Pub Date : 2016-10-01DOI: 10.1109/PMAPS.2016.7764084
Can. Chen, Pengfei Cao, Chen Shen, Linlin Wu, C. Singh
An important aspect of research on integrating wind farms is the analysis of short circuit current contribution to the power grid. In this paper, the fault related features of doubly fed induction generators (DFIGs) are modeled using low voltage ride through (LVRT) test data sets. The dynamic behavior of DFIGs after fault occurrence is represented by a typical curve that is obtained using a curve clustering technique - the backward scenario reduction method. Then, two fault features (the maximum value of the short circuit current termed as peak current and the time to reach it), which are important for protection relay settings, are collected and analyzed using the probability density functions (PDFs). Two cases are considered in the analysis and some discussions are presented in the end.
{"title":"Probabilistic analysis for low voltage ride through test data of doubly fed induction generators in China","authors":"Can. Chen, Pengfei Cao, Chen Shen, Linlin Wu, C. Singh","doi":"10.1109/PMAPS.2016.7764084","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764084","url":null,"abstract":"An important aspect of research on integrating wind farms is the analysis of short circuit current contribution to the power grid. In this paper, the fault related features of doubly fed induction generators (DFIGs) are modeled using low voltage ride through (LVRT) test data sets. The dynamic behavior of DFIGs after fault occurrence is represented by a typical curve that is obtained using a curve clustering technique - the backward scenario reduction method. Then, two fault features (the maximum value of the short circuit current termed as peak current and the time to reach it), which are important for protection relay settings, are collected and analyzed using the probability density functions (PDFs). Two cases are considered in the analysis and some discussions are presented in the end.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130576318","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764099
Shucheng Liu, Wenxiong Huang, Yi Zhang
A stochastic production simulation model was developed to evaluate the California Independent System Operator (CAISO) system capacity and flexibility sufficiency in order to integrate high volume of renewable generation to meet the California state renewables portfolio standard (RPS) goals. The model, which simulates the operation of the CAISO system, uses four stochastic variables, generation resource forced outages, load, solar and wind generation, to capture a wide range of possible system conditions. A novel pattern preserving methodology was developed to create samples of stochastic load, solar and wind generation variables. The model was used to study the system capacity and flexibility needs to integrate 33% renewable generation in California. The results of this study were filed to the California Public Utilities Commission (CPUC) in the Long Term Procurement Plan (LTPP) proceeding.
{"title":"A stochastic production simulation model for renewable integration and system flexibility studies","authors":"Shucheng Liu, Wenxiong Huang, Yi Zhang","doi":"10.1109/PMAPS.2016.7764099","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764099","url":null,"abstract":"A stochastic production simulation model was developed to evaluate the California Independent System Operator (CAISO) system capacity and flexibility sufficiency in order to integrate high volume of renewable generation to meet the California state renewables portfolio standard (RPS) goals. The model, which simulates the operation of the CAISO system, uses four stochastic variables, generation resource forced outages, load, solar and wind generation, to capture a wide range of possible system conditions. A novel pattern preserving methodology was developed to create samples of stochastic load, solar and wind generation variables. The model was used to study the system capacity and flexibility needs to integrate 33% renewable generation in California. The results of this study were filed to the California Public Utilities Commission (CPUC) in the Long Term Procurement Plan (LTPP) proceeding.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116584688","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 development of high voltage technology provides technical conditions for the transmission of offshore new energy, but it is necessary to consider the operation status of power grid when we decide the way of grid connection. This paper focuses on the stability of the system and evaluates three access form - the high voltage alternating current (HVAC), traditional direct current (DC) and flexible DC transmission. Evaluation index and evaluation system are established. The evaluation index selects indicators from three aspects of static security, transient stability and short circuit capacity. Evaluation system is based on math method. It gets the indicators' weight through the game theory and uses intuitionistic fuzzy theory combining strict fitting degree to get the optimization choice. The theoretical analysis is based on the actual island model, evaluated through BPA simulations. Simulation results are presented to validate the expected performance of the proposed evaluation method.
