Power Systems Stability through Piecewise Monotonic Data Approximations – Part 2: Adaptive Number of Monotonic Sections and Performance of L1PMA, L2WPMA, and L2CXCV in Overhead Medium-Voltage Broadband over Power Lines Networks

This second paper investigates the role of the number of monotonic sections during the mitigation of measurement differences in overhead medium-voltage broadband over power lines (OV MV BPL) transfer functions. The performance of two well-known piecewise monotonic data approximations that are based on the number of monotonic sections (i.e., L1PMA and L2WPMA) is assessed in comparison with the occurred measurement differences and L2CXCV, which is a piecewise monotonic data approximation without considering monotonic sections.The contribution of this paper is double. First, further examination regarding the definition of the optimal number of monotonic section is made so that the accuracy of L1PMA can be significantly enhanced. In fact, the goal is to render piecewise monotonic data approximations that are based on the optimal number of monotonic sections as the leading approximation against the other ones without monotonic sections. Second, a generic framework concerning the definition of an adaptive number of monotonic sections is proposed for given OV MV BPL topology.Citation: Lazaropoulos, A. G. (2017). Power Systems Stability through Piecewise Monotonic Data Approximations – Part 2: Adaptive Number of Monotonic Sections and Performance of L1PMA, L2WPMA, and L2CXCV in Overhead Medium-Voltage Broadband over Power Lines Networks. Trends in Renewable Energy, 3(1), 33-60. DOI: 10.17737/tre.2017.3.1.003

Main Line Fault Localization Methodology in Smart Grid – Part 3: Main Line Fault Localization Methodology (MLFLM)

Since the main distribution line faults can be securely identified as outlined in the first and second paper, this third paper presents the methodology of localizing the main distribution line fault when broadband over power lines (BPL) networks have already been deployed across the distribution power grids. The main issue of this paper is the detailed presentation of the main line localization methodology (MLFLM) as well as well as its performance assessment when measurement differences occur.The contribution of this paper, which is focused on the application of MLFLM, is double. First, the procedure, which is followed in order to create the database of faults and is used by MLFLM, is here analytically presented. This database is based on the application of the main distribution line fault identification percentage metric (MDLFI) to coupling reflection coefficients of all possible fault OV MV BPL topologies (modified OV MV BPL topologies). Second, the performance assessment of MLFLM is investigated with respect to the nature of the measurement differences and the location of main distribution line faults across the distribution power grid

Main Line Fault Localization Methodology in Smart Grid – Part 1: Extended TM2 Method for the Overhead Medium-Voltage Broadband over Power Lines Networks Case

These three papers cover the overall methodology for the identification and localization of faults that occur in main transmission and distribution lines when broadband over power lines (BPL) networks are deployed across the transmission and distribution power grids, respectively. In fact, this fault case is the only one that cannot be handled by the combined operation of Topology Identification Methodology (TIM) and Instability Identification Methodology (FIIM). After the phase of identification of main distribution line faults, which is presented in this paper, the main line fault localization methodology (MLFLM) is applied in order to localize the faults in overhead medium-voltage BPL (OV MV BPL) networks.The main contribution of this paper, which is focused on the identification of the main distribution line faults, is the presentation of TM2 method extension through the adoption of coupling reflection coefficients. Extended TM2 method is analyzed in order to identify a main distribution line fault regardless of its nature (i.e., short- or open-circuit termination). The behavior of the extended TM2 method is assessed in terms of the main line fault nature and, then, its results are compared against the respective ones during the normal operation, which are given by the original TM2 method, when different main distribution line fault scenarios occur. Extended TM2 method acts as the introductory phase (fault identification) of MLFLM

Measurement Differences, Faults and Instabilities in Intelligent Energy Systems – Part 2: Fault and Instability Prediction in Overhead High-Voltage Broadband over Power Lines Networks by Applying Fault and Instability Identification Methodology (FIIM)

