Pub Date : 2016-10-01DOI: 10.1109/PMAPS.2016.7764139
Jian Wang, Zongxiang Lu, Ying Qiao, Guiping Zhu
Wind curtailment is a severe problem in wind power development in China and demand response is considered to be one of the resources that have great potential to promote the utilization of wind power. This paper proposes a new day-ahead generation schedule model with demand response scheme in the background of joint operation of wind farms and high energy consuming loads. Considering the stochastic character of wind power, risk evaluation and corresponding optimization method is applied. The objective for this model is to minimize the secure and economic risks of wind power and the cost of thermal power units comprehensively. Detailed model and evaluation method are shown in this paper. The simulation results illustrate that this model presents better performance in reducing the wind curtailment ratio and operating cost compared with the demand response model without consideration of risks of wind power.
{"title":"Day-ahead generation schedule model with demand response considering the secure and economic risks of wind power","authors":"Jian Wang, Zongxiang Lu, Ying Qiao, Guiping Zhu","doi":"10.1109/PMAPS.2016.7764139","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764139","url":null,"abstract":"Wind curtailment is a severe problem in wind power development in China and demand response is considered to be one of the resources that have great potential to promote the utilization of wind power. This paper proposes a new day-ahead generation schedule model with demand response scheme in the background of joint operation of wind farms and high energy consuming loads. Considering the stochastic character of wind power, risk evaluation and corresponding optimization method is applied. The objective for this model is to minimize the secure and economic risks of wind power and the cost of thermal power units comprehensively. Detailed model and evaluation method are shown in this paper. The simulation results illustrate that this model presents better performance in reducing the wind curtailment ratio and operating cost compared with the demand response model without consideration of risks of wind power.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"1 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":"130193361","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.2016.7764079
Peng Zhang, Chunyan Li, Qian Zhang
Wind power forecast error has been considered to be the factor that increases the difficulty of power system dispatch, decreases the economy of system operation, and affects the wind power accommodation. A multiple time scales dispatch model of wind power integrated system is built considering the wind power forecast error and demand response. The price-based demand response (PDR) is used in the initial dispatch because of the large day-ahead forecast error. In the day, the price-based demand response is dispatched again to take advantage of its low cost. According to the strong timeliness of the incentive-based demand response (IDR), it is used in real-time dispatch to decrease the influence of wind power forecast error on the system dispatch and wind power accommodation. Study case shows that the multiple time scales optimal dispatch can increase wind power accommodations, save system operating costs, ensure the autonomy of consumers and reduce the impact of demand response.
{"title":"Wind power accommodation considering the prediction error of wind power","authors":"Peng Zhang, Chunyan Li, Qian Zhang","doi":"10.1109/PMAPS.2016.7764079","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764079","url":null,"abstract":"Wind power forecast error has been considered to be the factor that increases the difficulty of power system dispatch, decreases the economy of system operation, and affects the wind power accommodation. A multiple time scales dispatch model of wind power integrated system is built considering the wind power forecast error and demand response. The price-based demand response (PDR) is used in the initial dispatch because of the large day-ahead forecast error. In the day, the price-based demand response is dispatched again to take advantage of its low cost. According to the strong timeliness of the incentive-based demand response (IDR), it is used in real-time dispatch to decrease the influence of wind power forecast error on the system dispatch and wind power accommodation. Study case shows that the multiple time scales optimal dispatch can increase wind power accommodations, save system operating costs, ensure the autonomy of consumers and reduce the impact of demand response.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"5 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":"121332162","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.2016.7764198
Fan Chen, Haitao Liu, Jun Li, Zheng Huang
The solution of optimal load curtailment for the selected system contingency states is the most important step for the reliability analysis of composite power system. The linear reactive remedial model considering the bus voltage and reactive power constrains was formulated first based on the decoupled AC load flow model. Aiming at dealing with the discrete control variables in the reactive power optimal problem, a hybrid optimal method combined with interior point method and Genetic Algorithm (GA) method is proposed. Some reliability indices are defined to represent the reactive power adequacy similar to the indices used for representing active power adequacy in this paper. Case studies have been carried out on the modified IEEE RTS to validate the proposed optimal algorithm and investigate the effect of discreteness of shunt compensation capacity and bus voltage on system reliability indices.
