scholarly journals Overview on modeling and management of Smart Grids

2021 ◽  
Vol 12 (5) ◽  
pp. 1453-1465
Author(s):  
Jihen El Khaldi ◽  
Lotfi Bouslimi ◽  
Hamza Wertani ◽  
Mohamed Najeh Lakhoua
Keyword(s):  
Smart Grids ◽  
State Of The Art ◽  
Information Modeling ◽  
General Idea ◽  
Structural Elements ◽  
Intelligent Network ◽  
Resource Modeling ◽  
Modeling Methods ◽  
Complex Ecosystem

The concept of Smart Grids refers to a complex ecosystem that can be described as a combination of systems to capture its most structural elements. When studying these complex systems, the traditional tools of the Cartesian methods have shown their limits. There is therefore a need to resort to other methods to model them. These modeling methods are generally classified and grouped into five families: functional modeling, decision modeling, resource modeling, information modeling and mixed modeling.  This review provides an overview of the state of the art of an intelligent network. The classification of modeling methods is also presented. Then an application of the bond graph approach will be explained. Finally we describe a general idea on the management of smart grids.

An Information Management Environment Based on the Model of Object Primitives

2011 ◽  
pp. 199-218
Author(s):  
Nekatarios Georgalas
Keyword(s):  
Information Management ◽  
State Of The Art ◽  
Functional Integration ◽  
Information Modeling ◽  
Heterogeneous Information ◽  
Modeling Methods ◽  
Current State ◽  
Management Architecture ◽  
Information Management Systems ◽  
Computing Environments

The explosive emergence of distributed computing environments and component-based architectures increases the demand for flexible information modeling paradigms. A review of the state-of-the-art shows that contemporary modeling methods and technology, such as object-orientation (OO) and CORBA, facilitate to an extent the functional integration of heterogeneous information management systems. However, there are still issues to be resolved that mainly involve (i) the inflexibility of modeling semantics adopted by OO methods, (ii) the complication of developing new service components and their deployment in a distributed management environment. This chapter attempts to pinpoint some of those difficulties and suggests ways to overcome them. In this direction, we give a short overview of the problems encountered in the current state-of-the-art that act as motivation for this research. In response to challenges identified, we then continue on two main strands of analysis, one theoretical and one practical. In the theoretical part we introduce the Model of Object Primitives. It aims at providing a more flexible way to model information. The main objective here is to simply pinpoint the basic principles and elements of the model and not provide a thorough analysis of its semantics. The semantics of the model is analytically described in (Georgalas, 2000). Finally, in the practical part we present an information management architecture that adopts the idea of primitives in order to build components and deliver information services to client applications.

scholarly journals BIM for Existing Construction: A Different Logic Scheme and an Alternative Semantic to Enhance the Interoperabilty

2021 ◽  
Vol 11 (4) ◽  
pp. 1855
Author(s):  
Franco Guzzetti ◽  
Karen Lara Ngozi Anyabolu ◽  
Francesca Biolo ◽  
Lara D’Ambrosio
Keyword(s):  
Project Management ◽  
Building Information Modeling ◽  
Information Modeling ◽  
Historical Buildings ◽  
Architectural Heritage ◽  
New Approach ◽  
Building Information ◽  
Heritage Building ◽  
New Construction

In the construction field, the Building Information Modeling (BIM) methodology is becoming increasingly predominant and the standardization of its use is now an essential operation. This method has become widespread in recent years, thanks to the advantages provided in the framework of project management and interoperability. Hoping for its complete dissemination, it is unthinkable to use it only for new construction interventions. Many are experiencing what happens with the so-called Heritage Building Information Modeling (HBIM); that is, how BIM interfaces with Architectural Heritage or simply with historical buildings. This article aims to deal with the principles and working methodologies behind BIM/HBIM and modeling. The aim is to outline the themes on which to base a new approach to the instrument. In this way, it can be adapted to the needs and characteristics of each type of building. Going into the detail of standards, the text also contains a first study regarding the classification of moldable elements. This proposal is based on current regulations and it can provide flexible, expandable, and unambiguous language. Therefore, the content of the article focuses on a revision of the thinking underlying the process, also providing a more practical track on communication and interoperability.

scholarly journals Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4776
Author(s):  
Seyed Mahdi Miraftabzadeh ◽  
Michela Longo ◽  
Federica Foiadelli ◽  
Marco Pasetti ◽  
Raul Igual
Keyword(s):  
Machine Learning ◽  
Power Systems ◽  
Smart Grids ◽  
State Of The Art ◽  
Smart Cities ◽  
Power Grids ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
New Research ◽  
Traditional Approaches