{"title":"Optimal selection of high voltage transmission connected to island systems","authors":"Xiaoxi Li, Xin Zhang, Yunting Song, Wei Tang, Yinshun Wang, Jingjing Wang, Xiaofei Hu, Cheng Yang","doi":"10.1109/PMAPS.2016.7764127","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764127","url":null,"abstract":"The development of high voltage technology provides technical conditions for the transmission of offshore new energy, but it is necessary to consider the operation status of power grid when we decide the way of grid connection. This paper focuses on the stability of the system and evaluates three access form - the high voltage alternating current (HVAC), traditional direct current (DC) and flexible DC transmission. Evaluation index and evaluation system are established. The evaluation index selects indicators from three aspects of static security, transient stability and short circuit capacity. Evaluation system is based on math method. It gets the indicators' weight through the game theory and uses intuitionistic fuzzy theory combining strict fitting degree to get the optimization choice. The theoretical analysis is based on the actual island model, evaluated through BPA simulations. Simulation results are presented to validate the expected performance of the proposed evaluation method.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123798964","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764169
Sheng Wanxing, Liu Keyan, Niu Huanna, W. Yuzhu, Zhao Jingxiang
With the continuous development of smart grid and energy Internet, modern power system is gradually evolved into the one with funnel large amounts of data and calculation of large information systems, which shows the applicability and feasibility of the analysis technology of data mining. This paper puts forward a big data modeling method for the reactive power optimization based on the theory of the large dimensional random matrix. On the basis of it, large dimensional random matrix is disposed, applied with higher dimensional random matrix theory related to the characteristics of abnormal data detection, for judging the existence of abnormal data. If existed, this matrix is used in accordance with Pauta criterion identification to find the abnormal data. At the end of the article, it is verified by analysis examples of its effectiveness and applicability.
{"title":"The anomalous data identification study of reactive power optimization system based on big data","authors":"Sheng Wanxing, Liu Keyan, Niu Huanna, W. Yuzhu, Zhao Jingxiang","doi":"10.1109/PMAPS.2016.7764169","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764169","url":null,"abstract":"With the continuous development of smart grid and energy Internet, modern power system is gradually evolved into the one with funnel large amounts of data and calculation of large information systems, which shows the applicability and feasibility of the analysis technology of data mining. This paper puts forward a big data modeling method for the reactive power optimization based on the theory of the large dimensional random matrix. On the basis of it, large dimensional random matrix is disposed, applied with higher dimensional random matrix theory related to the characteristics of abnormal data detection, for judging the existence of abnormal data. If existed, this matrix is used in accordance with Pauta criterion identification to find the abnormal data. At the end of the article, it is verified by analysis examples of its effectiveness and applicability.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"202 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114014348","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764141
Cheng Tao, Chen Lei, Xu Fei, Dai Yuanhang
In order to achieve the grid line online fault warning, we used operational reliability theory to generate power line fault data, and then use the decision tree method to establish the relationships between pre-fault line data and the fault, and generate the corresponding fault warning rules, simulation results show that the decision tree method can effectively achieve line fault warning, which provides useful information for the operators to guarantee the security of the power system.
{"title":"Power line online fault warning method based on operational reliability and decision tree","authors":"Cheng Tao, Chen Lei, Xu Fei, Dai Yuanhang","doi":"10.1109/PMAPS.2016.7764141","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764141","url":null,"abstract":"In order to achieve the grid line online fault warning, we used operational reliability theory to generate power line fault data, and then use the decision tree method to establish the relationships between pre-fault line data and the fault, and generate the corresponding fault warning rules, simulation results show that the decision tree method can effectively achieve line fault warning, which provides useful information for the operators to guarantee the security of the power system.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122442381","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}
A user side integrated energy system (USIES) can supply energy in accordance with user demand, in order to make full use of terminal energy conditions, improve energy efficiency, and promote consumption of local renewable energy. A bi-level programming model of USIES multi-objective coordinated planning is developed based on the chance constrained programming. Multi-state models of wind turbine (WT), photovoltaic (PV) generation and load are established respectively according to probability density functions. Then a multi-state model of the IES can be proposed. Considering economic, energy influences, environmental protection and other factors, a configuration model of USIES based on bi-level programming is established, including WT, PV, micro gas turbine and gas boiler. Annual costs is minimized in the upper level objective function in order to accomplish configuration of distributed energy sources. The optimal scheduling of micro turbine is considered in the lower level, in which objective functions include the cost of USIES losses. The elitist strategy genetic algorithm and particle swarm optimization are applied for solving the planning model. A case of USIES planning, which used is in a residential and commercial areas in the North China, verifies the effectiveness of the proposed model and method. The simulation results show that the multi-state model can simplify the difficulty of model calculation. The USIES planning based on the chance constrained programming can adequately consider the uncertainty of USIES. Under a certain confidence level, the optimal investment with the corresponding probability of the confidence level is obtained.