{"title":"Reactive power adequacy assessment of composite power system based on interior point method and genetic algorithm","authors":"Fan Chen, Haitao Liu, Jun Li, Zheng Huang","doi":"10.1109/PMAPS.2016.7764198","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764198","url":null,"abstract":"The solution of optimal load curtailment for the selected system contingency states is the most important step for the reliability analysis of composite power system. The linear reactive remedial model considering the bus voltage and reactive power constrains was formulated first based on the decoupled AC load flow model. Aiming at dealing with the discrete control variables in the reactive power optimal problem, a hybrid optimal method combined with interior point method and Genetic Algorithm (GA) method is proposed. Some reliability indices are defined to represent the reactive power adequacy similar to the indices used for representing active power adequacy in this paper. Case studies have been carried out on the modified IEEE RTS to validate the proposed optimal algorithm and investigate the effect of discreteness of shunt compensation capacity and bus voltage on system reliability indices.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"1 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":"121175386","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.2016.7764215
M. D. da Rosa, G. Bolacell, I. Costa, D. Calado, D. Issicaba
Distribution Power System performance assessment is usually based on continuity indicators and power quality measurements. Generally, these evaluations are performed using distinct mechanisms, where continuity is assessed by past network performance observations and/or predicted simulation, whereas power quality is evaluated using electronic measurements. In fact, the concepts of reliability and power quality are dissociated, mainly when distribution power system performance is assessed. However, the current diversity of loads and sources, with more sensitivity to voltage variations, requires a wider ranging of power system tools, which consider aspects of both continuity and power quality effects. Aiming for a distribution systems performance approach that considers both reliability and power quality issues into a unique evaluation framework, aspects related to the systems voltage as well as distorting phenomena affecting the voltage waveform need to be modeled. This paper proposes the impact assessment of network geometric model on power quality indices using simulation techniques. The main idea is to include a short-circuit model into a sequential Monte Carlo algorithm in order to assess power quality indices through estimates. The proposed methodology is applied to the IEEE test feeder with 34 nodes.
{"title":"Impact evaluation of the network geometric model on power quality indices using probabilistic techniques","authors":"M. D. da Rosa, G. Bolacell, I. Costa, D. Calado, D. Issicaba","doi":"10.1109/PMAPS.2016.7764215","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764215","url":null,"abstract":"Distribution Power System performance assessment is usually based on continuity indicators and power quality measurements. Generally, these evaluations are performed using distinct mechanisms, where continuity is assessed by past network performance observations and/or predicted simulation, whereas power quality is evaluated using electronic measurements. In fact, the concepts of reliability and power quality are dissociated, mainly when distribution power system performance is assessed. However, the current diversity of loads and sources, with more sensitivity to voltage variations, requires a wider ranging of power system tools, which consider aspects of both continuity and power quality effects. Aiming for a distribution systems performance approach that considers both reliability and power quality issues into a unique evaluation framework, aspects related to the systems voltage as well as distorting phenomena affecting the voltage waveform need to be modeled. This paper proposes the impact assessment of network geometric model on power quality indices using simulation techniques. The main idea is to include a short-circuit model into a sequential Monte Carlo algorithm in order to assess power quality indices through estimates. The proposed methodology is applied to the IEEE test feeder with 34 nodes.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"42 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":"124415829","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.2016.7764111
F. Chen, Yi Dai, Zhouyang Ren, Wenyuan Li
This paper presents a spare strategy of circuit breakers (CBs) considering aging failures based on condition monitoring data. The monitoring data are used to estimate the functional ages of CBs and the aging failure rates of CBs are calculated using the functional ages. The loss-of-load damage costs caused by both repairable and aging failures of CBs are evaluated together with the investment of spares. The number and timing of spare CBs can be determined by comparing the damage cost reductions due to spares with the additional investment costs. The proposed strategy is applied to a substation located in the south China to demonstrate the effectiveness of the proposed method.
{"title":"A spare strategy of circuit breakers considering aging failures","authors":"F. Chen, Yi Dai, Zhouyang Ren, Wenyuan Li","doi":"10.1109/PMAPS.2016.7764111","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764111","url":null,"abstract":"This paper presents a spare strategy of circuit breakers (CBs) considering aging failures based on condition monitoring data. The monitoring data are used to estimate the functional ages of CBs and the aging failure rates of CBs are calculated using the functional ages. The loss-of-load damage costs caused by both repairable and aging failures of CBs are evaluated together with the investment of spares. The number and timing of spare CBs can be determined by comparing the damage cost reductions due to spares with the additional investment costs. The proposed strategy is applied to a substation located in the south China to demonstrate the effectiveness of the proposed method.","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":"130496696","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.2016.7764212
Ming Wang, Yingmeng Xiang, Lingfeng Wang, Jie Jiang, Ruosong Xiao, K. Xie
The increasing load demand is pushing power system to operate near its limit, making it more vulnerable to various disturbances and attacks, especially those that might initiate cascading failures. In this study, the joint line-generation attack is introduced which assumes that the lines and generators can be tripped by malicious attacks simultaneously, and it is a natural extension of the previous node-only or line-only attacks. The joint line-generation attack strategy is explored based on a search space reduction algorithm. The simulation is conducted based on several representative test systems. The performance of the proposed attack strategy is compared with other attack strategies and the computational burden is analyzed. It is demonstrated that the proposed attack strategy is effective and computationally efficient. This work can provide some meaningful insight on how to prevent power system cascading failures initiated by joint attacks.
