Pub Date : 2017-10-19DOI: 10.1109/ISAP.2017.8071400
Minjiang Chen, Dimitrios Athanasiadis, B. A. Faiya, S. Mcarthur, I. Kockar, Haowei Lu, F. de León
In this paper, an intelligent distributed multi-agent system (MAS) is proposed for the implementation of a novel optimization technique for distributed voltage regulation. The proposed MAS approach controls a large heavily-meshed distribution network which is grouped into small subnetworks using ε decomposition. The voltage regulation is accomplished by distributed generator (DG) agents, linear programming solver (LPS) agents, network violation detector (NVD) agents, and one ε decomposition agent. The LPS agent has an embedded control algorithm which optimizes DG generation within a subnetwork once the voltage at particular nodes exceeds the normal operational limits. The subnetworks and their control requirements are achieved through self-organization, which is the novelty of the research. Each intelligent agent has its own knowledge and reasoning logic to plan its own activities. The control actions are coordinated through agent communications within the subnetwork. The agent platform, Presage2, with improved autonomy and agent communication capability, has been used to develop the proposed MAS system and design the agents' behaviors.
{"title":"Design of a multi-agent system for distributed voltage regulation","authors":"Minjiang Chen, Dimitrios Athanasiadis, B. A. Faiya, S. Mcarthur, I. Kockar, Haowei Lu, F. de León","doi":"10.1109/ISAP.2017.8071400","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071400","url":null,"abstract":"In this paper, an intelligent distributed multi-agent system (MAS) is proposed for the implementation of a novel optimization technique for distributed voltage regulation. The proposed MAS approach controls a large heavily-meshed distribution network which is grouped into small subnetworks using ε decomposition. The voltage regulation is accomplished by distributed generator (DG) agents, linear programming solver (LPS) agents, network violation detector (NVD) agents, and one ε decomposition agent. The LPS agent has an embedded control algorithm which optimizes DG generation within a subnetwork once the voltage at particular nodes exceeds the normal operational limits. The subnetworks and their control requirements are achieved through self-organization, which is the novelty of the research. Each intelligent agent has its own knowledge and reasoning logic to plan its own activities. The control actions are coordinated through agent communications within the subnetwork. The agent platform, Presage2, with improved autonomy and agent communication capability, has been used to develop the proposed MAS system and design the agents' behaviors.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"44 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134593871","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071379
José Ubirajara Núñez de Nunes, A. Bretas
This paper presents an optimization methodology based on tabu search to solve a unconstraint voltage regulators allocation problem in power distribution networks. The main objective is to find a balance between costs related to system planning and the fulfillment of power quality indexes. Analysis of the voltage profile and the objective function are carried out in the MATLAB environment for a typical distribution feeder containing lateral branches. Test results indicate high method's robustness and potential for real life applications.
{"title":"Voltage regulators allocation in power distribution networks: A tabu search approach","authors":"José Ubirajara Núñez de Nunes, A. Bretas","doi":"10.1109/ISAP.2017.8071379","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071379","url":null,"abstract":"This paper presents an optimization methodology based on tabu search to solve a unconstraint voltage regulators allocation problem in power distribution networks. The main objective is to find a balance between costs related to system planning and the fulfillment of power quality indexes. Analysis of the voltage profile and the objective function are carried out in the MATLAB environment for a typical distribution feeder containing lateral branches. Test results indicate high method's robustness and potential for real life applications.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121924569","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071398
T. Lan, Garng M. Huang
Daily load variation and intermittence of renewable generation may sometime cause transmission congestion in modern power system. As a result, cheap generation cannot be fully dispatched and in extreme condition involuntary load shedding will be enforced. In this paper, an intelligent parallel scheduling method using optimal transmission switching (OTS) and batteries is proposed to mitigate transmission congestion and therefore reduce operational cost. OTS and batteries are embedded in AC optimal power flow (ACOPF) with binary variables used, which is formulated as a mixed integer nonlinear programming (MINLP) problem. To solve the MINLP problem efficiently for multi-hour case, a two-stage optimization scheme is proposed based on developed knowledge. A multi-hour case first is calculated in stage one with OTS disabled to obtain the knowledge of estimated the optimal charging/discharging strategy for batteries. Then, the multi-hour case is decoupled into several subproblems and solved simultaneously in parallel computing. Numerical results on modified IEEE-118 bus system shows the usefulness of the proposed intelligent parallel scheduling method.