{"title":"Optimal configuration of user side integrated energy system based on chance constrained programming","authors":"Chenxia Jia, Muke Bai, Chao Zhang, Jing Zhou, Gongbo Liu, Sheng Xu, Wei Tang, Cong Wu, Chenjun Sun","doi":"10.1109/PMAPS.2016.7764115","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764115","url":null,"abstract":"A user side integrated energy system (USIES) can supply energy in accordance with user demand, in order to make full use of terminal energy conditions, improve energy efficiency, and promote consumption of local renewable energy. A bi-level programming model of USIES multi-objective coordinated planning is developed based on the chance constrained programming. Multi-state models of wind turbine (WT), photovoltaic (PV) generation and load are established respectively according to probability density functions. Then a multi-state model of the IES can be proposed. Considering economic, energy influences, environmental protection and other factors, a configuration model of USIES based on bi-level programming is established, including WT, PV, micro gas turbine and gas boiler. Annual costs is minimized in the upper level objective function in order to accomplish configuration of distributed energy sources. The optimal scheduling of micro turbine is considered in the lower level, in which objective functions include the cost of USIES losses. The elitist strategy genetic algorithm and particle swarm optimization are applied for solving the planning model. A case of USIES planning, which used is in a residential and commercial areas in the North China, verifies the effectiveness of the proposed model and method. The simulation results show that the multi-state model can simplify the difficulty of model calculation. The USIES planning based on the chance constrained programming can adequately consider the uncertainty of USIES. Under a certain confidence level, the optimal investment with the corresponding probability of the confidence level is obtained.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131618297","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764154
Ye Xiaohui, Zhong Wuzhi, Song Xinli, Cheng Lin
Risk assessment theory is paid more and more attention to consider the random characteristics of power system, but traditional method could not consider the operating factors as frequency response of generators and loads, various emergency control measures. In this paper, a dynamic contingency analysis method base on dynamic load flow is proposed considering the above factors. The dynamic contingency analysis is a less time-consuming approach, but could simulate as well the detailed load shedding relay model, and the time-varying reliability model. So the proposed dynamic contingency analysis gives a good tool for cascading failure simulation.
{"title":"Power system risk assessment method based on dynamic power flow","authors":"Ye Xiaohui, Zhong Wuzhi, Song Xinli, Cheng Lin","doi":"10.1109/PMAPS.2016.7764154","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764154","url":null,"abstract":"Risk assessment theory is paid more and more attention to consider the random characteristics of power system, but traditional method could not consider the operating factors as frequency response of generators and loads, various emergency control measures. In this paper, a dynamic contingency analysis method base on dynamic load flow is proposed considering the above factors. The dynamic contingency analysis is a less time-consuming approach, but could simulate as well the detailed load shedding relay model, and the time-varying reliability model. So the proposed dynamic contingency analysis gives a good tool for cascading failure simulation.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134447742","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764194
M. Benidris, J. Mitra, C. Singh
This paper addresses the effects of transient instability on power system reliability. Composite system reliability evaluation has been performed based on steady-state estimation of load curtailments. In composite reliability evaluation, after each contingency, faulted components are assumed to be isolated from the rest of the system immediately and the system is assumed to return to a stable state with proper generation rescheduling for minimum load curtailments. In this context, minimum load curtailments are usually performed by solving linear/non-linear programming optimization problems. Although the optimization problem with minimum load curtailment may find a steady-state feasible solution, a stable transition to a post-fault stable equilibrium point is not guaranteed. In this paper, three probabilistic transient stability indices are proposed to assess system robustness against transient contingencies and update the reliability indices. Transient stability direct methods are used in assessing system stability and determining the probabilistic stability indices. This method is applied on the reduced WECC (Western Electricity Coordinating Council) system and the results showed that the effect of transient instability should not be ignored.