{"title":"Identification of critical line-generation combinations for hypothesized joint line-generation attacks","authors":"Ming Wang, Yingmeng Xiang, Lingfeng Wang, Jie Jiang, Ruosong Xiao, K. Xie","doi":"10.1109/PMAPS.2016.7764212","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764212","url":null,"abstract":"The increasing load demand is pushing power system to operate near its limit, making it more vulnerable to various disturbances and attacks, especially those that might initiate cascading failures. In this study, the joint line-generation attack is introduced which assumes that the lines and generators can be tripped by malicious attacks simultaneously, and it is a natural extension of the previous node-only or line-only attacks. The joint line-generation attack strategy is explored based on a search space reduction algorithm. The simulation is conducted based on several representative test systems. The performance of the proposed attack strategy is compared with other attack strategies and the computational burden is analyzed. It is demonstrated that the proposed attack strategy is effective and computationally efficient. This work can provide some meaningful insight on how to prevent power system cascading failures initiated by joint attacks.","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":"132502131","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.2016.7764218
Y. Liao, Yang Weng, Chin-Woo Tan, R. Rajagopal
The growing integration of distributed energy resources (DERs) in urban distribution grids raises various reliability issues due to complex uncertainties. With the large-scale penetration of DERs, traditional outage detection methods, which rely on customers making phone calls and smart meters' “last gasp” signals, will have limited performance because 1) the renewable generators can supply powers after line outages, and 2) many urban grids are mesh and line outages do not affect power supply. To address these drawbacks, we propose a new data-driven outage monitoring approach based on the stochastic time series analysis with the newly available smart meter data utilized. Specifically, based on the power flow analysis, we prove that the statistical dependency of time-series voltage measurements has significant changes after line outages. Hence, we use the optimal change point detection theory to detect and localize line outages. As the existing change point detection methods require the post-outage voltage distribution, which is unknown in power systems, we propose a maximum likelihood method to learn the distribution parameters from the historical data. The proposed outage detection using estimated parameters also achieves the optimal performance. Simulation results show highly accurate outage identification in IEEE standard distribution test systems with and without DERs using real smart meter data.
{"title":"Urban distribution grid line outage identification","authors":"Y. Liao, Yang Weng, Chin-Woo Tan, R. Rajagopal","doi":"10.1109/PMAPS.2016.7764218","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764218","url":null,"abstract":"The growing integration of distributed energy resources (DERs) in urban distribution grids raises various reliability issues due to complex uncertainties. With the large-scale penetration of DERs, traditional outage detection methods, which rely on customers making phone calls and smart meters' “last gasp” signals, will have limited performance because 1) the renewable generators can supply powers after line outages, and 2) many urban grids are mesh and line outages do not affect power supply. To address these drawbacks, we propose a new data-driven outage monitoring approach based on the stochastic time series analysis with the newly available smart meter data utilized. Specifically, based on the power flow analysis, we prove that the statistical dependency of time-series voltage measurements has significant changes after line outages. Hence, we use the optimal change point detection theory to detect and localize line outages. As the existing change point detection methods require the post-outage voltage distribution, which is unknown in power systems, we propose a maximum likelihood method to learn the distribution parameters from the historical data. The proposed outage detection using estimated parameters also achieves the optimal performance. Simulation results show highly accurate outage identification in IEEE standard distribution test systems with and without DERs using real smart meter data.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"1 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":"132789976","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.2016.7764106
Liting Tian, Jianbo Guo, Lin Cheng
Energy storage is used to balance the variant power for the stability of the grid. It is significant to understand the fluctuation characteristic of renewable energy (RE) generation and the requirements of energy storage when large-scale RE is integrated in the grid. In the paper, a novel method based on time and frequency domain analysis is proposed for energy storage system (ESS) sizing, including both power sizing and energy sizing. According to the relationship between charge/discharge power and stored energy, the sizing model is established based on autocorrelation function and power spectral density (PSD) of the stochastic cycling process. The time and spectral characteristic of RE generation is analyzed based on the historical generation data of a wind farm and a PV station in the Northwest region of China. The size of energy storage is determined by the time and frequency domain method respectively. Comparing with the time domain method, it is showed that the frequency domain method is sufficient for energy storage sizing with enough accuracy and a much easier calculation process at the same time.
