scholarly journals Adaptive Momentum Neural Learning for Anomaly Detection of Power Distribution and Consumption Load Data

Author(s):  
Yan Liu
2020 ◽  
Vol 14 (01) ◽  
pp. 93-105
Author(s):  
James Obert ◽  
Adrian Chavez

In recent years, the use of security gateways (SG) located within the electrical grid distribution network has become pervasive. SGs in substations and renewable distributed energy resource aggregators (DERAs) protect power distribution control devices from cyber and cyber-physical attacks. When encrypted communications within a DER network is used, TCP/IP packet inspection is restricted to packet header behavioral analysis which in most cases only allows the SG to perform anomaly detection of blocks of time-series data (event windows). Packet header anomaly detection calculates the probability of the presence of a threat within an event window, but fails in such cases where the unreadable encrypted payload contains the attack content. The SG system log (syslog) is a time-series record of behavioral patterns of network users and processes accessing and transferring data through the SG network interfaces. Threatening behavioral pattern in the syslog are measurable using both anomaly detection and graph theory. In this paper, it will be shown that it is possible to efficiently detect the presence of and classify a potential threat within an SG syslog using light-weight anomaly detection and graph theory.


The increase in the reliability, efficiency and security of the electrical grids was credited to the innovation of the smart grid. It is also a fact that the smart grids a very dependable on the digital communication technology that in turn gives rise to undiscovered weaknesses which have to be reconsidered for dependable and coherent power distribution. In this paper, we propose an unsupervised anomaly detection which is mainly focused the statistical correlation among the data. The main aim is to create a scalable anomaly detection system suitable for huge-scale smart grids, which are capable to denote a difference between a real fault from a disruption and an intelligent cyber-attack. We have presented a methodology that applies the concept of attribute extraction by the use of Symbolic Dynamic Filtering (SDF) to decrease compilation drift whilst uncovering usual interactions among subsystems. Results of simulation obtained on IEEE 39, 118 and 2848 bus systems confirm the execution of the method, proposed in this paper, under various working conditions. The results depict a precision of almost 99 percent, along with 98 percent of true positive rate and less than 2 percent of false positive rate.


Author(s):  
L.H. Bolz ◽  
D.H. Reneker

The attack, on the surface of a polymer, by the atomic, molecular and ionic species that are created in a low pressure electrical discharge in a gas is interesting because: 1) significant interior morphological features may be revealed, 2) dielectric breakdown of polymeric insulation on high voltage power distribution lines involves the attack on the polymer of such species created in a corona discharge, 3) adhesive bonds formed between polymer surfaces subjected to such SDecies are much stronger than bonds between untreated surfaces, 4) the chemical modification of the surface creates a reactive surface to which a thin layer of another polymer may be bonded by glow discharge polymerization.


2020 ◽  
pp. 28-33
Author(s):  
A. Yu. Dunaev ◽  
A. S. Baturin ◽  
V. N. Krutikov ◽  
S. P. Morozova

An improved monochromatic radiant source with spectral bandwidth of 4 nm based on supercontinuum laser and a double monochromator was included in absolute cryogenic radiometer-based facility to improve the accuracy of spectral responsivity measurement in the range 0.9–1.6 μm. The developed feedback system ensures stabilization of monochromatic radiant power with standard deviation up to 0.025 %. Radiant power that proceeds detector under test or absolute cryogenic radiometer varies from 0.1 to 1.5 mW in dependence of wavelength. The spectral power distribution of its monochromatic source for various operating mode is presented.


2019 ◽  
Vol 2 (3) ◽  
pp. 141-151
Author(s):  
O. E. Gnezdova ◽  
E. S. Chugunkova

Introduction: greenhouses need microclimate control systems to grow agricultural crops. The method of carbon dioxide injection, which is currently used by agricultural companies, causes particular problems. Co-generation power plants may boost the greenhouse efficiency, as they are capable of producing electric energy, heat and cold, as well as carbon dioxide designated for greenhouse plants.Methods: the co-authors provide their estimates of the future gas/electricity rates growth in the short term; they have made a breakdown of the costs of greenhouse products, and they have also compiled the diagrams describing electricity consumption in case of traditional and non-traditional patterns of power supply; they also provide a power distribution pattern typical for greenhouse businesses, as well as the structure and the principle of operation of a co-generation unit used by a greenhouse facility.Results and discussion: the co-authors highlight the strengths of co-generation units used by greenhouse facilities. They have also identified the biological features of carbon dioxide generation and consumption, and they have listed the consequences of using carbon dioxide to enrich vegetable crops.Conclusion: the co-authors have formulated the expediency of using co-generation power plants as part of power generation facilities that serve greenhouses.


2018 ◽  
Vol 18 (1) ◽  
pp. 20-32 ◽  
Author(s):  
Jong-Min Kim ◽  
Jaiwook Baik

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai

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