scholarly journals An Alternative Proposal for Quantification of Technical Losses Using a Reduced Equivalent Circuit

2021 ◽  
Author(s):  
Victor Do Prado Brasil ◽  
Pedro Augusto ◽  
Anésio De Leles Ferreira Filho ◽  
Jorge Cormane ◽  
Lelio Ribeiro Soares Junior ◽  
...  
Keyword(s):  
Time Series ◽  
Planning Process ◽  
Electrical Grid ◽  
Reduction Techniques ◽  
Speed Up ◽  
Indirect Evaluation ◽  
Time Series Simulation ◽  
Definition Of ◽  
Real Time Simulations ◽  
Electricity Tariff

Electrical grid technical losses affects the electricity tariff and the planning of new lines. Nonetheless, their assessment by means of time-series or real-time simulations is computationally burdensome for large grids. In order to achieve simplified equivalent circuits, reduction techniques have been developed. The only one that is applicable for unbalanced grids is the multiphase reduction, but it does not preserve the losses. This paper proposes an algorithm that allows indirect evaluation of total losses, thus extending the multiphase reduction technique. In the validation process, IEEE 34-bus and a Brazilian real feeder are evaluated. A daily time-series simulation, with hourly loadshapes, is performed in OpenDSS. Using this novel method, the losses errors obtained are lower than 2%. The proposed algorithm, therefore, may be applied to speed up the definition of electricity tariff and the planning process of unbalanced grids.

scholarly journals Robust Output Synchronization of Arrays of Chaotic Sprott Circuits

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Ernesto V. Gonzalez Solis ◽  
David I. Rosas Almeida
Keyword(s):  
Parametric Uncertainties ◽  
Electronic Components ◽  
Closed Loop System ◽  
Pass Filter ◽  
Low Pass Filter ◽  
State Variable ◽  
Output Synchronization ◽  
Low Pass ◽  
Definition Of ◽  
Real Time Simulations

This article presents a technique for synchronizing arrays of a class of chaotic systems known as Sprott circuits. This technique can be applied to different topologies and is robust to parametric uncertainties caused by tolerances in the electronic components. The design of coupling signals is based on the definition of a set of functionals which depend on the errors between the outputs of the nodes and the errors between the output of a reference system and the outputs of the nodes. When there are no parametric uncertainties, we establish a criterion to design the coupling signals using only one state variable of each system. When the parametric uncertainties are present, we add a robust observer and a low pass filter to estimate the perturbation terms, which are subsequently compensated through the coupling signals, resulting in a robust closed loop system. The performance of the synchronization technique is illustrated by real-time simulations.

IDENTIFYING DISTINCT STOCHASTIC DYNAMICS FROM CHAOS: A STUDY ON MULTIMODAL NEURAL FIRING PATTERNS

2009 ◽  
Vol 19 (02) ◽  
pp. 453-485 ◽  
Author(s):  
MINGHAO YANG ◽  
ZHIQIANG LIU ◽  
LI LI ◽  
YULIN XU ◽  
HONGJV LIU ◽  
...  
Keyword(s):  
Time Series ◽  
Limit Cycle ◽  
Stochastic Dynamics ◽  
Nonlinear Time Series ◽  
Special Importance ◽  
Neuronal System ◽  
Neural Firing ◽  
Firing Patterns ◽  
Theoretical Simulation ◽  
Definition Of

Some chaotic and a series of stochastic neural firings are multimodal. Stochastic multimodal firing patterns are of special importance because they indicate a possible utility of noise. A number of previous studies confused the dynamics of chaotic and stochastic multimodal firing patterns. The confusion resulted partly from inappropriate interpretations of estimations of nonlinear time series measures. With deliberately chosen examples the present paper introduces strategies and methods of identification of stochastic firing patterns from chaotic ones. Aided by theoretical simulation we show that the stochastic multimodal firing patterns result from the effects of noise on neuronal systems near to a bifurcation between two simpler attractors, such as a point attractor and a limit cycle attractor or two limit cycle attractors. In contrast, the multimodal chaotic firing trains are generated by the dynamics of a specific strange attractor. Three systems were carefully chosen to elucidate these two mechanisms. An experimental neural pacemaker model and the Chay mathematical model were used to show the stochastic dynamics, while the deterministic Wang model was used to show the deterministic dynamics. The usage and interpretation of nonlinear time series measures were systematically tested by applying them to firing trains generated by the three systems. We successfully identified the distinct differences between stochastic and chaotic multimodal firing patterns and showed the dynamics underlying two categories of stochastic firing patterns. The first category results from the effects of noise on the neuronal system near a Hopf bifurcation. The second category results from the effects of noise on the period-adding bifurcation between two limit cycles. Although direct application of nonlinear measures to interspike interval series of these firing trains misleadingly implies chaotic properties, definition of eigen events based on more appropriate judgments of the underlying dynamics leads to accurate identifications of the stochastic properties.

