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OverviewThis book consists of the identification, characterization, and modeling of electromagnetic interferences in substations for the deployment of wireless sensor networks. The authors present in chapter 3 the measurement setup to record sequences of impulsive noise samples in the ISM band of interest. The setup can measure substation impulsive noise, in wide band, with enough samples per time window and enough precision to allow a statistical study of the noise. During the measurement campaign, the authors recorded around 120 noise sequences in different substations and for four ranges of equipment voltage, which are 25 kV, 230 kV, 315 kV and 735 kV. A characterization process is proposed, by which physical characteristics of partial discharge can be measured in terms of first- and second-order statistics. From the measurement campaign, the authors infer the characteristics of substation impulsive noise as a function of the substation equipment voltage, and can provide representative parameters for the four voltage ranges and for several existing impulsive noise models. The authors investigate in chapters 4 and 5 the modeling of electromagnetic interferences caused by partial discharge sources. First, the authors propose a complete and coherent approach model that links physical characteristics of high-voltage installations to the induced radio-interference spectra of partial discharge sources. The goodness-of-fit of the proposed physical model has been measured based on some interesting statistical metrics. This allows one to assess the effectiveness of the authors' approach in terms of first- and second-order statistics. Chapter 6 proposes a model based on statistical approach. Indeed, substation impulsive noise is composed of correlated impulses, which would require models with memory in order to replicate a similar correlation. Among different models, we have configured a Partitioned Markov Chain (PMC) with 19 states (one state for the background noise and18 states for the impulse); this Markov-Gaussian model is able to generate impulsive noise with correlated impulse samples. The correlation is observable on the impulse duration and the power spectrum of the impulses. Our PMC model provides characteristics that are more similar to the characteristics of substation impulsive noise in comparison with other models, in terms of time and frequency response, as well as Probability Density Functions (PDF). Although PMC represents reliably substation impulsive noise, the model remains complex in terms of parameter estimation due to a large number of Markov states, which can be an obstacle for future wireless system design. In order to simplify the model, the authors decrease the number of states to 7 by assigning one state to the background noise and 6 states to the impulse and we call this model PMC-6. PMC-6 can generate realistic impulses and can be easily implemented in a receiver in order to mitigate substation impulsive noise. Representative parameters are provided in order to replicate substation impulsive noise for different voltage ranges (25-735 kV). Chapter 7, a generalized radio-noise model for substations is proposed, in which there are many discharges sources that are randomly distributed over space and time according to the Poisson field of interferers approach. This allows for the identification of some interesting statistical properties of moments, cumulants and probability distributions. These can, in turn, be utilized in signal processing algorithms for rapid partial discharge's identification, localization, and impulsive noise mitigation techniques in wireless communications in substations. The primary audience for this book is the electrical and power engineering industry, electricity providers and companies who are interested in substation automation systems using wireless communication technologies for smart grid applications. Researchers, engineers and students studying and workingin wireless communication will also want to buy this book as a reference. Full Product DetailsAuthor: Basile L. Agba , Fabien Sacuto , Minh Au , Fabrice LabeauPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG Edition: Softcover reprint of the original 1st ed. 2019 Dimensions: Width: 15.50cm , Height: 1.10cm , Length: 23.50cm Weight: 0.454kg ISBN: 9783030082260ISBN 10: 3030082261 Pages: 187 Publication Date: 20 December 2018 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of Contents1. Introduction 1.1. Motivation 1.2. Monograph organization 1.3. Contributions 2. State of art: Characterization and modeling of EMI and Wireless communications in power substations 2.1. Concept of EMI and classification 2.1.1. Definition of EMI sources 2.1.2. Natural noise sources 2.1.3. Man-made noise sources 2.2. The electromagnetic interferences in substations 2.2.1. Functions of power substations 2.2.2. Pieces of equipment