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Green Energy and Smart Systems
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Green Energy and Smart Systems

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (25 May 2020) | Viewed by 23661

Special Issue Editors

Dr. Gunasekaran Manogaran

E-Mail Website
Guest Editor
College of Engineering and Architecture (CEA), Department of Electrical Engineering and Computer Science, Howard University, Washington, DC 20059, USA
Interests: big data analytics; machine learning; internet of things
Special Issues, Collections and Topics in MDPI journals
Dr. Hassan Qudrat-Ullah

E-Mail Website
Guest Editor
School of Administrative Studies, York University, Toronto, ON, Canada
Interests: computing; decision making; system dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Qin Xin

E-Mail Website
Guest Editor
Faculty of Science and Technology, University of the Faroe Islands, Vestarabryggja 15, FO 100 Torshavn, Faroe Islands
Interests: algorithm and distributed computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Green energy comes from natural resources such as sunlight, rain, wind, algae, plants, and geothermal heat. These energy resources are renewable and naturally replenished. Green energy utilizes energy resources that are readily available around the world, including remote and rural areas that do not otherwise have access to electricity. Reducing carbon emissions increases green energy and green lifestyles. Fossil fuel, which is said to be one of the major contributors to emitted carbons, is a non-renewable source of fuel. Green energy includes solar power, wind power, hydropower, geothermal energy, biomass, and biofuel. An alternative or renewable energy source has a very minor impact on the environment, which reduces pollutants and reduces the greenhouse gases contributing to climate change. Furthermore green energy technologies such as wind energy, solar energy, and other green energy sources can be replaced in place of gas, oil, and coal for the creation of a green and clean emission-free environment for the future.

A smart system has different technological systems that can sense, acute and control according to specific situations. A smart energy system is always necessary for a smart environment because only an integrated green smart energy grid system can be an alternative solution to the traditional methods. A smart energy system can give a sustainable supply of energy by balancing between the real demand and supply processes. Since implementing green energy is mainly dependent on the renewable energy system, creating a balance between the energy sources can be a difficult problem. In order to overcome these smart-energy-based issues, new energy generating, storing, distributing, and monitoring technologies should be identified so that the smart systems can have a balanced energy supply to meet the demand. A smart energy solution has the significant potential to decarbonize and reduce environmental risks by increasing the economy, creating new opportunities in our smart system.

This Special Issue on “Green Energy and Smart Systems” will serve as an innovative and interesting platform for identifying solutions, modeling, and integrating smart energy generation and storage systems.

Topics of interest include but are not restricted to:

  • Importance of implementing smart systems using alternative and renewable energy;
  • Design and implementation of smart home energy management systems using green energy;
  • Holistic approaches to integrating green energy into smart cities;
  • Need of green energy in the future advancements of smart systems;
  • Application of solar and wind energy for smart home energy monitoring systems;
  • Recent advances in green energy for smart systems;
  • Efficient energy consumption system using renewable energy;
  • Future aspects of using renewable energy in smart home systems;
  • Role of green technologies in building smart energy systems.

Dr. Gunasekaran Manogaran
Prof. Hassan Qudrat-Ullah
Prof. Qin Xin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

