Pub Date : 2017-04-01DOI: 10.1109/ISGT.2017.8086088
E. Hreinsson
In a hydro-dominated power system, with complex inter-temporal linkages, capacities of individual projects and project configurations are more complicated than using the simple megawattage, often used to denote capacity in thermally dominated systems. In this paper, the long term hydro scheduling problem is solved and used to test novel definitions of hydro-capacities, based on expected cost and cost probability distributions for system operating cost, based on rising load and a within-the-year time distribution of load. The paper expands on previous capacity definitions and tests them numerically in a case study with realistic data from a hydro-dominated system. The principal contribution of this paper are new capacity concepts and practical applications for an example of sizing a given reservoir. The testing is performed using actual data from the Icelandic hydro-dominated power system, with the model HYDOVG delivering optimal schedules for various inflow instances and load cases and using linear programming (LP) CPLEX software to optimize each case and instant.
{"title":"Project and system firm capacity definitions with long term hydro scheduling","authors":"E. Hreinsson","doi":"10.1109/ISGT.2017.8086088","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086088","url":null,"abstract":"In a hydro-dominated power system, with complex inter-temporal linkages, capacities of individual projects and project configurations are more complicated than using the simple megawattage, often used to denote capacity in thermally dominated systems. In this paper, the long term hydro scheduling problem is solved and used to test novel definitions of hydro-capacities, based on expected cost and cost probability distributions for system operating cost, based on rising load and a within-the-year time distribution of load. The paper expands on previous capacity definitions and tests them numerically in a case study with realistic data from a hydro-dominated system. The principal contribution of this paper are new capacity concepts and practical applications for an example of sizing a given reservoir. The testing is performed using actual data from the Icelandic hydro-dominated power system, with the model HYDOVG delivering optimal schedules for various inflow instances and load cases and using linear programming (LP) CPLEX software to optimize each case and instant.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133735745","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086074
E. Abbasi, S. H. Hosseini, M. D. Ghamsari
In this paper a reliability, emission, and network security constrained unit commitment (UC) with the focus on wind power integration is formulated. It is shown that clearing both energy and spinning reserve markets taking into account network constraints provides a reliable and economic solution for day-ahead operation planning of a power system with a significant amount of thermal and wind power in the generation portfolio. The developed UC is formulated and implemented in MATLAB. The IEEE 24-Bus Reliability Test System (RTS) is used to verify the UC method by simulation.
{"title":"A unit commitment for electricity market participation of wind farms","authors":"E. Abbasi, S. H. Hosseini, M. D. Ghamsari","doi":"10.1109/ISGT.2017.8086074","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086074","url":null,"abstract":"In this paper a reliability, emission, and network security constrained unit commitment (UC) with the focus on wind power integration is formulated. It is shown that clearing both energy and spinning reserve markets taking into account network constraints provides a reliable and economic solution for day-ahead operation planning of a power system with a significant amount of thermal and wind power in the generation portfolio. The developed UC is formulated and implemented in MATLAB. The IEEE 24-Bus Reliability Test System (RTS) is used to verify the UC method by simulation.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122218649","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086023
Daijiafan Mao, D. Meyer, Jiankang Wang
With increasing penetration and improving fast charging technologies, Plug-in Electric Vehicles (PEV) exert a disruptive influence on power delivery systems. The impulsive and high-power-density characteristics of PEV make conventional assessment methods of load impact unsuitable. This paper proposes an integrated method to investigate the long-term impact of PEV charging on temporal response and depreciation of grid assets in sub-transmission and distribution grid levels (below 69kV). Compared to conventional methods, the proposed method embeds dynamical system models of grid assets in Time-Series (TS) analysis and captures stochastic charging behavior through Monte-Carlo simulation, promising more robust and accurate assessment. Under the proposed method, the Total Cost of Ownership (TCO) of grid assets formulation is re-established. The results of this paper will enable utilities to quantify the capital and operation cost of grid assets induced under various PEV's penetration level and during any time span of interest.