This companion paper of [1] focuses on the prediction of various faults and instabilities that may occur during the operation of the transmission power grid when overhead high-voltage broadband over power lines (OV HV BPL) networks are deployed across it. Having already been identified the theoretical OV HV BPL transfer function for a given OV HV BPL network [1], the faults and instabilities of the transmission power grid are first differentiated from the measurement differences, which can occur during the determination of an OV HV BPL transfer function, and, then, are identified by applying the best L1 Piecewise Monotonic data Approximation (best L1PMA) to the measured OV HV BPL transfer function. When faults and instabilities are detected, a warning is issued.The contribution of this paper is triple. First, the Topology Identification Methodology (TIM) of [1] is here extended to the proposed Fault and Instability Identification Methodology (FIIM) so that faults and instabilities across the transmission power grid can be identified. Also, the curve similarity performance percentage metric (CSPpM) that acts as the accompanying performance metric of FIIM is introduced. Second, the impact of various fault and instability conditions on the OV HV BPL transfer functions is demonstrated. Third, the fault and instability prediction procedure by applying the FIIM is first reported.Citation: Lazaropoulos, A. G. (2016). Measurement Differences, Faults and Instabilities in Intelligent Energy Systems – Part 2: Fault and Instability Prediction in Overhead High-Voltage Broadband over Power Lines Networks by Applying Fault and Instability Identification Methodology (FIIM). Trends in Renewable Energy, 2(3), 113-142. DOI: 10.17737/tre.2016.2.3.002

Virtual Indicative Broadband over Power Lines Topologies for Respective Subclasses by Adjusting Channel Attenuation Statistical Distribution Parameters of Statistical Hybrid Models (Class Maps) – Part 3: The Case of Overhead Transmission Power Grids

In [1], [2], the theoretical framework and the numerical results concerning the class mapping of overhead and underground medium voltage broadband over power lines (OV and UN MV BPL) topologies have been presented on the basis of the recently proposed initial statistical hybrid model (iSHM), modified statistical hybrid model (mSHM) and class map definition procedure. In this paper, all the recent findings regarding the statistical channel modeling and class mapping are first applied to transmission BPL networks; say, OV high voltage (HV) BPL topologies. The numerical results of OV HV BPL networks are compared against the respective ones of OV and UN distribution networks revealing significant similarities and differences. Finally, the impact of considering minimum or maximum capacity value instead of the average one during the definition procedure is investigated as well as the behavior of the total simulation time of class mapping.Citation: Lazaropoulos, A. G. (2019). Virtual Indicative Broadband over Power Lines Topologies for Respective Subclasses by Adjusting Channel Attenuation Statistical Distribution Parameters of Statistical Hybrid Models (Class Maps) – Part 3: The Case of Overhead Transmission Power Grids. Trends in Renewable Energy, 5, 282-306. DOI: 10.17737/tre.2019.5.3.0010

Smart Energy and Spectral Efficiency (SE) of Distribution Broadband over Power Lines (BPL) Networks – Part 2: L1PMA, L2WPMA and L2CXCV for SE against Measurement Differences in Overhead Medium-Voltage BPL Networks

This second paper assesses the performance of piecewise monotonic data approximations, such as L1PMA, L2WPMA and L2CXCV, against the measurement differences during the spectral efficiency (SE) calculations in overhead medium-voltage broadband over power lines (OV MV BPL) networks. In this case study paper, the performance of the aforementioned three already known piecewise monotonic data approximations, which are considered as countermeasure techniques against measurement differences, is here extended during the SE computations. The indicative BPL topologies of the first paper are again considered while the 3-30 MHz frequency band of the BPL operation is assumed.Citation: Lazaropoulos, A. G. (2018). Smart Energy and Spectral Efficiency (SE) of Distribution Broadband over Power Lines (BPL) Networks – Part 2: L1PMA, L2WPMA and L2CXCV for SE against Measurement Differences in Overhead Medium-Voltage BPL Networks. Trends in Renewable Energy, 4, 185-212. DOI: 10.17737/tre.2018.4.2.007

Main Line Fault Localization Methodology in Smart Grid – Part 2: Extended TM2 Method, Measurement Differences and L1 Piecewise Monotonic Data Approximation for the Overhead Medium-Voltage Broadband over Power Lines Networks Case

Enriching the fault identification methodology of the first paper, this second paper investigates the performance of the identification of main distribution line faults when broadband over power lines (BPL) networks are deployed. The main issue that is concerned in this paper is the impact of measurement differences on the fault identification process performance.The main contribution of this paper, which is focused on the identification of the main distribution line faults when measurement differences occur, is the application of the L1 piecewise monotonic data approximation (l1PMA) in order to cope with the measurement differences that influence the reflection coefficients derived from the extended TM2 method. Through the L1PMA application, measurement differences are confronted in order to prevent the trigger of a false alarm about the existence of a main distribution line fault. The combined operation of the extended TM2 method and L1PMA concludes the introductory phase (fault identification) of the main line fault localization methodology (MLFLM)

Virtual Indicative Broadband over Power Lines Topologies for Respective Subclasses by Adjusting Channel Attenuation Statistical Distribution Parameters of Statistical Hybrid Models (Class Maps) – Part 1: Theory

