scholarly journals Intelligent system for non-technical losses management in residential users of the electricity sector

2018 ◽  
Vol 38 (2) ◽  
pp. 52-60
Author(s):  
Miguel Uparela Cantillo ◽  
Ruben González ◽  
Jamer Jiménez Mares ◽  
Christian Quintero Monroy
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Demand Forecasting ◽  
Electricity Sector ◽  
Caribbean Region ◽  
Self Organizing Maps ◽  
Detection Rates ◽  
Distribution Company

The identification of irregular users is an important assignment in the recovery of energy in the distribution sector. This analysis requires low error levels to minimize non-technical electrical losses in power grid. However, the detection of fraudulent users who have billing does not present a generalized methodology. This issue is complex and varies according to the case study. This paper presents a novel methodology to identify residential fraudulent users by using intelligent systems. The proposed intelligent system consists of three fundamental modules. The first module performs the classification of users with similar power consumption curves using self-organizing maps and genetic algorithms. The second module allows carrying out the monthly electricity demand forecasting through of recursive adjustment of ARIMA models. The third module performs the detection of fraudulent users through an artificial neural network for pattern recognition. For the design and validation of the proposed intelligent system, several tests were performed in each developed module. The database used for the design and evaluation of the modules was constructed with data supplied by the energy distribution company of the Colombian Caribbean Region. The results obtained by the proposed intelligent system show a better performance versus the detection rates obtained by the company.

scholarly journals Intelligent system for non-technical losses management in residential users of the electricity sector

2018 ◽  
Vol 38 (2) ◽  
pp. 52-60 ◽  
Author(s):  
Miguel Uparela Cantillo ◽  
Ruben González ◽  
Jamer Jiménez Mares ◽  
Christian Quintero Monroy
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Demand Forecasting ◽  
Electricity Sector ◽  
Caribbean Region ◽  
Self Organizing Maps ◽  
Detection Rates ◽  
Distribution Company

The identification of irregular users is an important assignment in the recovery of energy in the distribution sector. This analysis requires low error levels to minimize non-technical electrical losses in power grid. However, the detection of fraudulent users who have billing does not present a generalized methodology. This issue is complex and varies according to the case study. This paper presents a novel methodology to identify residential fraudulent users by using intelligent systems. The proposed intelligent system consists of three fundamental modules. The first module performs the classification of users with similar power consumption curves using self-organizing maps and genetic algorithms. The second module allows carrying out the monthly electricity demand forecasting through of recursive adjustment of ARIMA models. The third module performs the detection of fraudulent users through an artificial neural network for pattern recognition. For the design and validation of the proposed intelligent system, several tests were performed in each developed module. The database used for the design and evaluation of the modules was constructed with data supplied by the energy distribution company of the Colombian Caribbean Region. The results obtained by the proposed intelligent system show a better performance versus the detection rates obtained by the company.

scholarly journals Computational Intelligent Approaches for Non-Technical Losses Management of Electricity

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2393
Author(s):  
Rubén González Rodríguez ◽  
Jamer Jiménez Mares ◽  
Christian G. Quintero M.
Keyword(s):  
Intelligent System ◽  
Moving Average ◽  
Demand Forecasting ◽  
Real Data ◽  
Electrical Energy ◽  
Caribbean Region ◽  
Self Organizing Maps ◽  
Moving Average Models ◽  
Intelligent Approach ◽  
Computational Intelligent

This paper presents an intelligent system for the detection of non-technical losses of electrical energy associated with the fraudulent behaviors of system users. This proposal has three stages: a non-supervised clustering of consumption profiles based on a hybrid algorithm between self-organizing maps (SOM) and genetic algorithms (GA). A second stage for demand forecasting is based on ARIMA (autoregressive integrated moving average) models corrected intelligently through neural networks (ANN). The final stage is a classifier based on random forests for fraudulent user detection. The proposed intelligent approach was trained and tested with real data from the Colombian Caribbean region, where the utility reports energy losses of around 18% of the total energy purchased by the company during the five last years. The results show an average overall performance of 82.9% in the detection process of fraudulent users, significantly increasing the effectiveness compared to the approaches (68%) previously applied by the utility in the region.