{"title":"Evaluating PEV's impact on long-term cost of grid assets","authors":"Daijiafan Mao, D. Meyer, Jiankang Wang","doi":"10.1109/ISGT.2017.8086023","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086023","url":null,"abstract":"With increasing penetration and improving fast charging technologies, Plug-in Electric Vehicles (PEV) exert a disruptive influence on power delivery systems. The impulsive and high-power-density characteristics of PEV make conventional assessment methods of load impact unsuitable. This paper proposes an integrated method to investigate the long-term impact of PEV charging on temporal response and depreciation of grid assets in sub-transmission and distribution grid levels (below 69kV). Compared to conventional methods, the proposed method embeds dynamical system models of grid assets in Time-Series (TS) analysis and captures stochastic charging behavior through Monte-Carlo simulation, promising more robust and accurate assessment. Under the proposed method, the Total Cost of Ownership (TCO) of grid assets formulation is re-established. The results of this paper will enable utilities to quantify the capital and operation cost of grid assets induced under various PEV's penetration level and during any time span of interest.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127368273","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8085995
O. Ciniglio, M. Papic, M. Vaiman, M. Vaiman
This paper presents an effective practical approach for identifying optimal locations of Phasor Measurement Units (PMUs) to achieve complete system observability. The approach, implemented in Physical and Operational Margins/Region Of Stability Existence (POM/ROSE) software, is based on automated iterative process of forming variables and constraints of a binary integer programming problem. The problem is then solved with standard linear programming solvers. The proposed approach was tested using Idaho Power Co. (IPC) system. It allows us to reduce the number of PMUs as compared to conventional techniques while maintaining complete system observability. A fast topological approach was also demonstrated and tested using IPC data in order to analyze the observability of the IPC network. The algorithm is fast and can be used in real-time as a part of bad data detection framework.
{"title":"Optimal PMU placement to achieve complete observability of Idaho Power Co. System","authors":"O. Ciniglio, M. Papic, M. Vaiman, M. Vaiman","doi":"10.1109/ISGT.2017.8085995","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085995","url":null,"abstract":"This paper presents an effective practical approach for identifying optimal locations of Phasor Measurement Units (PMUs) to achieve complete system observability. The approach, implemented in Physical and Operational Margins/Region Of Stability Existence (POM/ROSE) software, is based on automated iterative process of forming variables and constraints of a binary integer programming problem. The problem is then solved with standard linear programming solvers. The proposed approach was tested using Idaho Power Co. (IPC) system. It allows us to reduce the number of PMUs as compared to conventional techniques while maintaining complete system observability. A fast topological approach was also demonstrated and tested using IPC data in order to analyze the observability of the IPC network. The algorithm is fast and can be used in real-time as a part of bad data detection framework.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128260134","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086047
A. Rouhani, A. Abur
This paper proposes the use of a couple of local PMUs and associated dynamic state estimators in order to detect and remove bad data in PMU measurements. Distinguishing features of the proposed approach is that it facilitates detection of bad-data in local PMU measurements without requiring a system-wide state estimator. The proposed approach relies on a performance evaluation technique which computes the probability density function (pdf) of the residuals provided by a dynamic state estimator. In the proposed approach it is assumed that there are at least two local PMUs that provide measurements to the dynamic state estimators of a synchronous generator. The proposed approach is implemented using a two-axis model of a synchronous generator with IEEE-Type 1 exciter. The performance of the proposed approach is investigated in the presence of bad-data associated with the measurements provided by the PMUs.