Based on a set of indicative overhead and underground medium voltage broadband over power lines (OV and UN MV BPL) topologies, initial statistical hybrid model (iSHM) and modified statistical hybrid model (mSHM) are statistical channel models suitable for the distribution BPL networks. Both iSHM and mSHM statistically process channel attenuation and capacity values of assumed indicative OV and UN MV BPL topologies by exploiting channel attenuation statistical distributions (CASDs). iSHM exploits a set of well-known CASDs (i.e., Gaussian, Lognormal, Wald, Weibull and Gumbel CASDs) while mSHM exploits the Empirical CASD. Each indicative OV and UN MV BPL topology acts as the representative one of a respective OV and UN MV BPL topology class (i.e., rural, suburban, urban and aggravated urban class) that consists of a number of respective statistically equivalent OV and UN MV BPL topologies. The contribution of this paper is the theoretical framework presentation of the creation of new virtual indicative OV and UN MV BPL topologies by appropriately adjusting the parameters of iSHM and mSHM CASDs. These new virtual indicative OV and UN MV BPL topologies will enrich the respective today’s OV and UN MV BPL topology classes with respective OV and UN MV BPL topology subclasses while each subclass will be enriched by a number of respective statistically equivalent OV and UN MV BPL topologies. The procedure of defining new virtual distribution BPL topologies by applying iSHM and mSHM will allow a better capacity study of OV and UN MV BPL topology classes. Apart from the definition procedure of the virtual indicative OV MV and UN MV BPL topologies and their respective virtual subclasses by adjusting CASD parameters of iSHM and mSHM, the contribution of this paper is the class map that analytically describes the taxonomy of distribution BPL topology classes and subclasses.Citation: Lazaropoulos, A. G. (2019). Virtual Indicative Broadband over Power Lines Topologies for Respective Subclasses by Adjusting Channel Attenuation Statistical Distribution Parameters of Statistical Hybrid Models (Class Maps) – Part 1: Theory. Trends in Renewable Energy, 5, 237-257. DOI: 10.17737/tre.2019.5.3.009

Capacity Performance of Overhead Transmission Multiple-Input Multiple-Output Broadband over Power Lines Networks: The Insidious Effect of Noise and the Role of Noise Models

Extending the analysis already presented in [1], this paper considers broadband potential of overhead (OV) transmission multiple-input multiple-output (MIMO) broadband over power lines (BPL) networks when different noise conditions occur and different well-proven noise models are adopted.The contribution of this paper is two-fold. First, the broadband potential of a great number of indicative OV high-voltage (HV) BPL topologies and of MIMO transmission schemes is studied in terms of appropriate capacity metrics. The relevant numerical results reveal the significant dependence of ΜΙΜΟ capacity metrics on noise conditions. Second, various well-known BPL noise models from the literature are compared on the basis of their achieved OV HV MIMO BPL capacity. Through the careful study of the capacity results of noise models, it is demonstrated that spectrally flat additive white Gaussian noise (AWGN) may be comfortably assumed as an efficient noise model in transmission MIMO BPL networks. Also in MIMO BPL networks, the comparative capacity analysis of noise models shows small differences among them in the 3-88MHz frequency range.Citation：Lazaropoulos, A. G. (2016). Capacity Performance of Overhead Transmission Multiple-Input Multiple-Output Broadband over Power Lines Networks: The Insidious Effect of Noise and the Role of Noise Models. Trends in Renewable Energy, 2(2), 61-82. DOI: 10.17737/tre.2016.2.2.002

Special Cases during the Detection of the Hook Style Energy Theft in Overhead Low-Voltage Power Grids through HS-DET Method – Part 1: High Measurement Differences, Very Long Hook Technique and “Smart†Hooks

On the basis of [1], this pair of companion papers investigates the possibility of jamming the method of the detection of the hook style energy theft (HS-DET method) that can be used for the detection of the hook style energy theft in the overhead low-voltage (OV LV) power grids. The three main suspicious issues that have been identified in [1] are further investigated in this paper. The robustness of the HS-DET method against these issues is assessed by using percent error sum (PES) submetrics, appropriate contour plots and a new proposed robustness PES submetric against the hook style energy theft of HS-DET method.Citation: Lazaropoulos, A. G. (2019). Special Cases during the Detection of the Hook Style Energy Theft in Overhead Low-Voltage Power Grids through HS-DET Method – Part 1: High Measurement Differences, Very Long Hook Technique and “Smart†Hooks. Trends in Renewable Energy, 5, 60-89. DOI: 10.17737/tre.2019.5.1.008