{"title":"An intelligent parallel scheduling method for optimal transmission switching in power systems with batteries","authors":"T. Lan, Garng M. Huang","doi":"10.1109/ISAP.2017.8071398","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071398","url":null,"abstract":"Daily load variation and intermittence of renewable generation may sometime cause transmission congestion in modern power system. As a result, cheap generation cannot be fully dispatched and in extreme condition involuntary load shedding will be enforced. In this paper, an intelligent parallel scheduling method using optimal transmission switching (OTS) and batteries is proposed to mitigate transmission congestion and therefore reduce operational cost. OTS and batteries are embedded in AC optimal power flow (ACOPF) with binary variables used, which is formulated as a mixed integer nonlinear programming (MINLP) problem. To solve the MINLP problem efficiently for multi-hour case, a two-stage optimization scheme is proposed based on developed knowledge. A multi-hour case first is calculated in stage one with OTS disabled to obtain the knowledge of estimated the optimal charging/discharging strategy for batteries. Then, the multi-hour case is decoupled into several subproblems and solved simultaneously in parallel computing. Numerical results on modified IEEE-118 bus system shows the usefulness of the proposed intelligent parallel scheduling method.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129449302","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071425
W. Richardson, H. Krishnaswami, L. Shephard, R. Vega
Increasing penetration of photovoltaics (PV) into the electric grid necessitates accurate intra-hour solar irra-diance forecasting. The authors have previously developed a low cost all-sky imaging system at the University of Texas at San Antonio. The SkyImager hardware is designed around a Raspberry Pi single board computer (SBC) with a fully programmable, high resolution Pi Camera, housed in an all-weather enclosure. The software to process the images and to make minutes-ahead forecasts is written in Python 2.7 and utilizes the open source computer vision package OpenCV. A two-step approach for the forecasts uses optical flow to track low-level cumulus clouds and ray-tracing to predict the location of cloud shadows. This paper proposes to replace the ray-tracing approach which is traditionally known to be an ill-posed inverse problem with a machine learning strategy that utilizes a novel multi-layer perceptron (MLP) to classify cloud-cover in sub-images of the circumsolar region. The developed SkyImager was deployed at the National Renewable Energy Laboratory (NREL) in 2015, where it successfully collected months of all-sky image data. In 2016 a second SkyImager was integrated into a microgrid management system at Joint Base San Antonio. Results are presented to validate the proposed methodology.
{"title":"Machine learning versus ray-tracing to forecast irradiance for an edge-computing SkyImager","authors":"W. Richardson, H. Krishnaswami, L. Shephard, R. Vega","doi":"10.1109/ISAP.2017.8071425","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071425","url":null,"abstract":"Increasing penetration of photovoltaics (PV) into the electric grid necessitates accurate intra-hour solar irra-diance forecasting. The authors have previously developed a low cost all-sky imaging system at the University of Texas at San Antonio. The SkyImager hardware is designed around a Raspberry Pi single board computer (SBC) with a fully programmable, high resolution Pi Camera, housed in an all-weather enclosure. The software to process the images and to make minutes-ahead forecasts is written in Python 2.7 and utilizes the open source computer vision package OpenCV. A two-step approach for the forecasts uses optical flow to track low-level cumulus clouds and ray-tracing to predict the location of cloud shadows. This paper proposes to replace the ray-tracing approach which is traditionally known to be an ill-posed inverse problem with a machine learning strategy that utilizes a novel multi-layer perceptron (MLP) to classify cloud-cover in sub-images of the circumsolar region. The developed SkyImager was deployed at the National Renewable Energy Laboratory (NREL) in 2015, where it successfully collected months of all-sky image data. In 2016 a second SkyImager was integrated into a microgrid management system at Joint Base San Antonio. Results are presented to validate the proposed methodology.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"888 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113982353","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071383
Dimitrios Zografos, M. Ghandhari, K. Paridari
Power system inertia is being globally reduced, due to the substitution of conventional synchronous power plants by intermittent generation. This threatens the frequency stability of the system and makes the estimation of power system inertia necessary, so that proactive measures can be imposed. A disturbance-based method is proposed in this paper, which estimates the total inertia constant of the power system. The method applies particle swarm optimization (PSO) to minimize a cost function, which is defined based on the swing equation. To do that, data available at the generator buses are employed. The proposed method is applied on the Nordic57 test system under twenty different scenarios, which include generator and load disconnections. Furthermore, a comparison with two methods presented in the literature is performed and demonstrates the higher performance of the proposed method, in the sense of the mean and the variance of the errors.
