State of the Art of E-Democracy for Smart Cities

Author(s):  
T. M. Vinod Kumar
Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4776
Author(s):  
Seyed Mahdi Miraftabzadeh ◽  
Michela Longo ◽  
Federica Foiadelli ◽  
Marco Pasetti ◽  
Raul Igual

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.


Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1928 ◽  
Author(s):  
Alfonso González-Briones ◽  
Fernando De La Prieta ◽  
Mohd Mohamad ◽  
Sigeru Omatu ◽  
Juan Corchado

This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of agent-based architectures are described, the role played by the environment is analysed and we look at how MAS recognizes the characteristics of the environment to adapt to it. Moreover, it is discussed how MAS can be used as tools that simulate the results of different actions aimed at reducing energy consumption. Then, we look at MAS as a tool that makes it easy to model and simulate certain behaviors. This modeling and simulation is easily extrapolated to the energy field, and can even evolve further within this field by using the Internet of Things (IoT) paradigm. Therefore, we can argue that MAS is a widespread approach in the field of energy optimization and that it is commonly used due to its capacity for the communication, coordination, cooperation of agents and the robustness that this methodology gives in assigning different tasks to agents. Finally, this article considers how MASs can be used for various purposes, from capturing sensor data to decision-making. We propose some research perspectives on the development of electrical optimization solutions through their development using MASs. In conclusion, we argue that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings.


2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Ramin Keivani ◽  
Sina Faizollahzadeh Ardabili ◽  
Farshid Aram

Deep learning (DL) and machine learning (ML) methods have recently contributed to the advancement of models in the various aspects of prediction, planning, and uncertainty analysis of smart cities and urban development. This paper presents the state of the art of DL and ML methods used in this realm. Through a novel taxonomy, the advances in model development and new application domains in urban sustainability and smart cities are presented. Findings reveal that five DL and ML methods have been most applied to address the different aspects of smart cities. These are artificial neural networks; support vector machines; decision trees; ensembles, Bayesians, hybrids, and neuro-fuzzy; and deep learning. It is also disclosed that energy, health, and urban transport are the main domains of smart cities that DL and ML methods contributed in to address their problems.


Author(s):  
Yessenia Berenice Llive ◽  
Norbert Varga ◽  
László Bokor

In the near future with the innovative services and solutions being currently tested and deployed for cars, homes, offices, transport systems, smart cities, etc., the user connectivity will considerably change. It means that smart devices will be connected to the internet and produce a big impact on the internet traffic, increasing the service demand generated by devices and sensors. However most of these devices are vulnerable to attacks. Hence, the security and privacy become a crucial feature to be included in towards its appropriate deployment. Interconnected, cooperative, service-oriented devices and their related hardware/software solutions will contain sensitive data making such systems susceptible to attacks and leakage of information. Therefore, robust secure communication infrastructures must be established to aid suitable deployment. This chapter is a state-of-the-art assessment of US and EU C-ITS security solutions.


2020 ◽  
Vol 138 ◽  
pp. 282-289
Author(s):  
Nayan Kumar Subhashis Behera ◽  
Pankaj Kumar Sa ◽  
Sambit Bakshi

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Mohamad Mouazen ◽  
Ana Beatriz Hernández-Lara

Purpose Smart cities attract efficient and profitable economic activities, contribute to the societal welfare of their citizens and foster the efficient use and conservation of natural resources. Developing smart cities has become a priority for many developed countries, but as they are preferred destinations for migrants, this raises sustainability issues. They attract people who are seeking a better quality of life, smart services and solutions, a better environment and business activities. The purpose of this paper is to review the state of the art on the relationship between smart cities and migration, with a view to determining sustainability. Design/methodology/approach A bibliometric review and text mining analyses were conducted on publications between 2000 and 2019. Findings The results determined the main parameters of this research topic in terms of its growth, top journals and articles. The role of sustainability in the relationship between smart cities and migration is also identified, highlighting the special interest of its social dimension. Originality/value A bibliometric approach has not been used previously to investigate the link between smart cities and migration. However, given the current relevance of both phenomena, their emergence and growth, this approach is appropriate in determining the state of the art and its main descriptors, with special emphasis on the sustainability implications.


2019 ◽  
Vol 113 ◽  
pp. 03006
Author(s):  
Stefano Bracco ◽  
Federico Delfino ◽  
Paola Laiolo ◽  
Luisa Pagnini ◽  
Giorgio Piazza

A microgrid can be considered a profitable solution to be adopted in smart cities if it is marketable, i.e. more, or at least equally convenient than other traditional energy supply sources. Different economic parameters can be defined to determine its affordability. In particular, the LCOE (Levelized Cost of Electricity) is the most popular indicator adopted in the energy sector, widely used both for conventional and renewable power sources. However, the use of this metric still disregards important aspects that concerns microgrid applications. After providing a state-of-the-art of the use of LCOE, the present paper proposes a new methodology for sustainable microgrids in smart city, taking into account benefits due to cogeneration and trigeneration, integration costs as well as positive and negative side effects.


Author(s):  
Hongxu Zhu ◽  
Anna S. F. Chang ◽  
Roy S. Kalawsky ◽  
Kim Fung Tsang ◽  
Gerhard Petrus Hancke ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document