Due to the significant volatility of Broadband over Power Lines (BPL) networks regarding their circuital and topological characteristics, channel statistical modeling recently gains special attention from the BPL communications engineers. Among the recently presented channel attenuation statistical models, initial statistical hybrid model (iSHM) and modified statistical hybrid model (mSHM) have been theoretically defined and applied to overhead medium voltage (OV MV), underground medium voltage (UN MV) and overhead high voltage (OV HV) BPL networks so far. Apart from the iSHM and mSHM definition and application, the theory of the definition procedure of new virtual distribution and transmission BPL topologies, which describes the phases tow...
Business analytics and IT infrastructure preserve the integrity of the smart grid (SG) operation aga...
This paper assesses the performance of the main line fault localization methodology (MLFLM) when its...
This second paper assesses the performance of piecewise monotonic data approximations, such as L1PMA...
In [1], the theoretical framework for the interoperability of DHM, iSHM, mSHM, the definition proced...
In [1], [2], the theoretical framework and the numerical results concerning the class mapping of ove...
On the basis of the initial Statistical Hybrid Model (iSHM), the iSHM class maps, which are 2D conto...
With reference to the initial statistical hybrid model (iSHM) and modified statistical hybrid model ...
This first paper considers the identification of the structure of overhead high-voltage broadband ov...
This paper investigates the possibility of detecting the hook style energy theft in the overhead low...
Until now, the neural network identification methodology for the branch number identification (NNIM-...
Based on the techno-economic pedagogical (TEP) method proposed in [1] that is suitable for designing...
This companion paper of [1] focuses on the prediction of various faults and instabilities that may o...
Due to the smart grid (SG) operation, the power utilities are dealing with a cataclysm of big data t...
This paper investigates the possibility of detecting the hook style energy theft in the overhead low...
Until now, the neural network identification methodology for the branch number identification (NNIM-...
Business analytics and IT infrastructure preserve the integrity of the smart grid (SG) operation aga...
This paper assesses the performance of the main line fault localization methodology (MLFLM) when its...
This second paper assesses the performance of piecewise monotonic data approximations, such as L1PMA...
In [1], the theoretical framework for the interoperability of DHM, iSHM, mSHM, the definition proced...
In [1], [2], the theoretical framework and the numerical results concerning the class mapping of ove...
On the basis of the initial Statistical Hybrid Model (iSHM), the iSHM class maps, which are 2D conto...
With reference to the initial statistical hybrid model (iSHM) and modified statistical hybrid model ...
This first paper considers the identification of the structure of overhead high-voltage broadband ov...
This paper investigates the possibility of detecting the hook style energy theft in the overhead low...
Until now, the neural network identification methodology for the branch number identification (NNIM-...
Based on the techno-economic pedagogical (TEP) method proposed in [1] that is suitable for designing...
This companion paper of [1] focuses on the prediction of various faults and instabilities that may o...
Due to the smart grid (SG) operation, the power utilities are dealing with a cataclysm of big data t...
This paper investigates the possibility of detecting the hook style energy theft in the overhead low...
Until now, the neural network identification methodology for the branch number identification (NNIM-...
Business analytics and IT infrastructure preserve the integrity of the smart grid (SG) operation aga...
This paper assesses the performance of the main line fault localization methodology (MLFLM) when its...
This second paper assesses the performance of piecewise monotonic data approximations, such as L1PMA...