{"title":"Estimation of power system inertia using particle swarm optimization","authors":"Dimitrios Zografos, M. Ghandhari, K. Paridari","doi":"10.1109/ISAP.2017.8071383","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071383","url":null,"abstract":"Power system inertia is being globally reduced, due to the substitution of conventional synchronous power plants by intermittent generation. This threatens the frequency stability of the system and makes the estimation of power system inertia necessary, so that proactive measures can be imposed. A disturbance-based method is proposed in this paper, which estimates the total inertia constant of the power system. The method applies particle swarm optimization (PSO) to minimize a cost function, which is defined based on the swing equation. To do that, data available at the generator buses are employed. The proposed method is applied on the Nordic57 test system under twenty different scenarios, which include generator and load disconnections. Furthermore, a comparison with two methods presented in the literature is performed and demonstrates the higher performance of the proposed method, in the sense of the mean and the variance of the errors.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121846542","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071385
Monir Hossain, Lipika Mittal, P. Rastgoufard
Alienation coefficient based busbar fault discriminator is one of the latest methods used to supervise the busbar differential protection schemes for detecting internal and external faults correctly. This fault discriminator uses alienation coefficient of current signals obtained from equivalent two-terminal busbar configuration to discriminate internal and external faults. This paper reports the impact of dynamic changes in network topology of power systems on the performance of alienation coefficient based fault discriminator. A Dynamic Current Allocation Algorithm (DCAA) is presented for the fault discriminator to address the impact of network topology alteration. The performance of the modified fault discriminator is validated by a simulation study. The results documented in this paper show the capability of modified fault discriminator in discriminating internal and external faults even when there is a dynamic change in network topology.
{"title":"A dynamic current allocation algorithm for alienation coefficient based busbar fault discriminator","authors":"Monir Hossain, Lipika Mittal, P. Rastgoufard","doi":"10.1109/ISAP.2017.8071385","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071385","url":null,"abstract":"Alienation coefficient based busbar fault discriminator is one of the latest methods used to supervise the busbar differential protection schemes for detecting internal and external faults correctly. This fault discriminator uses alienation coefficient of current signals obtained from equivalent two-terminal busbar configuration to discriminate internal and external faults. This paper reports the impact of dynamic changes in network topology of power systems on the performance of alienation coefficient based fault discriminator. A Dynamic Current Allocation Algorithm (DCAA) is presented for the fault discriminator to address the impact of network topology alteration. The performance of the modified fault discriminator is validated by a simulation study. The results documented in this paper show the capability of modified fault discriminator in discriminating internal and external faults even when there is a dynamic change in network topology.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128845925","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071378
M. Vallem, B. Vyakaranam, Jesse T. Holzer, M. Elizondo, N. Samaan
Power system algorithms such as AC optimal power flow and coordinated volt/var control of the bulk power system are computationally intensive and become difficult to solve in operational time frames. The computational time required to run these algorithms increases exponentially as the size of the power system increases. The solution time for multiple subsystems is less than that for solving the entire system simultaneously, and the local nature of the voltage problem lends itself to such decomposition. This paper describes an algorithm that can be used to perform power system decomposition from the point of view of the voltage control problem. Our approach takes advantage of the dominant localized effect of voltage control and is based on clustering buses according to the electrical distances between them. One of the contributions of the paper is to use multidimensional scaling to compute «-dimensional Euclidean coordinates for each bus based on electrical distance to perform algorithms like K-means clustering. A simple coordinated reactive power control of photovoltaic inverters for voltage regulation is used to demonstrate the effectiveness of the proposed decomposition algorithm and its components. The proposed decomposition method is demonstrated on the IEEE 118-bus system.
{"title":"Power system decomposition for practical implementation of bulk-grid voltage control methods","authors":"M. Vallem, B. Vyakaranam, Jesse T. Holzer, M. Elizondo, N. Samaan","doi":"10.1109/ISAP.2017.8071378","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071378","url":null,"abstract":"Power system algorithms such as AC optimal power flow and coordinated volt/var control of the bulk power system are computationally intensive and become difficult to solve in operational time frames. The computational time required to run these algorithms increases exponentially as the size of the power system increases. The solution time for multiple subsystems is less than that for solving the entire system simultaneously, and the local nature of the voltage problem lends itself to such decomposition. This paper describes an algorithm that can be used to perform power system decomposition from the point of view of the voltage control problem. Our approach takes advantage of the dominant localized effect of voltage control and is based on clustering buses according to the electrical distances between them. One of the contributions of the paper is to use multidimensional scaling to compute «-dimensional Euclidean coordinates for each bus based on electrical distance to perform algorithms like K-means clustering. A simple coordinated reactive power control of photovoltaic inverters for voltage regulation is used to demonstrate the effectiveness of the proposed decomposition algorithm and its components. The proposed decomposition method is demonstrated on the IEEE 118-bus system.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115010715","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071391
Aysun Koksal, A. Ozdemir, O. Ata
RCAM based maintenance planning of power transmission grid aims to optimize the planned outage of the assets that maximizes the system reliability without additional cost increases. A recent RCAM based transformer maintenance procedure is extended to the system level and a revised maintenance plan is proposed to achieve better reliability indices, total costs and longer life cycles. k-means clustering algorithm is used for criticality assessment and classification of the transformers with respect to two criticality criteria. The proposed classification is applied to the power transformers of Turkish National Power Transmission System and the results are discussed in terms of accuracy and the applicability.