{"title":"Local detection of PMU measurement errors using dynamic state estimators","authors":"A. Rouhani, A. Abur","doi":"10.1109/ISGT.2017.8086047","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086047","url":null,"abstract":"This paper proposes the use of a couple of local PMUs and associated dynamic state estimators in order to detect and remove bad data in PMU measurements. Distinguishing features of the proposed approach is that it facilitates detection of bad-data in local PMU measurements without requiring a system-wide state estimator. The proposed approach relies on a performance evaluation technique which computes the probability density function (pdf) of the residuals provided by a dynamic state estimator. In the proposed approach it is assumed that there are at least two local PMUs that provide measurements to the dynamic state estimators of a synchronous generator. The proposed approach is implemented using a two-axis model of a synchronous generator with IEEE-Type 1 exciter. The performance of the proposed approach is investigated in the presence of bad-data associated with the measurements provided by the PMUs.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125540405","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086051
A. Khatib, B. Nayak, Bowen Dai, Jito Coleman, S. Hoskins, Jan Tierson
This paper presents a centralized microgrid control system for effective operation of wind turbines and diesel engines coupled to a flywheel electrical storage component on Saint Paul Island. The wind turbines have sufficient capacity to support the entire island without using the diesel engines, allowing the formation of an islanded power system completely powered by renewables. The proposed strategy includes use of the flywheel, wind turbines, and diesel generators to attain survivability and resilience. The strategy is challenged and validated against different low to turbulent wind gust profiles and low to peak loading. Multiple permissive-based decoupling schemes, tie-flow controls, and heat load trading features are implemented. The tie-line flow control/heat load trading is operated in tandem with local diesel generators and wind turbines to maintain a minimum flow from the utility. The control system was tested using hardware-in-the-loop (HIL) with a simplified electrical model of Saint Paul Island.
{"title":"Design and development of a microgrid control system for integration of induction generation with storage capability at Saint Paul Island, Alaska","authors":"A. Khatib, B. Nayak, Bowen Dai, Jito Coleman, S. Hoskins, Jan Tierson","doi":"10.1109/ISGT.2017.8086051","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086051","url":null,"abstract":"This paper presents a centralized microgrid control system for effective operation of wind turbines and diesel engines coupled to a flywheel electrical storage component on Saint Paul Island. The wind turbines have sufficient capacity to support the entire island without using the diesel engines, allowing the formation of an islanded power system completely powered by renewables. The proposed strategy includes use of the flywheel, wind turbines, and diesel generators to attain survivability and resilience. The strategy is challenged and validated against different low to turbulent wind gust profiles and low to peak loading. Multiple permissive-based decoupling schemes, tie-flow controls, and heat load trading features are implemented. The tie-line flow control/heat load trading is operated in tandem with local diesel generators and wind turbines to maintain a minimum flow from the utility. The control system was tested using hardware-in-the-loop (HIL) with a simplified electrical model of Saint Paul Island.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129351576","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8085972
Smita Lokhande, Y. Bichpuriya
Increasing penetration of intermittent renewable energy at distributed and bulk generation level introduces challenges in maintaining supply-demand balance in the electric grid. To achieve demand-following-generation regime, it is important to utilize flexibility of demand by direct or indirect control. It is referred as Demand Response (DR). Indirect control involves incentives or variable prices in different time blocks to bring the aggregated demand at a desired level. In a market scenario, demand and price are mutually dependent variables, i.e., demand can affect the price and vice-versa. In this paper, we present an empirical analysis of demand response based on real time pricing. The analysis is done to study the convergence of the demand in a closed loop market scenario and sensitivity of DR with varying price elasticity.
{"title":"Empirical analysis of convergence and sensitivity of demand response based on real time pricing","authors":"Smita Lokhande, Y. Bichpuriya","doi":"10.1109/ISGT.2017.8085972","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085972","url":null,"abstract":"Increasing penetration of intermittent renewable energy at distributed and bulk generation level introduces challenges in maintaining supply-demand balance in the electric grid. To achieve demand-following-generation regime, it is important to utilize flexibility of demand by direct or indirect control. It is referred as Demand Response (DR). Indirect control involves incentives or variable prices in different time blocks to bring the aggregated demand at a desired level. In a market scenario, demand and price are mutually dependent variables, i.e., demand can affect the price and vice-versa. In this paper, we present an empirical analysis of demand response based on real time pricing. The analysis is done to study the convergence of the demand in a closed loop market scenario and sensitivity of DR with varying price elasticity.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134554226","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086076
Rui Yang, Huaiguang Jiang, Y. Zhang
A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severe voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.