{"title":"A novel method for energy storage sizing based on time and frequency domain analysis","authors":"Liting Tian, Jianbo Guo, Lin Cheng","doi":"10.1109/PMAPS.2016.7764106","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764106","url":null,"abstract":"Energy storage is used to balance the variant power for the stability of the grid. It is significant to understand the fluctuation characteristic of renewable energy (RE) generation and the requirements of energy storage when large-scale RE is integrated in the grid. In the paper, a novel method based on time and frequency domain analysis is proposed for energy storage system (ESS) sizing, including both power sizing and energy sizing. According to the relationship between charge/discharge power and stored energy, the sizing model is established based on autocorrelation function and power spectral density (PSD) of the stochastic cycling process. The time and spectral characteristic of RE generation is analyzed based on the historical generation data of a wind farm and a PV station in the Northwest region of China. The size of energy storage is determined by the time and frequency domain method respectively. Comparing with the time domain method, it is showed that the frequency domain method is sufficient for energy storage sizing with enough accuracy and a much easier calculation process at the same time.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"1 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":"131655649","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.2016.7764187
Meng Xu, C. Dent, Amy L. Wilson
Long-term generation investment (LTGI) models have been widely used as a decision-making tool of design of energy policy. Adequate LTGI models with detailed modelling of operations are often computationally intensive. Uncertainty involved in these models poses a great challenge to the uncertainty quantification in power system reliability. This paper presents a Bayesian framework for addressing this challenge systematically. The use of Bayesian techniques enables an efficient model calibration and quantitative study on the robustness of different market designs. In the case study on the future UK power system, the robustness index estimated by the calibrated model is obtained through uncertainty analysis of loss-of-load expectation.
{"title":"Uncertainty quantification in power system reliability using a Bayesian framework","authors":"Meng Xu, C. Dent, Amy L. Wilson","doi":"10.1109/PMAPS.2016.7764187","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764187","url":null,"abstract":"Long-term generation investment (LTGI) models have been widely used as a decision-making tool of design of energy policy. Adequate LTGI models with detailed modelling of operations are often computationally intensive. Uncertainty involved in these models poses a great challenge to the uncertainty quantification in power system reliability. This paper presents a Bayesian framework for addressing this challenge systematically. The use of Bayesian techniques enables an efficient model calibration and quantitative study on the robustness of different market designs. In the case study on the future UK power system, the robustness index estimated by the calibrated model is obtained through uncertainty analysis of loss-of-load expectation.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"383 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":"133433924","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.2016.7764152
Heping Jia, Yi Ding, Yonghua Song, Weidong Liu, Lijun Zhang, Yikai Sun
With the development of information and communication technologies, flexible loads have become more and more popular to participate in the two-way interaction between power generation and consumption. However, the growing proportion of flexible loads has made the reliability of smart grids different from that of traditional power systems. In this paper, time-varying load model including flexible loads has been represented by developed Markov process model. Load curtailment and shifting have been considered in the developed Markov model for flexible loads. Moreover, time-sequential simulation procedures of reliability evaluation for distribution systems considering flexible loads have been developed. The proposed techniques have been validated to the modified IEEE RBTS.
{"title":"Reliability evaluation for distribution systems considering flexible loads utilizing time-sequential simulation techniques","authors":"Heping Jia, Yi Ding, Yonghua Song, Weidong Liu, Lijun Zhang, Yikai Sun","doi":"10.1109/PMAPS.2016.7764152","DOIUrl":"https://doi.org/10.1109/PMAPS.2016.7764152","url":null,"abstract":"With the development of information and communication technologies, flexible loads have become more and more popular to participate in the two-way interaction between power generation and consumption. However, the growing proportion of flexible loads has made the reliability of smart grids different from that of traditional power systems. In this paper, time-varying load model including flexible loads has been represented by developed Markov process model. Load curtailment and shifting have been considered in the developed Markov model for flexible loads. Moreover, time-sequential simulation procedures of reliability evaluation for distribution systems considering flexible loads have been developed. The proposed techniques have been validated to the modified IEEE RBTS.","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":"122579547","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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