A taxonomy of energy optimization techniques for smart cities: Architecture and future directions

2021 ◽  
Author(s):  
Sudeep Tanwar ◽  
Aarti Popat ◽  
Pronaya Bhattacharya ◽  
Rajesh Gupta ◽  
Neeraj Kumar
Keyword(s):  
Smart Cities ◽  
Energy Optimization ◽  
Optimization Techniques ◽  
Future Directions

scholarly journals Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1928 ◽  
Author(s):  
Alfonso González-Briones ◽  
Fernando De La Prieta ◽  
Mohd Mohamad ◽  
Sigeru Omatu ◽  
Juan Corchado
Keyword(s):  
Optimization Problems ◽  
State Of The Art ◽  
Smart Cities ◽  
Energy Optimization ◽  
Sensor Data ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Research Perspectives ◽  
Wide Range ◽  
Multi Agent

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.

DSM for Energy Optimization and Communications Within Smart Grid CPSs

2022 ◽  
pp. 506-528
Author(s):  
Sa'ed Abed ◽  
Areej Abdelaal ◽  
Amjad Gawanmeh
Keyword(s):  
Developing Countries ◽  
Smart Grid ◽  
Energy Demand ◽  
New Technologies ◽  
Power Grid ◽  
Energy Optimization ◽  
Cyber Physical Systems ◽  
Optimization Techniques ◽  
Grid System ◽  
Potential Solution

Energy demand has increased significantly in the recent years due to the emerging of new technologies and industries, in particular in the developing countries. This increase requires much more developed power grid system than the existing traditional ones. Smart grid (SG) offers a potential solution to this problem. Being one of the most needed and complex cyber-physical systems (CPS), SG has been addressed exhaustively by researchers, from different views and aspects. However, energy optimization yet needs much more studying and examination. Therefore, this chapter presents a comprehensive investigation and analysis of the state-of-the-art developments in SG as a CPS with emphasis on energy optimization techniques and challenges. It also surveys the main challenges facing the SG considering CPS factors and the remarkable accomplishments and techniques in addressing these challenges. In addition, the document contrasts between different techniques according to their efficiency, usage, and feasibility. Moreover, this work explores the most effective applications of the SG as a CPS.

scholarly journals A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 108 ◽  
Author(s):  
Abdul Shah ◽  
Haidawati Nasir ◽  
Muhammad Fayaz ◽  
Adidah Lajis ◽  
Asadullah Shah
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Optimization Algorithms ◽  
Energy Optimization ◽  
Smart Homes ◽  
Electrical Energy ◽  
Optimization Techniques ◽  
Comfort Level ◽  
Energy Consumption Optimization ◽  
User Comfort

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique is to maintain a balance between user comfort and energy requirements, such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gaps in the literature are due to advancements in technology, the drawbacks of optimization algorithms, and the introduction of new optimization algorithms. Further, many newly proposed optimization algorithms have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. Detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes.

scholarly journals Prototype Survey of Different Energy Optimization and Routing Approaches in Wireless Sensor Networks

2019 ◽  
pp. 01-09
Author(s):  
G. Mohan Ram ◽  
M. V. Subba Rao ◽  
T. Kesava
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Performance ◽  
Energy Optimization ◽  
Data Communication ◽  
Optimization Techniques ◽  
Wireless Sensor ◽  
Design Parameters ◽  
Network Efficiency ◽  
Sensor Networking

For personal, mobiles and sensor communications wireless sensor networking are an emerging concept in recent years. Normally wireless sensor network (WSN) is combined and integrated data relations for modern communication in infrastructure, energy efficiency; these are the main design parameters to improve network performance with respect to mitigate communication relations. This paper describes different types of energy optimization techniques/approaches and basic routing scenarios used for efficient communication in wireless sensor networks. We also give brief description about different routing protocols to support data communication in wireless sensor networks. And also define different routing algorithms used in data communication to increase network efficiency with respect to different network parameters. In this survey, discuss about energy optimization approaches in wireless sensor networks, and also define several techniques which aim energy consumption in wireless nodes in WSNs.

Sustainable Process Analytics Formalism: A Case Study of Book Binding System for Energy Optimization

2013 ◽  
Author(s):  
Duck Bong Kim ◽  
Guodong Shao ◽  
Alexander Brodsky ◽  
Ryan Consylman
Keyword(s):  
Energy Efficiency ◽  
Preliminary Analysis ◽  
Energy Optimization ◽  
Optimization Techniques ◽  
Flow Data ◽  
Improve Energy Efficiency ◽  
Process Analytics ◽  
Manufacturing Optimization ◽  
Provide Decision Support

Energy is considered as one of the important factors for manufacturers to achieve the sustainability objective. To improve energy efficiency in manufacturing, optimization techniques are essential to provide decision support. However, formulating and solving energy optimization in manufacturing is still time-consuming and difficult due to its complexity with a broad scope. In addition, it is a challenging task since it requires substantial development efforts and modeling expertise. To address this drawback, Sustainable Process Analytics Formalism (SPAF) is proposed to facilitate the modeling and optimization. In this paper, SPAF will be applied to a case study of energy optimization for a book binding production system for its feasibility validation. The knowledge of process flow, data, and metrics of the case study is represented using SPAF, and a preliminary analysis of optimization results was performed.

Smart Cities: Study and Comparison of Traffic Light Optimization in Modern Urban Areas Using Artificial Intelligence

2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Mustapha Kabrane ◽  
Salah-ddine Krit ◽  
Lahoucine El Maimouni
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Road Network ◽  
Smart Cities ◽  
Optimization Techniques ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
The Road ◽  
Road Signs

In large cities, the increasing number of vehicles private, society, merchandise, and public transport, has led to traffic congestion. Users spend much of their time in endless traffic congestion. To solve this problem, several solutions can be envisaged. The interest is focused on the  system of road signs: The use of a road infrastructure is controlled by a traffic light controller, so it is a matter of knowing how to make the best use of the controls of this system (traffic lights) so as to make traffic more fluid. The values of the commands computed by the controller are determined by an algorithm which is ultimately, only solves a mathematical model representing the problem to be solved. The objective is to make a study and then the comparison on the optimization techniques based on artificial intelligence1 to intelligently route vehicle traffic. These techniques make it possible to minimize a certain function expressing the congestion of the road network. It can be a function, the length of the queue at intersections, the average waiting time, also the total number of vehicles waiting at the intersection

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