and broadcasted to all power plants involved in secondary control. Considering the received signal (positive or negative) and power plant participation factors, each power plant will react in order to reduce ACE. This LFC type is around 20 years in service in the Serbian power system with minimum maintenance. The advantage of this LFC is that it is simple, reliable, it can follow strict ENTSO- E rules, and it could be implemented to all generation types including renewable sources. The paper does not bring a new LFC methodology. However, it provides a contribution to modelling existing LFCs.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131120199","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571582
N. Trinh, M. Zeller, I. Erlich
This paper presents a study on coordination of functional controllers equipped on a multi-terminal MMC-VSC-HVDC control system for enhancing grid dynamic performance. The study was carried on in a typical transmission power system embedded with a three-terminal MMC-VSC-HVDC system. The HVDC system control was equipped with Power Oscillation Damping (POD) controller, Primary Frequency Support (PFS) controller and Fast Voltage Support (FVS) controller which were designed for improving small signal stability, supporting load-flow in primary frequency control and enhancing transient stability of the AC power system, respectively. The study results showed that, there were potential incorporated interactions between the POD and FVS controllers equipped on the reactive power modulation channel. Whereas, the POD and PFS controllers equipped on the active power modulation channel were found to be well-coordinated. In this study, a counter measure was also proposed to mitigate the identified incorporated interactions between the FVS and POD controllers.
{"title":"Coordination of Functional Controllers in a Multiterminal MMC-VSC-HVDC System Control","authors":"N. Trinh, M. Zeller, I. Erlich","doi":"10.1109/ISGTEurope.2018.8571582","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571582","url":null,"abstract":"This paper presents a study on coordination of functional controllers equipped on a multi-terminal MMC-VSC-HVDC control system for enhancing grid dynamic performance. The study was carried on in a typical transmission power system embedded with a three-terminal MMC-VSC-HVDC system. The HVDC system control was equipped with Power Oscillation Damping (POD) controller, Primary Frequency Support (PFS) controller and Fast Voltage Support (FVS) controller which were designed for improving small signal stability, supporting load-flow in primary frequency control and enhancing transient stability of the AC power system, respectively. The study results showed that, there were potential incorporated interactions between the POD and FVS controllers equipped on the reactive power modulation channel. Whereas, the POD and PFS controllers equipped on the active power modulation channel were found to be well-coordinated. In this study, a counter measure was also proposed to mitigate the identified incorporated interactions between the FVS and POD controllers.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122597873","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 : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571660
I. Stoyanova, Chenxi Wu, A. Monti
In this work, we propose the application of methods from Statistical Process Control (SPC) to evaluate and classify online load variations as neglectable common or as critical variations that require immediate actions. The SPC strategy is adapted to the specific requirements of load profile variation analysis and could offer a low-requirement option to cope with data unavailability in distribution grids. We investigate the feasibility of two control charts, Shewhart and exponentially weighted moving average, to provide insight into the development of the aggregated load profile in areas with limited monitoring and without communication with individual consumers. The performance of the control charts is compared in terms of deviation detection. To investigate the effect of data availability, load variations for 74 households are categorized according to the season, day and time of the day. Finally, the results of the adapted SPC method applied with specific and with general deviation information is compared. Tests showed that the adapted SPC method is feasible to support assumptions about the load curve trend if its limitations are taken into account.
{"title":"Adapted Methods from Statistical Process Control for Evaluation of Load Variations in Distribution Grids","authors":"I. Stoyanova, Chenxi Wu, A. Monti","doi":"10.1109/ISGTEurope.2018.8571660","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571660","url":null,"abstract":"In this work, we propose the application of methods from Statistical Process Control (SPC) to evaluate and classify online load variations as neglectable common or as critical variations that require immediate actions. The SPC strategy is adapted to the specific requirements of load profile variation analysis and could offer a low-requirement option to cope with data unavailability in distribution grids. We investigate the feasibility of two control charts, Shewhart and exponentially weighted moving average, to provide insight into the development of the aggregated load profile in areas with limited monitoring and without communication with individual consumers. The performance of the control charts is compared in terms of deviation detection. To investigate the effect of data availability, load variations for 74 households are categorized according to the season, day and time of the day. Finally, the results of the adapted SPC method applied with specific and with general deviation information is compared. Tests showed that the adapted SPC method is feasible to support assumptions about the load curve trend if its limitations are taken into account.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126250075","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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