Efficient Time Series Clustering and Its Application to Social Network Mining

2014 ◽  
Vol 23 (2) ◽  
pp. 213-229 ◽  
Author(s):  
Cangqi Zhou ◽  
Qianchuan Zhao
Keyword(s):  
Time Series ◽  
Social Network ◽  
Information Diffusion ◽  
Time Series Data ◽  
Online Social Network ◽  
Dissimilarity Measure ◽  
Series Data ◽  
Formation Mechanisms ◽  
Network Analyses ◽  
Definition Of

AbstractMining time series data is of great significance in various areas. To efficiently find representative patterns in these data, this article focuses on the definition of a valid dissimilarity measure and the acceleration of partitioning clustering, a common group of techniques used to discover typical shapes of time series. Dissimilarity measure is a crucial component in clustering. It is required, by some particular applications, to be invariant to specific transformations. The rationale for using the angle between two time series to define a dissimilarity is analyzed. Moreover, our proposed measure satisfies the triangle inequality with specific restrictions. This property can be employed to accelerate clustering. An integrated algorithm is proposed. The experiments show that angle-based dissimilarity captures the essence of time series patterns that are invariant to amplitude scaling. In addition, the accelerated algorithm outperforms the standard one as redundancies are pruned. Our approach has been applied to discover typical patterns of information diffusion in an online social network. Analyses revealed the formation mechanisms of different patterns.

scholarly journals Comparison of Quantitative PCR (qPCR) Paenibacillus larvae Targeted Assays and Definition of Optimal Conditions for Its Detection/Quantification in Honey and Hive Debris

2018 ◽  
Author(s):  
Franca Rossi ◽  
Carmela Amadoro ◽  
Addolorato Ruberto ◽  
Luciano Ricchiuti
Keyword(s):  
Quantitative Pcr ◽  
Clinical Symptoms ◽  
Sequence Data ◽  
Standard Procedure ◽  
Paenibacillus Larvae ◽  
Optimal Conditions ◽  
Target Species ◽  
Speed Up ◽  
Definition Of ◽  
Culture Dependent

The application of quantitative PCR (qPCR) as a routine method to detect and enumerate Paenibacillus larvae in honey and hive debris could greatly speed up the estimation of prevalence and outbreak risk of the American foulbrood (AFB) disease of Apis mellifera. However, none of the qPCR tests described so far has been officially proposed as a standard procedure for P. larvae detection and enumeration for surveillance purposes. Therefore, in this study inclusivity, exclusivity and sensitivity in detection of P. larvae spores directly in samples of honey and hive debris were re-evaluated for the previously published qPCR methods. To this aim recently acquired P. larvae sequence data were considered to assess inclusivity in silico and more appropriate non-target species were used to verify exclusivity experimentally. This led to the modification of one of the previously described methods resulting in a new test capable to allow the detection of P. larvae spores in honey and hive debris down to 1 CFU/g. The application of the qPCR test optimized in this study can allow to reliably detect and quantify P. larvae in honey and hive debris, thus circumventing the disadvantages of late AFB diagnosis based on clinical symptoms and possible underestimation of spore numbers that is the main drawback of culture-dependent procedures.

scholarly journals Time series simulation in a sloping bottom environment using ray theory

1986 ◽  
Vol 80 (S1) ◽  
pp. S53-S53
Author(s):  
Evan K. Westwood ◽  
H. Hobaek ◽  
C. T. Tindle
Keyword(s):  
Time Series ◽  
Ray Theory ◽  
Time Series Simulation ◽  
Sloping Bottom

scholarly journals Determination of the Starting Point in Time Series for Trend Detection Based on Overlapping Trend