scholarly journals Self-Organization and Adaptation in Intelligent Systems

1998 ◽  
Vol 2 (6) ◽  
pp. 177-177
Author(s):  
Nikola Kasabov ◽  
◽  
Robert Kozma ◽  
Keyword(s):  
Neural Networks ◽  
Information Systems ◽  
Intelligent Systems ◽  
Adaptive Systems ◽  
Hebbian Learning ◽  
Intelligent System ◽  
Self Organizing Maps ◽  
Intelligent Information Systems ◽  
Intelligent Information ◽  
Self Organizing

This special issue is devoted to one of the important topics of current intelligent information systems-their ability to adapt to the environment they operate in, as adaptation is one of the most important features of intelligence. Several milestones in the literature on adaptive systems mark the development in this area. The Hebbian learning rule,1) self-organizing maps,2,3) and adaptive resonance theory4) have influenced the research in this area a great deal. Some current development suggests methods for building adaptive neurofuzzy systems,5) and adaptive self-organizing systems based on principles from biological brains.6) The papers in this issue are organized as follows: The first two papers present material on organization and adaptation in the human brain. The third paper, by Kasabov, presents a novel approach to building open structured adaptive systems for on-line adaptation called evolving connectionist systems. The fourth paper by Kawahara and Saito suggests a method for building virtually connected adaptive cell structures. Papers 5 and 6 discuss the use of genetic algorithms and evolutionary computation for optimizing and adapting the structure of an intelligent system. The last two papers suggest methods for adaptive learning of a sequence of data in a feed-forward neural network that has a fixed structure. References: 1) D.O. Hebb, "The Organization of Behavior," Jwiley, New York, (1949). 2) T. Kohonen, "Self-organisation and associative memory," Springer-Verlag, Berlin, (1988). 3) T. Kohonen, "Self-Organizing Maps, second edition," Springer Verlag, (1997). 4) G. Carpenter and S. Grossberg, "Pattern recognition by self-organizing neural networks," The MIT Press, Cambridge, Massachusetts, (1991). 5) N. Kasabov, "Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering," The MIT Press, CA, MA, (1996). 6) S. Amari and N. Kasabov "Brain-like Computing and Intelligent Information Systems," Springer Verlag, Singapore, (1997).

scholarly journals PORTFOLIO ROBUSTNESS EVALUATION: A CASE STUDY IN THE ELECTRICITY SECTOR

2015 ◽  
Vol 23 (1) ◽  
pp. 59-80 ◽  
Author(s):  
João Carlos LOURENÇO ◽  
João Oliveira SOARES ◽  
Carlos A. BANA E COSTA
Keyword(s):  
Large Scale ◽  
Evaluation Model ◽  
Electricity Sector ◽  
Small Scale ◽  
Multiple Time ◽  
Electricity Distribution ◽  
Different Types ◽  
Distribution Company ◽  
Multicriteria Decision Support

Managers continually face the task of allocating resources to projects when there is not enough money to fund them all. Portfolio Robustness Evaluation (PROBE) is a multicriteria decision support system developed to help managers to perform that difficult task. This paper presents a PROBE model, developed for an electricity distribution company, to select the best portfolio of projects, subject to budget constraints for different types of projects and various organisational units in multiple time periods. Projects requiring large-scale investments are analysed separately from the small-scale projects. The robustness of the selected portfolio of large-scale projects is analysed in an iterative process where broader uncertainty ranges are considered for the values of the projects, and also when an environmental impact criterion is added to the evaluation model.

scholarly journals Total Quality Management: the case of an electricity distribution company