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models.

scholarly journals Improving Land Cover Classification Using Genetic Programming for Feature Construction

2021 ◽  
Vol 13 (9) ◽  
pp. 1623
Author(s):  
João E. Batista ◽  
Ana I. R. Cabral ◽  
Maria J. P. Vasconcelos ◽  
Leonardo Vanneschi ◽  
Sara Silva
Keyword(s):  
Land Cover ◽  
Genetic Programming ◽  
Satellite Images ◽  
State Of The Art ◽  
Binary Classification ◽  
Feature Construction ◽  
Classification Problems ◽  
Construction Methods ◽  
Box Models

Genetic programming (GP) is a powerful machine learning (ML) algorithm that can produce readable white-box models. Although successfully used for solving an array of problems in different scientific areas, GP is still not well known in the field of remote sensing. The M3GP algorithm, a variant of the standard GP algorithm, performs feature construction by evolving hyperfeatures from the original ones. In this work, we use the M3GP algorithm on several sets of satellite images over different countries to create hyperfeatures from satellite bands to improve the classification of land cover types. We add the evolved hyperfeatures to the reference datasets and observe a significant improvement of the performance of three state-of-the-art ML algorithms (decision trees, random forests, and XGBoost) on multiclass classifications and no significant effect on the binary classifications. We show that adding the M3GP hyperfeatures to the reference datasets brings better results than adding the well-known spectral indices NDVI, NDWI, and NBR. We also compare the performance of the M3GP hyperfeatures in the binary classification problems with those created by other feature construction methods such as FFX and EFS.

scholarly journals Review of Control and Energy Management Approaches in Micro-Grid Systems

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 168
Author(s):  
Abdellatif Elmouatamid ◽  
Radouane Ouladsine ◽  
Mohamed Bakhouya ◽  
Najib El Kamoun ◽  
Mohammed Khaidar ◽  
...  
Keyword(s):  
Energy Management ◽  
Predictive Control ◽  
State Of The Art ◽  
Household Demand ◽  
Grid Systems ◽  
Control Approach ◽  
Micro Grid ◽  
Management Approaches ◽  
Air Conditioning Systems

The demand for electricity is increased due to the development of the industry, the electrification of transport, the rise of household demand, and the increase in demand for digitally connected devices and air conditioning systems. For that, solutions and actions should be developed for greater consumers of electricity. For instance, MG (Micro-grid) buildings are one of the main consumers of electricity, and if they are correctly constructed, controlled, and operated, a significant energy saving can be attained. As a solution, hybrid RES (renewable energy source) systems are proposed, offering the possibility for simple consumers to be producers of electricity. This hybrid system contains different renewable generators connected to energy storage systems, making it possible to locally produce a part of energy in order to minimize the consumption from the utility grid. This work gives a concise state-of-the-art overview of the main control approaches for energy management in MG systems. Principally, this study is carried out in order to define the suitable control approach for MGs for energy management in buildings. A classification of approaches is also given in order to shed more light on the need for predictive control for energy management in MGs.

scholarly journals A Machine Vision Approach for Bioreactor Foam Sensing

2021 ◽  
pp. 247263032110088
Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Vision ◽  
State Of The Art ◽  
Low Cost ◽  
High Accuracy ◽  
Consumer Electronics ◽  
Learning System ◽  
Automotive Applications ◽  
Fine Grained

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.

Hydrogel-Based Bioinks for Three-Dimensional Bioprinting: Patent Analysis

2021 ◽  
Vol 7 (1) ◽  
pp. 3
Author(s):  
Ahmed Fatimi
Keyword(s):  
Tissue Engineering ◽  
Detailed Analysis ◽  
State Of The Art ◽  
Three Dimensional ◽  
Patent Analysis ◽  
The State ◽  
Driving Factors ◽  
3D Bioprinting ◽  
Preparation Methods

There are a variety of hydrogel-based bioinks commonly used in three-dimensional bioprinting. In this study, in the form of patent analysis, the state of the art has been reviewed by introducing what has been patented in relation to hydrogel-based bioinks. Furthermore, a detailed analysis of the patentability of the used hydrogels, their preparation methods and their formulations, as well as the 3D bioprinting process using hydrogels, have been provided by determining publication years, jurisdictions, inventors, applicants, owners, and classifications. The classification of patents reveals that most inventions intended for hydrogels used as materials for prostheses or for coating prostheses are characterized by their function or properties Knowledge clusters and expert driving factors show that biomaterials, tissue engineering, and biofabrication research is concentrated in the most patents.

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