and electrical operations · Corona effect · Partial discharges · Early impulsive noise measurements 2.2.3. Ionization process and electrical discharge in gases 2.2.4. Partial discharges mechanisms 2.2.5. Measurement and characterization of partial discharge sources 2.2.6. Partial discharge modeling 2.3. Characterization of impulsive noise models 2.3.1. A statistical characterization of impulsive noise 2.3.2. Impulsive noise models 2.3.3. Existing statistical models of impulsive noise 2.4. Wireless communications in substations 2.4.1. Communications channels in presence of impulsive noise 2.4.2. Wireless technologies 2.4.3. Existing systems for wireless communications in high voltage environment 2.5. Summary 3. Impulsive noise measurements 3.1. Objectives of the measurement campaign 3.2. Measurement setup 3.2.1. Design of the setup 3.2.2. Tests in laboratory 3.2.3. Impulse detection method 3.3. Measurements in Substation 1 3.3.1. Substation presentation 3.3.2. Locations of the antenna 3.3.3. Results 3.4. Measurements in Substation 2 3.4.1. Substation presentation 3.4.2. Locations of the antenna 3.4.3. Results 3.5. Classification of impulsive noise characteristics 3.5.1. Amplitude 3.5.2. Impulse duration 3.5.3. Repetition rate 3.5.4. Sample value 3.6. An experimental characterization of the discharge sources 3.6.1. Signal processing tools for impulsive noise measurement 3.6.2. Definition of characterization metrics 3.6.3. Characterization based on first-order statistics (First order-statistics) 3.6.4. Characterization based on second-order statistics (Waveforms and second-order statistics) 3.7. Representative parameters for classic impulsive noise models 3.7.1. Two-state Markov Chain (MC2) 3.7.2. Middleton class-A (MCA) 3.8. Conclusion 4. A physical model of EMI induced by a partial discharge source 4.1. Introduction 4.2. Partial discharge phenomenon and its mechanism 4.3. The physical model of partial discharge source 4.3.1. Electric field stress 4.3.2. Discharge process 4.3.3. Current and charge density 4.4. The electromagnetic radiation of the interference source induced by partial discharges 4.4.1. Electric dipole formulation 4.4.2. Power radiation of the interference source received at the antenna 4.4.3. Modeling impulsive waveforms and PSD 4.4.4. Brief summary of interference induced by partial discharge sources 4.5. Experimental validation 4.5.1. Brief description of the measurement setup 4.5.2. Simulation setup 4.5.3. Simulation-measurement comparison 4.6. Conclusion 5. Analysis and modeling of wideband RF impulsive signals induced by partial discharges using second-order statistics 5.1. Introduction 5.2. Measurement setup 5.3. Conjectures and mathematical formulation of EM waves 5.3.1. Second-order statistics 5.3.2. A Physical interpretation 5.4. The proposed model 5.4.1. Theory of filters and relationship with time series models 5.4.2. Definition of time series model 5.4.3. Tests for unit roots 5.4.4. Estimation and selection 5.5. The goodness-of-fit 5.5.1. Analysis of the residuals 5.5.2. Tests for residuals 5.5.3. Tests for heteroscedasticity 5.5.4. Analysis of residuals of the improved models 5.5.5. Summary 5.6. Simulation and results 5.6.1. Simulation parameters 5.6.2. A comparison of measurements vs. simulation results 5.6.3. Analysis of simulated impulsive waveforms 5.6.4. Advantages and limitations of the proposed model 5.7. Conclusion 6. Wideband statistical model for substation impulsive noise 6.1. Introduction to PMC model 6.2. Impulsive system and oscillations 6.3. Damping effect 6.4. Transition matrix 6.5. Parameter estimation 6.5.1. Fuzzy C-means algorithm 6.6. Results 6.6.1. Divergence between measurements and models 6.6.2. Spectrum analysis 6.7. Representative parameters for PMC model in wide band 6.8. Conclusions 7. A statistical analysis of impulsive noise in a Poisson field of interferers in substation environments and an application to a rapid identification of PD sources 7.1. Introduction 7.2. A mathematical formulation of multiple PD interference sources 7.2.1. EM radiation of multiple PD sources 7.2.2. Propagation of EM waves induced by PD sources 7.2.3. Spatial and temporal distribution of PD sources 7.3. Statistical analysis 7.3.1. Probability density function of instantaneous amplitude 7.3.2. Amplitude probability distribution 7.3.3. Tails and moments 7.3.4. A summary of important findings 7.4. Experimentation and simulation results 7.4.1. Measurements in substations 7.4.2. A procedure for estimation 7.4.3. A comparison Measurement and simulation results 7.5. A rapid identification of PD sources using blind source separation 7.5.1. Motivation and contribution 7.5.2. System model 7.5.3. Blind source separation via generalized eigenvalue decomposition 7.5.4. Simulation and results 7.6. Conclusion 8. Conclusions and recommendationsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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