Varuneswara Panyam, Hao Huang, Bogdan Pinte, K. Davis, A. Layton
{"title":"Bio-Inspired Design for Robust Power Networks","authors":"Varuneswara Panyam, Hao Huang, Bogdan Pinte, K. Davis, A. Layton","doi":"10.1109/TPEC.2019.8662130","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662130","url":null,"abstract":"Extreme events continue to show that existing power grid configurations can be vulnerable to disturbances. Drawing inspiration from naturally robust biological ecosystems presents a potential source of robust design guidelines for modern power grids. The robust network structure of ecosystems is partially derived from a unique balance between pathway efficiency and redundancy. Structural and basic-functional similarities support the application of ecological properties and analysis techniques to power grid design. The work presented here quantitatively investigates the level of similarity between ecosystems and power grids by applying ecological network metrics to a basic, realistic hypothetical 5-bus power system. A comparison between the power grid’s performance and average ecosystem performance substantiates the use of the ecological robustness metric for the development of a bio-inspired power grid optimization model. The bio-inspired optimization model re-configures the five bus grid to mimic ecosystem robustness. The results demonstrate the potential of ecosystems to provide new robust design principles for power grids.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124658477","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}
Okan Ciftci, M. Mehrtash, F. Safdarian, A. Kargarian
{"title":"Chance-Constrained Microgrid Energy Management with Flexibility Constraints Provided by Battery Storage","authors":"Okan Ciftci, M. Mehrtash, F. Safdarian, A. Kargarian","doi":"10.1109/TPEC.2019.8662200","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662200","url":null,"abstract":"Battery storage devices can potentially provide multiple services to microgrids. However, concurrent modeling and formulation of multiple services in grid management is a challenging problem. This paper proposes an energy management approach for microgrids including electrical and thermal forms of energy sources. The proposed approach takes advantage of battery storage devices for providing multiple services by applying chance-constrained optimization. The battery storage is deployed for 5-minute load following and energy arbitrage purposes. In addition, we have formulated a set of flexibility constraints, taking advantage of battery’s fast ramping capabilities, to enhance microgrid reliability in response to short-term solar power and load fluctuations. That is, the battery is deployed for load following, energy arbitrage, and regulation reserve procurement. Chance constraints are implemented to handle uncertainties of solar generation and load forecasting errors. Interdependencies between thermal and electrical energies are taken into account in the proposed approach. Numerical results show the effectiveness of the proposed approach to handle uncertainties, alleviate the short-term fluctuations, and enhance grid flexibility and reliability.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114649768","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}
{"title":"Fatigue Life Prediction of a Coaxial Multi-Stage Magnetic Gear","authors":"S. Modaresahmadi, A. Hosseinpour, W. Williams","doi":"10.1109/TPEC.2019.8662170","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662170","url":null,"abstract":"Magnetic gearing is an emerging approach to avoid contact failures from the gear teeth interface of mechanical gearboxes through a non-contact torque transmission concept. In this concept, magnetic flux between the inner and outer rotors is modulated through an array of magnetic pieces called the cage rotor. Despite the non-contact nature of magnetic gears in torque transmission, a minimal air-gap between the three rotors is required to achieve the best performance, which leads to more prerequisites in the design process, including bending analysis, thermal stress analysis, dynamic analysis, etc. Due to the fact that there are segmented magnets in a circumferential direction in the inner and outer rotors, as well as segmented pole pieces in the cage rotor, rotation of the gears causes oscillating forces in the active region. On the other hand, in order to increase the performance of the magnetic gearing system, steel bars in the active region are substituted with laminated stacks to gain stronger flow of magnetic flux throughout the system. The presence of the laminated parts is a potential candidate for failure under static and dynamic loads in the system, especially in long term system operation. Due to the lack of contact failure modes in magnetic gears, they are originally designed to be utilized in remote access applications, e.g. offshore, marine hydro-kinetic, and wind turbines, which require the longest operational life time. This demands fatigue analysis in all the critical parts under dynamic loads, specifically the laminated parts and rods holding magnetic components still. In this study, dynamic and fatigue analysis of a flux focusing multi stage magnetic gearbox is investigated through a multi-body dynamics and Finite Element Method, respectively.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116106383","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}
Yu-Cheng Chen, Tim Gieseking, D. Campbell, V. Mooney, S. Grijalva
{"title":"A Hybrid Attack Model for Cyber-Physical Security Assessment in Electricity Grid","authors":"Yu-Cheng Chen, Tim Gieseking, D. Campbell, V. Mooney, S. Grijalva","doi":"10.1109/TPEC.2019.8662138","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662138","url":null,"abstract":"A detailed model of an attack on the power grid involves both a preparation stage as well as an execution stage of the attack. This paper introduces a novel Hybrid Attack Model (HAM) that combines Probabilistic Learning Attacker, Dynamic Defender (PLADD) model and a Markov Chain model to simulate the planning and execution stages of a bad data injection attack in power grid. We discuss the advantages and limitations of the prior work models and of our proposed Hybrid Attack Model and show that HAM is more effective compared to individual PLADD or Markov Chain models.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121240320","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}
F. Safdarian, Logan Lamonte, A. Kargarian, M. Farasat
