Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems.

[1]  Mirko Perkusich,et al.  A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems , 2015, Sensors.

[2]  Saeed Zolfaghari,et al.  Chaotic time series prediction with residual analysis method using hybrid Elman-NARX neural networks , 2010, Neurocomputing.

[3]  Youda Liu,et al.  Asynchronous harmonic analysis based on out-of-sequence measurement for large-scale residential power network , 2015, 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings.

[4]  Yuanqing Xia,et al.  Optimal linear estimation for systems with transmission delays and packet dropouts , 2013, IET Signal Process..

[5]  S. Coraluppi,et al.  Advances in asynchronous and decentralized estimation , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[6]  Juan A. Besada,et al.  Multisensor fusion for linear control systems with asynchronous, Out-Of-Sequence and erroneous data , 2011, Autom..

[7]  Thiagalingam Kirubarajan,et al.  Out-of-sequence measurement processing for tracking ground target using particle filters , 2002, Proceedings, IEEE Aerospace Conference.

[8]  Ronald J. Williams,et al.  Gradient-based learning algorithms for recurrent networks and their computational complexity , 1995 .

[9]  A. Marrs,et al.  Particle filters for tracking with out-of-sequence measurements , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[10]  J. H. Marks,et al.  Predictive transient-following control of shunt and series active power filters , 2002 .

[11]  Yaakov Bar-Shalom,et al.  Update with out-of-sequence measurements in tracking: exact solution , 2000, SPIE Defense + Commercial Sensing.

[12]  Klaus C. J. Dietmayer,et al.  Impact of out-of-sequence measurements on the joint integrated probabilistic data association filter for vehicle safety systems , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[13]  Wenxia Liu,et al.  A Key Management Scheme for Secure Communications of Advanced Metering Infrastructure in Smart Grid , 2013, IEEE Transactions on Industrial Electronics.

[14]  Gayadhar Panda,et al.  Fast and accurate measurement of harmonic parameters employing hybrid adaptive linear neural network and filtered-x least mean square algorithm , 2016 .

[15]  Nikos D. Sidiropoulos,et al.  Optimal Particle Filters for Tracking a Time-Varying Harmonic or Chirp Signal , 2008, IEEE Transactions on Signal Processing.

[16]  José M. F. Moura,et al.  Modeling of Future Cyber–Physical Energy Systems for Distributed Sensing and Control , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[17]  Y. Bar-Shalom,et al.  One-step solution for the multistep out-of-sequence-measurement problem in tracking , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[18]  Huimin Chen,et al.  One-step solution for the general out-of-sequence-measurement problem in tracking , 2002, Proceedings, IEEE Aerospace Conference.

[19]  Shuo Zhang,et al.  Optimal Update with Multiple Out-of-Sequence Measurements with Arbitrary Arriving Order , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[20]  José Luís Calvo-Rolle,et al.  A New Missing Data Imputation Algorithm Applied to Electrical Data Loggers , 2015, Sensors.

[21]  José Antonio López Orozco,et al.  Localization of Non-Linearly Modeled Autonomous Mobile Robots Using Out-of-Sequence Measurements , 2012, Sensors.

[22]  Xenofon D. Koutsoukos,et al.  Efficient Evaluation of Wireless Real-Time Control Networks , 2015, Sensors.

[23]  A.G. Exposito,et al.  Self-tuning of Kalman filters for harmonic computation , 2006, IEEE Transactions on Power Delivery.

[24]  Marco L. Della Vedova,et al.  Real-Time Modeling for Direct Load Control in Cyber-Physical Power Systems , 2011, IEEE Transactions on Industrial Informatics.

[25]  Roque Alfredo Osornio-Rios,et al.  A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances , 2013, Sensors.

[26]  Xuan Liu,et al.  Efficient Delay-Tolerant Particle Filtering , 2011, IEEE Transactions on Signal Processing.

[27]  Li Cheng,et al.  Parameterized Convergence Bounds for Volterra Series Expansion of NARX Models , 2013, IEEE Transactions on Signal Processing.

[28]  Hengyi Wang,et al.  Adaptive Kalman filter for harmonic detection in active power filter application , 2015, 2015 IEEE Electrical Power and Energy Conference (EPEC).

[29]  Xue Wang,et al.  Collaborative signal processing for target tracking in distributed wireless sensor networks , 2007, J. Parallel Distributed Comput..

[30]  Isaac Skog,et al.  Bayesian Estimation With Distance Bounds , 2012, IEEE Signal Processing Letters.

[31]  Yunmin Zhu,et al.  Optimal update with out-of-sequence measurements , 2005, IEEE Transactions on Signal Processing.

[32]  Vinod Khadkikar,et al.  Application of Artificial Neural Networks for Shunt Active Power Filter Control , 2014, IEEE Transactions on Industrial Informatics.

[33]  Makarand S. Ballal,et al.  Modeling the measurement error of energy meter using NARX model , 2016, 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[34]  Robin J. Evans,et al.  A Bayesian solution and its approximations to out-of-sequence measurement problems , 2003, Inf. Fusion.

[35]  Fredrik Gustafsson,et al.  Storage efficient particle filters for the out of sequence measurement problem , 2008, 2008 11th International Conference on Information Fusion.

[36]  Quanbo Ge,et al.  Multisensor Estimation Fusion for Wireless Networks with Mixed Data Delays , 2010, 2010 2nd International Workshop on Database Technology and Applications.

[37]  Spilios D. Fassois,et al.  Aircraft Virtual Sensor Design Via a Time-Dependent Functional Pooling NARX Methodology , 2013 .

[38]  Shuo Zhang,et al.  Particle filter processing of out-of-sequence measurements: Exact Bayesian solution , 2011, 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[39]  Gordon Lightbody,et al.  Power system harmonic analysis using the Kalman filter , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[40]  Sanggil Kang,et al.  A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks , 2010, Sensors.

[41]  Youda Liu,et al.  Pure harmonics extracting from time-varying power signal based on improved empirical mode decomposition , 2014 .

[42]  Ulrich Hofmann,et al.  Timestamping and latency analysis for multi-sensor perception systems , 2013, 2013 IEEE SENSORS.

[43]  Kyoung Kwan Ahn,et al.  Hybrid control of a pneumatic artificial muscle (PAM) robot arm using an inverse NARX fuzzy model , 2011, Eng. Appl. Artif. Intell..

[44]  Y. Bar-Shalom,et al.  A two-step method for out-of-sequence measurements , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[45]  Taek Lyul Song,et al.  Out-of-sequence measurements update using the information filter with reduced data storage , 2014, 2014 Sensor Data Fusion: Trends, Solutions, Applications (SDF).

[46]  Y. Bar-Shalom,et al.  Out-of-Sequence Measurement Processing for Particle Filter: Exact Bayesian Solution , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[47]  Karl-Erik Årzén,et al.  Rao–Blackwellized Particle Filters With Out-of-Sequence Measurement Processing , 2014, IEEE Transactions on Signal Processing.

[48]  Wei Xing Zheng,et al.  Identification of a Class of Nonlinear Autoregressive Models With Exogenous Inputs Based on Kernel Machines , 2011, IEEE Transactions on Signal Processing.