Non-technical losses(NTL)of electric power are a serious problem for electric distribution *** solution determines the cost,stability,reliability,and quality of the supplied *** widespread use of advanced metering inf...
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Non-technical losses(NTL)of electric power are a serious problem for electric distribution *** solution determines the cost,stability,reliability,and quality of the supplied *** widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity *** the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption *** model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural *** best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test *** a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL *** use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.
In this work, software is developed for modeling the drying process of hygroscopic materials using cellular automata. The modeling process using cellular automata is described, and the developed transition rules that ...
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ISBN:
(数字)9798331542634
ISBN:
(纸本)9798331542641
In this work, software is developed for modeling the drying process of hygroscopic materials using cellular automata. The modeling process using cellular automata is described, and the developed transition rules that consider heat and mass transfer not only within the material but also between stacks are provided. The developed software uses a modern multi-tier client-server architecture, including a database for handling large volumes of computational data. Additionally, the results of the modeling, including their validation based on existing experimental data, are presented and analyzed.
Problems of research of underground gas storage (UGS) wells are given. The analysis of the results of well research is carried out and the constant variability of filtration resistance coefficients of bottomhole zones...
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Problems of research of underground gas storage (UGS) wells are given. The analysis of the results of well research is carried out and the constant variability of filtration resistance coefficients of bottomhole zones...
Problems of research of underground gas storage (UGS) wells are given. The analysis of the results of well research is carried out and the constant variability of filtration resistance coefficients of bottomhole zones of wells is substantiated. Studies of the influence of bottomhole pressures of wells on the calculated pressure at gas gathering stations (GGS) of underground storage facilities have been carried out. It was found that the calculated filtration resistance coefficients do not allow to calculate the pressures at the gas gathering stations of the underground storage plant with sufficient accuracy. The magnitude of the discrepancy between the measured and calculated pressures on the GGS varies depending on the flow rate and operating time of wells. It is established that the calculation of depression (repression) of pressure in the bottomhole zones of wells in non-stationary conditions of their operation gives underestimated results.
The article analyzes the concept of process control at an industrial enterprise, ensuring the functional stability of technological processes. A novelty of the proposed model is the use of pseudo- inversion tools as a...
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作者：
Suresh KalyanasundaramEdwin K. P. ChongNess B. ShroffMotorola India Electronics Limited
No. 66/1 Plot 5 Bagmane Techpark C. V. Raman Nagar Post Bangalore 560 093 India. Department of Electrical and Computer Engineering
Colorado State University Fort Collins CO 80523-1373 USA. Professor Edwin K. P. Chong received the B.E.(Hons.) degree with First Class Honors from the University of Adelaide
South Australia in 1987 graduating top of his class and the M.A. and Ph.D. degrees in 1989 and 1991
respectively both from Princeton University where he held an IBM Fellowship. He joined the School of Electrical and Computer Engineering at Purdue University in 1991 where he was named a University Faculty Scholar in 1999 and promoted to Full Professor in 2001. Since August 2001 he has been a Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University. His current interests are in communication networks and optimization methods. He coauthored the best-selling book An Introduction to Optimization 2nd Edition Wiley-Interscience 2001. He received the NSF CAREER Award in 1995 and the ASEE Frederick Emmons Terman Award in 1998. He coauthored a paper that was awarded Best Paper in the journal Computer Networks 2003. Professor Chong is a Fellow of the IEEE. He was founding chairman of the IEEE Control Systems Society Technical Committee on Discrete Event Systems and until recently served as an IEEE Control Systems Society Distinguished Lecturer. He has been on the editorial board of the IEEE Transactions on Automatic Control. He is currently on the editorial board of the journal Computer Networks. He has also served on the organizing committees of several international conferences. He has been on the program committees for the IEEE Conference on Decision and Control the American Control Conference the IEEE International Symposium on Intelligent Control IEEE Symposium on Computers and Communications and the IEEE Global Telecommunications Conference. He has also served in the executive committees for the IEEE Co
Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain tran...
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Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per-unit-time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max-min optimal policy, which maximizes the worst-case average per-unit-time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time-varying transition rates.
We propose a level set method-based framework for the conceptual design of compliant *** this method,the compliant mechanism design problem is recast as an infinite dimensional optimization problem,where the design va...
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We propose a level set method-based framework for the conceptual design of compliant *** this method,the compliant mechanism design problem is recast as an infinite dimensional optimization problem,where the design variable is the geometric shape of the compliant mechanism and the goal is to find a suitable shape in the admissible design space so that the objective functional can reach a *** geometric shape of the compliant mechanism is represented as the zero level set of a one-higher dimensional level set function,and the dynamic variations of the shape are governed by the Hamilton-Jacobi partial differential *** application of level set methods endows the optimization process with the particular quality that topological changes of the boundary,such as merging or splitting,can be handled in a natural *** making a connection between the velocity field in the Hamilton-Jacobi partial differential equation with the shape gradient of the objective functional,we go further to transform the optimization problem into that of finding a steady-state solution of the partial differential *** the above-mentioned methodological issues,some numerical examples together with prototypes are presented to validate the performance of the method.
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