2019 ◽  
Vol 16 (1) ◽  
pp. 53-65 ◽  
Author(s):  
Ana Carla de Souza Gomes dos Santos ◽  
Leandro Machado Carvalho ◽  
Caio Ferreira de Souza ◽  
Augusto da Cunha Reis ◽  
Alberto Eduardo Besser Freitag
Keyword(s):  
Design Methodology ◽  
Electricity Sector ◽  
Electricity Distribution ◽  
Total Quality ◽  
Management Guidelines ◽  
Technical Procedure ◽  
Pdca Cycle ◽  
Distribution Company ◽  
Practical Implications

Goal: this research aims to deploy TQM in the new customers area of an electricity distribution company, located in Campos dos Goytacazes (Rio de Janeiro), based on three management pillars: guidelines, processes and routine. Design / Methodology / Approach: the nature of this work is applied research, with a qualitative problem approach, characterized as exploratory, using case study as a technical procedure, with data collected between april and september of 2015. Results: the performed methodology allowed a reduction of both "orders after deadline" (12%) and "unproductive visits" (22%) indicators. Limitations of the investigation: the research presented limitations, first, because of the resistance of some employees during the tools implementation and second, the methodology was implemented only in a sector of the company. Practical implications: the study was based on indicators and targets already used by the company. It was proposed and implemented an anomalies analysis and tools such asthe PDCA cycle, Pareto and Ishikawa diagrams, 5W1H, and Standard Operating Procedures. Originality / Value: there is little research with emphasis on TQM, especially when referring to an analysis using three levels of management (guidelines, process and routine) in the Brazilian electricity sector.

scholarly journals Sistem Pendukung Keputusan Prediksi Kecepatan Studi Mahasiswa Menggunakan Metode ID3

2011 ◽  
Vol 2 (2) ◽  
Author(s):  
Ronny Ardi Giovani ◽  
Paulus Mudjihartono ◽  
Pranowo Pranowo
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Computer Science ◽  
Support System ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Speed Prediction ◽  
Past Data ◽  
Tree Development

Abstract. Decision Support System of Students’ Study Speed Prediction Using ID3 Method. Speed can be a decisive period of study a student taking a degree in sajana. In this study would be built applications that serve to speed decision making predictions Students study Computer Science University of Atma Jaya Yogyakarta. Students will be expected sooner or later than the period of study by taking one course or thesis that will be undertaken after a certain semesters. There are many methods of classification of one method of ID3 (Induction Decision 3 'Tree'). Development system in this study made use of intelligent systems-based applications. The results achieved after the system is formed, among others, sophisticated and intelligent system capable of storing past data is used as a reference for decision making, where students with certain criteria can know the travel time of their studies, and can refer to the database so the system can be more detailed and rigorous in determining the choice. Keywords: study period speed, Decision Support Systems, ID3, Intelligent Systems Kecepatan masa studi dapat menjadi penentu seorang mahasiswa dalam menempuh gelar sajana. Dalam penelitian ini akan dibangun aplikasi yang berfungsi untuk pengambilan keputusan prediksi kecepatan studi Mahasiswa Teknik Informatika Universitas Atma Jaya Yogyakarta. Mahasiswa akan diprediksi  cepat atau lambatnya masa studi dalam menempuh mata kuliah maupun skripsi yang akan dijalani setelah semester tertentu. Ada banyak metode klasifikasi salah satunya metode ID3 (Induction Decision 3 ‘Tree’). Pembangunan sistem dalam penelitian ini dibuat menggunakan aplikasi berbasis sistem  cerdas. Hasil yang dicapai setelah sistem ini terbentuk antara lain sistem canggih dan cerdas yang mampu menyimpan data masa lalu yang digunakan sebagai acuan pengambilan keputusan, dimana mahasiswa dengan kriteria tertentu dapat diketahui masa tempuh studi mereka, serta dapat mengacu pada database sehingga sistem dapat lebih detail serta teliti dalam menentukan pilihan. Kata Kunci: kecepatan masa studi, Sistem Pendukung Keputusan, ID3, Sistem Cerdas

scholarly journals Learning IS-A relations from specialized-domain texts with co-occurrence measures

