Pub Date : 2015-12-01DOI: 10.1109/SGC.2015.7857382
M. Alipour, M. Jalali, K. Zare
This paper presents an effective method for deriving stochastic solution to the security- constrained unit commitment (SCUC) problem, which takes into account wind uncertainties via effective scenarios. Increasing penetration of intermittent renewable generations forces independent system operators (ISOs) with new challenges for the economic and secure operation of power systems. The proposed model is applied to a modified 24-bus IEEE Reliability Test System considering two case studies. The case studies investigate the effect of PV arrays in the stochastic SCUC problem. The simulation outcomes confirm the applicability and effectiveness of proposed model.
{"title":"A comprehensive model for security-constrained unit commitment considering renewable energy resources","authors":"M. Alipour, M. Jalali, K. Zare","doi":"10.1109/SGC.2015.7857382","DOIUrl":"https://doi.org/10.1109/SGC.2015.7857382","url":null,"abstract":"This paper presents an effective method for deriving stochastic solution to the security- constrained unit commitment (SCUC) problem, which takes into account wind uncertainties via effective scenarios. Increasing penetration of intermittent renewable generations forces independent system operators (ISOs) with new challenges for the economic and secure operation of power systems. The proposed model is applied to a modified 24-bus IEEE Reliability Test System considering two case studies. The case studies investigate the effect of PV arrays in the stochastic SCUC problem. The simulation outcomes confirm the applicability and effectiveness of proposed model.","PeriodicalId":117785,"journal":{"name":"2015 Smart Grid Conference (SGC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124139613","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 : 2015-12-01DOI: 10.1109/SGC.2015.7857419
S. Jamali, A. Bahmanyar, H. Borhani-Bahabadi
This paper proposes a fault-location method for distribution networks with dispersed generation (DG) based on the measured voltages at DG terminals. The main idea is to estimate the faulty node by considering the fault in different points and exploring the level of similarity between the calculated and measured voltage sags. In the proposed method, this process is considered as an optimization problem of which the fault location and fault resistance are unknown variables and an efficient genetic algorithm-based technique is developed to obtain an optimal solution. The performance of the proposed method is demonstrated by simulation studies on a 25-node distribution system. The results indicate that using an intelligent search procedure, the method has a good performance for different values of fault resistances, and locations.
{"title":"A fast and accurate fault location method for distribution networks with dg using genetic algorithms","authors":"S. Jamali, A. Bahmanyar, H. Borhani-Bahabadi","doi":"10.1109/SGC.2015.7857419","DOIUrl":"https://doi.org/10.1109/SGC.2015.7857419","url":null,"abstract":"This paper proposes a fault-location method for distribution networks with dispersed generation (DG) based on the measured voltages at DG terminals. The main idea is to estimate the faulty node by considering the fault in different points and exploring the level of similarity between the calculated and measured voltage sags. In the proposed method, this process is considered as an optimization problem of which the fault location and fault resistance are unknown variables and an efficient genetic algorithm-based technique is developed to obtain an optimal solution. The performance of the proposed method is demonstrated by simulation studies on a 25-node distribution system. The results indicate that using an intelligent search procedure, the method has a good performance for different values of fault resistances, and locations.","PeriodicalId":117785,"journal":{"name":"2015 Smart Grid Conference (SGC)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128275600","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 : 2015-12-01DOI: 10.1109/SGC.2015.7857418
Seyed Sina Mousavi-Seyedi, F. Aminifar, M. Rezaei, R. Hasani
A new synchrophasor-based fault location algorithm for series-compensated transmission lines is presented in this paper. Both prefault and fault voltage and current phasors associated with either ends of a given line accessible through the phasor measurement units (PMUs) are taken as input data. The proposed algorithm initially estimates the line parameters using prefault data; thereafter, these parameters are used for estimating the fault location. This method is based on the positive-sequence equivalent π models of transmission lines, and since PMU can measure prefault and fault positivesequence data in both symmetrical and unsymmetrical conditions, the method is applicable to all types of faults. The nonlinear weighted least square error (NWLSE) as a powerful method for tackling nonlinear estimation problem is used for the estimation process. Numerical case studies using MATLAB program demonstrate effectiveness of the new method.
{"title":"Optimal fault location algorithm for series-compensated transmission lines based on PMU data","authors":"Seyed Sina Mousavi-Seyedi, F. Aminifar, M. Rezaei, R. Hasani","doi":"10.1109/SGC.2015.7857418","DOIUrl":"https://doi.org/10.1109/SGC.2015.7857418","url":null,"abstract":"A new synchrophasor-based fault location algorithm for series-compensated transmission lines is presented in this paper. Both prefault and fault voltage and current phasors associated with either ends of a given line accessible through the phasor measurement units (PMUs) are taken as input data. The proposed algorithm initially estimates the line parameters using prefault data; thereafter, these parameters are used for estimating the fault location. This method is based on the positive-sequence equivalent π models of transmission lines, and since PMU can measure prefault and fault positivesequence data in both symmetrical and unsymmetrical conditions, the method is applicable to all types of faults. The nonlinear weighted least square error (NWLSE) as a powerful method for tackling nonlinear estimation problem is used for the estimation process. Numerical case studies using MATLAB program demonstrate effectiveness of the new method.","PeriodicalId":117785,"journal":{"name":"2015 Smart Grid Conference (SGC)","volume":"893 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123253219","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 : 2015-12-01DOI: 10.1109/SGC.2015.7857416
N. Nikmehr, S. Najafi-Ravadanegh
In this paper, Multi-Microgrids (MMG) are considered as future smart distribution grids, in which small scale energy resources (SSER) are main power generation units with small scales. Optimal operation of microgrids in defined intervals is carried out to achieve economic conditions in distribution systems. The defined operating problem is optimized using a heuristic algorithm considering uncertainties in loads and renewable energy resources (RERs). The probability density functions (PDFs) are used to encounter with the uncertainties. The total cost of the network is minimized by the algorithm. Then the reliability evaluation is done for each MG. Some new introduced reliability indices in the literature for MGs are used to evaluate the MGs reliability and costs. In proposed structure, the MGs are in interconnected mode and there is power exchanging between MGs. The particle swarm optimization (PSO) algorithm is applied to optimal power dispatch and the obtained results are compared by Monte Carlo simulation (MCS) method.
{"title":"Reliability evaluation in multi-microgrids under probabilistic optimum operation using heuristic algorithm","authors":"N. Nikmehr, S. Najafi-Ravadanegh","doi":"10.1109/SGC.2015.7857416","DOIUrl":"https://doi.org/10.1109/SGC.2015.7857416","url":null,"abstract":"In this paper, Multi-Microgrids (MMG) are considered as future smart distribution grids, in which small scale energy resources (SSER) are main power generation units with small scales. Optimal operation of microgrids in defined intervals is carried out to achieve economic conditions in distribution systems. The defined operating problem is optimized using a heuristic algorithm considering uncertainties in loads and renewable energy resources (RERs). The probability density functions (PDFs) are used to encounter with the uncertainties. The total cost of the network is minimized by the algorithm. Then the reliability evaluation is done for each MG. Some new introduced reliability indices in the literature for MGs are used to evaluate the MGs reliability and costs. In proposed structure, the MGs are in interconnected mode and there is power exchanging between MGs. The particle swarm optimization (PSO) algorithm is applied to optimal power dispatch and the obtained results are compared by Monte Carlo simulation (MCS) method.","PeriodicalId":117785,"journal":{"name":"2015 Smart Grid Conference (SGC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124372920","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：