{"title":"Short-term state forecasting-based optimal voltage regulation in distribution systems","authors":"Rui Yang, Huaiguang Jiang, Y. Zhang","doi":"10.1109/ISGT.2017.8086076","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086076","url":null,"abstract":"A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severe voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"653 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134165918","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086013
H. Moradi, D. D. Groff, A. Abtahi
A standalone microgrid with renewable and regular power resources along with storage system play an important role in remote areas in order to solve power supply problems. In this research, an optimal energy management of a standalone microgrid under different operational modes is studied. The objective of the optimization model is to improve energy utilization efficiency; reduce fuel cost and gas emissions by scheduling productions of energy resources in each hour on the next day. In another word, the problem is modeled as a constrained single-objective programming to minimize cost of power and emission generations. The system is tested under two different operational policies where microgrid power generation sources work with and without battery storage system. Then the final results are compared and investigated. The results show a considerable reduction in system total cost and generated emission in comparison with previously proposed methods.
{"title":"Optimal energy scheduling of a stand-alone multi-sourced microgrid considering environmental aspects","authors":"H. Moradi, D. D. Groff, A. Abtahi","doi":"10.1109/ISGT.2017.8086013","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086013","url":null,"abstract":"A standalone microgrid with renewable and regular power resources along with storage system play an important role in remote areas in order to solve power supply problems. In this research, an optimal energy management of a standalone microgrid under different operational modes is studied. The objective of the optimization model is to improve energy utilization efficiency; reduce fuel cost and gas emissions by scheduling productions of energy resources in each hour on the next day. In another word, the problem is modeled as a constrained single-objective programming to minimize cost of power and emission generations. The system is tested under two different operational policies where microgrid power generation sources work with and without battery storage system. Then the final results are compared and investigated. The results show a considerable reduction in system total cost and generated emission in comparison with previously proposed methods.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133260896","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086003
F. Mohammadi, H. Keshtkar, A. Feliachi, V. Kulathumani
This paper is on the design of an adaptive sending rate for frequency regulation of a smart microgrid. The frequency controller itself is designed using an optimal LQR (Linear Quadratic Regulator) approach whose parameters are obtained using Particle Swarm Optimization (PSO). The utilized isolated smart microgrid comprises different Distributed Generation (DG) units and Renewable Energy Sources (RESs). Implementation of the optimal LQR controller requires a communication network. The key issue in this Networked Control System (NCS) is the transmission of measured data from the multiple sensing agents to the controller. Usually the data is sent in constant intervals which raises energy issues and channel capacity and requires bigger sending rate that will cause more error in the frequency response. The paper proposes different adaptive approaches for determining an adequate sending rate. Simulation results show the effectiveness of the proposed approaches as compared to conventional methods.
{"title":"Design of an adaptive sending rate for frequency regulation of a smart microgrid with optimal LQR controller","authors":"F. Mohammadi, H. Keshtkar, A. Feliachi, V. Kulathumani","doi":"10.1109/ISGT.2017.8086003","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086003","url":null,"abstract":"This paper is on the design of an adaptive sending rate for frequency regulation of a smart microgrid. The frequency controller itself is designed using an optimal LQR (Linear Quadratic Regulator) approach whose parameters are obtained using Particle Swarm Optimization (PSO). The utilized isolated smart microgrid comprises different Distributed Generation (DG) units and Renewable Energy Sources (RESs). Implementation of the optimal LQR controller requires a communication network. The key issue in this Networked Control System (NCS) is the transmission of measured data from the multiple sensing agents to the controller. Usually the data is sent in constant intervals which raises energy issues and channel capacity and requires bigger sending rate that will cause more error in the frequency response. The paper proposes different adaptive approaches for determining an adequate sending rate. Simulation results show the effectiveness of the proposed approaches as compared to conventional methods.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122238095","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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