{"title":"Impacts of transient instability on power system reliability","authors":"M. Benidris, J. Mitra, C. Singh","doi":"10.1109/PMAPS.2016.7764194","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764194","url":null,"abstract":"This paper addresses the effects of transient instability on power system reliability. Composite system reliability evaluation has been performed based on steady-state estimation of load curtailments. In composite reliability evaluation, after each contingency, faulted components are assumed to be isolated from the rest of the system immediately and the system is assumed to return to a stable state with proper generation rescheduling for minimum load curtailments. In this context, minimum load curtailments are usually performed by solving linear/non-linear programming optimization problems. Although the optimization problem with minimum load curtailment may find a steady-state feasible solution, a stable transition to a post-fault stable equilibrium point is not guaranteed. In this paper, three probabilistic transient stability indices are proposed to assess system robustness against transient contingencies and update the reliability indices. Transient stability direct methods are used in assessing system stability and determining the probabilistic stability indices. This method is applied on the reduced WECC (Western Electricity Coordinating Council) system and the results showed that the effect of transient instability should not be ignored.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133058735","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764175
F. Ni, Phuong H. Nguyen, J.F.G. Cobben, Junjie Tang
In this paper, the authors apply a surrogate model-based method for probabilistic power flow (PPF) in the power system subject to truncated random variables. Due to a growing number of uncertainty sources are being brought into the modern power system, the traditional deterministic power flow analysis lacks its ability to recognize the realistic states of power systems, and thus turns to PPF for help. However, the PPF analysis is still facing several challenges: the computational effort required by the traditional simulation method is prohibitively expensive; and the modeling of uncertainty sources needs the improvement on both distribution type selection and parameter evaluation. The novelty of this work lies in taking advantage of both general polynomial chaos (gPC) expansion and ordinary least squares (OLS) to deal with PPF in presence of the truncated random variables. The performance of the proposed method is verified on the IEEE 30-Bus test system, considering uncertain factors brought by active power at load buses. In different test scenarios, the proposed method shows sound performances at the cost of less computational effort, compared to the traditional approach.
{"title":"Application of non-intrusive polynomial chaos expansion in probabilistic power flow with truncated random variables","authors":"F. Ni, Phuong H. Nguyen, J.F.G. Cobben, Junjie Tang","doi":"10.1109/PMAPS.2016.7764175","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764175","url":null,"abstract":"In this paper, the authors apply a surrogate model-based method for probabilistic power flow (PPF) in the power system subject to truncated random variables. Due to a growing number of uncertainty sources are being brought into the modern power system, the traditional deterministic power flow analysis lacks its ability to recognize the realistic states of power systems, and thus turns to PPF for help. However, the PPF analysis is still facing several challenges: the computational effort required by the traditional simulation method is prohibitively expensive; and the modeling of uncertainty sources needs the improvement on both distribution type selection and parameter evaluation. The novelty of this work lies in taking advantage of both general polynomial chaos (gPC) expansion and ordinary least squares (OLS) to deal with PPF in presence of the truncated random variables. The performance of the proposed method is verified on the IEEE 30-Bus test system, considering uncertain factors brought by active power at load buses. In different test scenarios, the proposed method shows sound performances at the cost of less computational effort, compared to the traditional approach.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133064099","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 : 2016-10-01DOI: 10.1109/PMAPS.2016.7764097
Chi Zhang, Wenyuan Li, Juan Yu, Ruilin Xu
PM2.5 concentration can have significant impacts on solar irradiation and thus on photovoltaic (PV) power output. This paper presents a method to model impacts of PM2.5 concentration on PV power. A non-parametric kernel density estimation is used to fit the probability distribution of PM2.5 concentration. An incremental relation between the increase of PM2.5 concentration and the decrease of solar irradiation is established for each PM2.5 level based on the PM2.5 air quality index. The simulation results using the PM2.5 and solar irradiation data in Beijing verified the effectiveness of the proposed method.
{"title":"Modeling impacts of PM 2.5 concentration on PV power outputs","authors":"Chi Zhang, Wenyuan Li, Juan Yu, Ruilin Xu","doi":"10.1109/PMAPS.2016.7764097","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764097","url":null,"abstract":"PM2.5 concentration can have significant impacts on solar irradiation and thus on photovoltaic (PV) power output. This paper presents a method to model impacts of PM2.5 concentration on PV power. A non-parametric kernel density estimation is used to fit the probability distribution of PM2.5 concentration. An incremental relation between the increase of PM2.5 concentration and the decrease of solar irradiation is established for each PM2.5 level based on the PM2.5 air quality index. The simulation results using the PM2.5 and solar irradiation data in Beijing verified the effectiveness of the proposed method.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130370484","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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