{"title":"RCAM based maintenance plan of the power transformers using k-means clustering algorithm","authors":"Aysun Koksal, A. Ozdemir, O. Ata","doi":"10.1109/ISAP.2017.8071391","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071391","url":null,"abstract":"RCAM based maintenance planning of power transmission grid aims to optimize the planned outage of the assets that maximizes the system reliability without additional cost increases. A recent RCAM based transformer maintenance procedure is extended to the system level and a revised maintenance plan is proposed to achieve better reliability indices, total costs and longer life cycles. k-means clustering algorithm is used for criticality assessment and classification of the transformers with respect to two criticality criteria. The proposed classification is applied to the power transformers of Turkish National Power Transmission System and the results are discussed in terms of accuracy and the applicability.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124048711","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071416
Xinbo Geng, Le Xie, D. Obadina
Reactive power support devices (RPSDs) such as capacitor banks and Static Var Compensators (SVCs) play a pivotal role in ensuring system voltage security. In large power systems with high penetration of renewables, the variability brought about by the renewables requires more coordination among these reactive power support devices. In this paper, we investigate the benefits of look-ahead coordination of both continuous-state and discrete-state RPSDs across multiple control areas. The objective is to coordinate multiple RPSDs in anticipation of near-term net load variations in order to minimize the costs of RPSD operations and transmission losses. Constraints include ensuring voltage security with respect to a set of possible contingency scenarios. This problem is first formulated as a Mixed Integer Non-Linear Programming (MINLP) problem and then approximated as a Mixed Integer Quadratic Programming (MIQP) problem via power flow Jacobian matrix. The validity of the solution to the MIQP problem is verified by solving AC power flow equations. The proposed approach is examined on the IEEE 24-bus Reliability Test System (RTS) system. Critical discussions on the impacts of wind uncertainties are provided, and a linear approximation approach is proposed to estimate the impacts of wind fluctuations on voltage magnitudes.
{"title":"Voltage security constrained look-ahead coordination of reactive power support devices with high renewables","authors":"Xinbo Geng, Le Xie, D. Obadina","doi":"10.1109/ISAP.2017.8071416","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071416","url":null,"abstract":"Reactive power support devices (RPSDs) such as capacitor banks and Static Var Compensators (SVCs) play a pivotal role in ensuring system voltage security. In large power systems with high penetration of renewables, the variability brought about by the renewables requires more coordination among these reactive power support devices. In this paper, we investigate the benefits of look-ahead coordination of both continuous-state and discrete-state RPSDs across multiple control areas. The objective is to coordinate multiple RPSDs in anticipation of near-term net load variations in order to minimize the costs of RPSD operations and transmission losses. Constraints include ensuring voltage security with respect to a set of possible contingency scenarios. This problem is first formulated as a Mixed Integer Non-Linear Programming (MINLP) problem and then approximated as a Mixed Integer Quadratic Programming (MIQP) problem via power flow Jacobian matrix. The validity of the solution to the MIQP problem is verified by solving AC power flow equations. The proposed approach is examined on the IEEE 24-bus Reliability Test System (RTS) system. Critical discussions on the impacts of wind uncertainties are provided, and a linear approximation approach is proposed to estimate the impacts of wind fluctuations on voltage magnitudes.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115295091","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 : 2017-09-01DOI: 10.1109/ISAP.2017.8071369
Ikponmwosa Idehen, T. Overbye
This paper presents a two stage error detection technique for a power system time series data. It implements a local similarity method to isolate an anomalous time series data, and further applies a window scanning technique to detect instances of inconsistent data segments. The requirement for few parameter definitions and small computation time makes this technique attractive for data error detection. Validation of the technique is carried out using data obtained from prototyped PMU clock delay and GPS signal loss.
{"title":"A similarity-based PMU error detection technique","authors":"Ikponmwosa Idehen, T. Overbye","doi":"10.1109/ISAP.2017.8071369","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071369","url":null,"abstract":"This paper presents a two stage error detection technique for a power system time series data. It implements a local similarity method to isolate an anomalous time series data, and further applies a window scanning technique to detect instances of inconsistent data segments. The requirement for few parameter definitions and small computation time makes this technique attractive for data error detection. Validation of the technique is carried out using data obtained from prototyped PMU clock delay and GPS signal loss.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123832586","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：