{"title":"Distributed Optimization-Based Hourly Coordination for V2G and G2V","authors":"F. Safdarian, Logan Lamonte, A. Kargarian, M. Farasat","doi":"10.1109/TPEC.2019.8662148","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662148","url":null,"abstract":"Network-constrained economic dispatch (NCED) problem, which takes into account the random mobility of electric vehicles (EV) and additional variables corresponding to each EV’s charge/discharge cycles, is large scale, complex and computationally expensive. To reduce the computational burden associated with this optimization problem, distributed optimization is introduced. Since EVs randomly move from one bus to another bus, this paper proposes a temporal, rather than a geographical, decomposition approach to divide a ramp-constrained NCED. Thousands of EVs are considered over the scheduling horizon in order to take advantage of parallel computing and achieve reduced solution time. A ramp-constrained NCED is formulated for each sub-horizon while the connections between subproblems are modeled as shared variables/constraints. In order to coordinate the subproblems and find the optimal solution for the entire operation horizon, distributed auxiliary problem principle (APP) is proposed. Further, an efficient initialization strategy is presented to enhance the convergence time of the solution algorithm. The proposed method is employed to solve a week-ahead NCED on a 6-bus and IEEE 118-bus test systems. The results are compared with those of a centralized approach and effectiveness of the proposed method in reducing the solution time is verified.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123366413","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}
{"title":"Half Cycle Negative Sequence Differential Protection for Synchronous Generator","authors":"Ashish Doorwar, B. Bhalja","doi":"10.1109/TPEC.2019.8662180","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662180","url":null,"abstract":"In this paper, a half cycle negative-sequence differential protection principle for internal faults in synchronous generators is presented. In the presented scheme, a new modified half-cycle discrete Fourier transform (DFT)-based phasor estimation algorithm is used. This scheme has many advantages over conventional differential protection (87P) in terms of sensitivity, speed, security, and reliability. The presented technique has been verified on a Phase Domain Synchronous Machine model simulated on the Real Time Digital Simulator (RTDS®). The analysis of congregated fault dataset clearly shows that the scheme is able to discriminate well between internal and external faults even during current transformer saturation, unbalance condition and overloading.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117316202","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}
{"title":"Smart Grid Congestion Caused by Plug-in Electric Vehicle Charging","authors":"Rachel E. Jarvis, P. Moses","doi":"10.1109/TPEC.2019.8662152","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662152","url":null,"abstract":"Plug-in electric vehicles (PEVs) will place a sizeable load on future residential distribution systems. As the popularity of PEVs increases, the network congestion of uncoordinated PEV charging will likely also increase. Until smart charging becomes available, the impact of uncoordinated charging on residential distribution systems must be considered. This paper studies the effects of PEV charger activities of randomly populated, randomly arriving PEVs within several low voltage residential networks. The impacts on network voltages, feeder congestion overloads and distribution transformer loading are investigated.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115446699","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}
{"title":"Future Electric Power Grid and Battery Storage","authors":"Aoxia Chen, Y. Velaga, P. Sen","doi":"10.1109/TPEC.2019.8662126","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662126","url":null,"abstract":"Battery technology is the most promising (besides pumped hydro) of all energy storage applications for the future power grid. With the growth of renewable energy, distributed energy resources, the number of Plug-in Electric Vehicles and more PV installations: large and small, future electric power grid is evolving into a two-way flow of information and electricity between demand and supply. This paper provides an up-to-date information on battery storage as applied to the electric power grid including the cost, technology, design and applications.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123456099","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}
{"title":"Power System Transient Stability Analysis Using High-Order Taylor Expansion Systems","authors":"Bin Wang, Xin Xu, K. Sun","doi":"10.1109/TPEC.2019.8662157","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662157","url":null,"abstract":"Small signal analysis is a special case of analytical approaches using 1st-order Taylor expansion of power system differential equations. High-order Taylor expansions (TEs) can lead to better analytical approaches for stability analysis by considering higher-order nonlinearities, e.g. normal form, modal series and nonlinear modal decoupling. This paper presents fundamental studies on how accurate transient stability analysis results can be obtained from the high-order TEs compared to that based on the original system. Analytical investigations are conducted on single-machine-infinite-bus power systems. Observations are summarized from there and verified on two multi-machine power systems by extensive simulations.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125318870","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}
G. Hussain, Detlef Hummes, M. Shafiq, Madia Safdar
{"title":"Detection of Multiple Partial Discharge Faults in Switchgear and Power Cables","authors":"G. Hussain, Detlef Hummes, M. Shafiq, Madia Safdar","doi":"10.1109/TPEC.2019.8662173","DOIUrl":"https://doi.org/10.1109/TPEC.2019.8662173","url":null,"abstract":"Partial Discharge (PD) measurements are considered as the early detection of insulation degradation in power system equipment. In switchgear and power cables, multiple PD faults may exist, which make the detection and location of such incipient faults challenging. This paper deals with identification of multiple PD faults by a hybrid detection technique, by combining conventional and unconventional measurement methods.Unconventional PD measurements rely on detection of physical emissions due to such faults, e.g. detection of radio frequency (RF) electromagnetic (EM) fields in the vicinity of PD activity, ultrasonic waves, optical emissions and heat produced by the PD, whereas the conventional measurement methods are based on detection of high frequency current and voltage, superimposed on the power frequency current and voltage.In this paper, the apparent charge of PD events is calculated by using conventional measurement technique and EM signal energy is calculated based on unconventional method. The high frequency electric field was measured using a D-dot sensor. The comparison between the two parameters show that a second degree polynomial relation exists between the EM energy and apparent charge. The scatter plots between the two variables show a number of patterns due to the number of PD faults. Therefore, the detection of multiple faults is possible.","PeriodicalId":424038,"journal":{"name":"2019 IEEE Texas Power and Energy Conference (TPEC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128340777","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}