2016 ◽  
Vol 16 (6) ◽  
pp. 98-110
Author(s):  
Gao Xuedong ◽  
Gu Kan
Keyword(s):  
Time Series ◽  
Piecewise Linear ◽  
Negative Influence ◽  
Trend Detection ◽  
Computational Accuracy ◽  
Starting Point ◽  
Time Series Studies ◽  
Definition Of ◽  
Stage Characteristic

Abstract The traditional time series studies consider the time series as a whole while carrying on the trend detection; therefore not enough attention is paid to the stage characteristic. On the other hand, the piecewise linear fitting type methods for trend detection are lacking consideration of the possibility that the same node belongs to multiple trends. The above two methods are affected by the start position of the sequence. In this paper, the concept of overlapping trend is proposed, and the definition of milestone nodes is given on its base; these way not only the recognition of overlapping trend is realized, but also the negative influence of the starting point of sequence is effectively reduced. The experimental results show that the computational accuracy is not affected by the improved algorithm and the time cost is greatly reduced when dealing with the processing tasks on dynamic growing data sequence.

Time Series Simulations of Wide-Band Spectra for Fatigue Tests of Offshore Structures

1984 ◽  
Vol 106 (4) ◽  
pp. 466-470 ◽  
Author(s):  
N. K. Lin ◽  
W. H. Hartt
Keyword(s):  
Time Series ◽  
Fatigue Testing ◽  
Wide Band ◽  
Simulation Method ◽  
Offshore Structures ◽  
Fatigue Tests ◽  
Time Series Model ◽  
Long Time ◽  
Band Spectra ◽  
Time Series Simulation

A time-series simulation method, based on the principle of time series modeling for dynamic systems, is used to reproduce a wide-band stress history from a prescribed stress spectral model for fatigue testing of offshore structures. The optimization procedures and stability of the time series model for the prescribed spectrum are presented and discussed. The optimization procedures are developed on the basis of the Levison-Durbin algorithm, which usually produces a stable time series model if the order of the time series model is even. An example is presented to demonstrate the applicability of the proposed method to long-time, high-cycle fatigue testing.

DEVELOPMENT OF MODELS FOR DIAGNOSTIC DIABETES BASED ON FUZZY LOGIC METODS

2021 ◽  
pp. 90-95
Author(s):  
Евгений Николаевич Коровин ◽  
Екатерина Ивановна Новикова ◽  
Олег Валерьевич Родионов
Keyword(s):  
Mathematical Modeling ◽  
Decision Making ◽  
Information Technology ◽  
Fuzzy Logic ◽  
Human Body ◽  
Patient Information ◽  
Decision Making Process ◽  
Speed Up ◽  
Definition Of

В статье рассматриваются разработки методов интеллектуальной поддержки процесса диагностики сахарного диабета, а также определение его типа. В последние годы количество людей, страдающих данным заболеванием, неуклонно растет, а без своевременной диагностики эта патология может нанести огромный вред организму человека. Сахарный диабет 1 типа опасен тем, что в основном возникает у людей молодого возраста. Оперативное обнаружение диабета, а также определение его типа, поможет не только избежать возможных осложнений, но и в некоторых случаях предотвратить смерть пациента. Информационные технологии все чаще используются в различных сферах деятельности для разработки новых или совершенствования существующих методов обработки данных, особенно это можно заметить в сфере медицины. В настоящее время врач самостоятельно ставит диагноз, основываясь на результатах различных анализов, однако, для ускорения процесса принятия решения, можно воспользоваться методами математического моделирования, а именно: моделями диагностики диабета на основе нечеткой логики. Для наибольшего удобства данный способ распознавания заболевания впоследствии можно реализовать в информационно-программное обеспечение, которое сможет еще больше увеличить эффективность и скорость распознавания патологии The article discusses the issues of the incidence of diabetes in the population, in particular, the definition of its type. In recent years, the number of people suffering from this disease has been steadily growing, and without timely diagnosis, this pathology can cause enormous harm to the human body. Prompt detection of diabetes, as well as determination of its type, will help not only avoid possible complications, but also in some cases prevent the death of the patient. Information technology is increasingly being used in various fields of activity to develop new or improve existing methods of data processing, especially in the field of medicine. Currently, the doctor independently makes a diagnosis based on the results of various analyzes, however, to speed up the decision-making process, you can use the methods of mathematical modeling, namely, models of diabetes diagnostics based on fuzzy logic. For the greatest convenience, this method of disease recognition can subsequently be implemented in information software, which can further increase the efficiency and speed of pathology recognition

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