2018 ◽  
Vol 2 (1) ◽  
pp. 21
Author(s):  
Pedro Urena
Keyword(s):  
Language Processing ◽  
Intelligent Systems ◽  
Knowledge Engineering ◽  
Classification Problem ◽  
Chemical Substance ◽  
Distributional Semantics ◽  
Input Unit ◽  
Feature Extraction Method

<p>Ontology  enrichment  is  a  classification  problem  in which  an  algorithm  categorizes  an  input conceptual unit  in the corresponding node  in a target ontology. Conceptual enrichment  is of great importance both to Knowledge Engineering and Natural Language Processing, because it helps maximize the efficacy of intelligent systems, making them more adaptable to scenarios where  information  is  produced  by  means  of  language.  Following  previous  research  on distributional  semantics,  this  paper  presents  a  case  study  of  ontology  enrichment  using  a feature-extraction  method  which  relies  on  collocational  information  from  corpora.  The  major advantage  of  this  method  is  that  it  can  help  locate  an  input  unit  within  its  corresponding superordinate node in a taxonomy using a relatively small number of lexical features. In order to  evaluate  the  proposed  framework,  this  paper  presents  an  experiment  consisting  of  the automatic classification of a chemical substance in a taxonomy of toxicology.</p>

scholarly journals R&D Portfolio Management: the case study of a big energy company in Brazil

2013 ◽  
Vol 1 (1) ◽  
pp. 74-94
Author(s):  
Mariana Savedra Pfitzner ◽  
Ruy de Quadros Carvalho
Keyword(s):  
Portfolio Management ◽  
Organizational Context ◽  
Tariff Reduction ◽  
Electricity Sector ◽  
Systematic Evaluation ◽  
Management Tools ◽  
Energy Company ◽  
Distribution Company ◽  
Energy Companies

DOI: http://dx.doi.org/10.13071/regec.2317-5087.2012.1.1.4038.74-94Portfolio Management entails the systematic evaluation, selection and prioritization of R&D projects in the organizational context. The aim of this article is to discuss the use of tools for managing the R&D portfolio in the Brazilian electricity sector, using the case study of an energy distribution company as an analytical support. In this sector, investment in research projects and guidelines for their completion are enforced by law. Otherwise, energy companies would not invest in R&D, they would rather buy equipment and systems from international suppliers. The execution of these projects is also strongly supervised by ANEEL, which guarantees that their results will turn into new products, patents, job creation, tariff reduction and operational efficiency for the company. If projects do not accomplish with government criteria, energy companies may be strongly penalized. In order to avoid such risk, companies may implement Portfolio Management tools.

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

2019 ◽  
pp. 21-30
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Interaction Analysis ◽  
Educational Data Mining ◽  
Main Task ◽  
Intellectual System ◽  
Will Force ◽  
To Come ◽  
Artificial Intelligence Systems

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

The Central Role of Cognitive Computations in Human-Information Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Jessie Chin ◽  
Q. Vera Liao
Keyword(s):  
Information Systems ◽  
Cognitive Science ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Levels Of Abstraction ◽  
Intelligent Information Systems ◽  
Emergent Behaviour ◽  
Information Interaction ◽  
Intelligent Information

Cognitive science is a science of intelligent systems. This chapter proposes that cognitive science can provide useful perspectives for research on technology-mediated human-information interaction (HII) when HII is cast as emergent behaviour of a coupled intelligent system. It starts with a review of a few foundational concepts related to cognitive computations and how they can be applied to understand the nature of HII. It discusses several important properties of a coupled cognitive system and their implication to designs of information systems. Finally, it covers how levels of abstraction have been useful for cognitive science, and how these levels can inform design of intelligent information systems that are more compatible with human cognitive computations.

Sign in / Sign up

Export Citation Format

Share Document