19 pages, 3265 KiB  
Article
Internet-of-Things-Assisted Smart System 4.0 Framework Using Simulated Routing Procedures
by Jinglei Su, Xue Chu, Seifedine Kadry and Rajkumar S
Sustainability 2020, 12(15), 6119; https://0-doi-org.brum.beds.ac.uk/10.3390/su12156119 - 29 Jul 2020
Cited by 4 | Viewed by 1981
Abstract
The environment and energy are two important issues in the current century. The development of modern society is closely linked to energy and the environment. Internet of Things (IoT) and Wireless Sensor Networks (WSNs) have recently been developed substantially to contribute to the [...] Read more.
The environment and energy are two important issues in the current century. The development of modern society is closely linked to energy and the environment. Internet of Things (IoT) and Wireless Sensor Networks (WSNs) have recently been developed substantially to contribute to the fourth transformation of the power grid, namely the smart grid. WSNs have the potential to improve power grid reliability via cable replacements, fault-tolerance features, large-scale protection, versatility to deploy, and cost savings in the smart grid environment. Moreover, because of equipment noise, dust heat, electromagnetic interference, multipath effects, and fading, current WSNs are making it very difficult to provide effective communication for the smart grid (SG) environment, in which WSN work is more difficult. For the smart system 4.0 framework, a highly reliable communication network based on the WSN is critically important for the successful operation of electricity grids in the next decade. To solve the above problem, a Robust Bio-Dynamic Stimulated Routing Procedure (RDSRP) has been proposed based on the real-time behavior of a new Hybrid Bird Optimizer (HBO) model. The presented innovative research and development is a small yet important aspect of continuous critical activities that address one of our society’s major challenges and that reverse the dangerous trends of environmental destruction. This study explores some of the most recent advances in this area, including energy efficiency and energy harvesting, which are expected to have a significant impact on green topics under smart systems in the Internet of things. The experimental results show that the proposed distributed system suggestively enhances network efficiency and reduces the transmission of excess packets for wireless sensor network-based smart grid applications. Full article
(This article belongs to the Special Issue Green Energy and Smart Systems)
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17 pages, 3230 KiB  
Article
Sustainable Smart City Building Construction Methods
by Haoran Zhuang, Jian Zhang, Sivaparthipan C. B. and Bala Anand Muthu
Sustainability 2020, 12(12), 4947; https://0-doi-org.brum.beds.ac.uk/10.3390/su12124947 - 17 Jun 2020
Cited by 26 | Viewed by 4991
Abstract
In a global world, the human population invariably increases while resources gradually decrease as cities and towns constantly consume resources to satisfy their needs and requirements. At this point, it is very necessary to focus on making these urban areas more sustainable and [...] Read more.
In a global world, the human population invariably increases while resources gradually decrease as cities and towns constantly consume resources to satisfy their needs and requirements. At this point, it is very necessary to focus on making these urban areas more sustainable and greener. The need for some advanced and automated systems improves the situation, which leads to the innovation of smart cities. Smart city is the concept that helps in developing sustainable cities via optimized resource utilization methods. In smart city development, various sensing technologies can be used that can sense and utilize natural resources in better ways, like storing rainwater to use afterward, intelligent and smart control system, smart infrastructure monitoring system, smart healthcare system, smart transportation system, and smart system for energy consumption and generation by various facilities. To make the city smart and sustainable with efficient energy consumption, we propose renewable solar and wind energy-enabled hybrid heating and cooling HVAC-DHW (heating, ventilation, and air conditioning-Domestic Hot Water) system in which energy consumption is evaluated using optimized NARX-ANN and fuzzy controller based on user needs, dynamic behavior of the atmospheric environment, and spatial distribution of energy supply. To achieve the proposed goal, first, via sensor, heating and cooling effect of environment and building is sensed and these sensed inputs are then fed into deep-learning-based NARX-ANN that forecast internal building temperature. This forecasted temperature is fed into a fuzzy controller for optimizing output based on user demand. This processed information leads to energy distribution based on their requirement using a smart energy sensing system. Based on the experimentation result and performance analysis, it was found that the proposed system is more robust and has a high control response in comparison to the existing systems with minimum energy consumption. The analytical results support the feasibility of the proposed framework architecture to facilitate energy conserving in smart city buildings. Full article
(This article belongs to the Special Issue Green Energy and Smart Systems)
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14 pages, 3962 KiB  
Article
Minimal Green Energy Consumption and Workload Management for Data Centers on Smart City Platforms
by Pei Pei, Zongjie Huo, Oscar Sanjuán Martínez and Rubén González Crespo
Sustainability 2020, 12(8), 3140; https://0-doi-org.brum.beds.ac.uk/10.3390/su12083140 - 14 Apr 2020
Cited by 13 | Viewed by 2732
Abstract
Presently, energy is considered a significant resource that grows scarce with high demand and population in the global market. Therefore, a survey suggested that renewable energy sources are required to avoid scarcity. Hence, in this paper, a smart, sustainable probability distribution hybridized genetic [...] Read more.
Presently, energy is considered a significant resource that grows scarce with high demand and population in the global market. Therefore, a survey suggested that renewable energy sources are required to avoid scarcity. Hence, in this paper, a smart, sustainable probability distribution hybridized genetic approach (SSPD-HG) has been proposed to decrease energy consumption and minimize the total completion time for a single machine in smart city machine interface platforms. Further, the estimated set of non-dominated alternative using a multi-objective genetic algorithm has been hybridized to address the problem, which is mathematically computed in this research. This paper discusses the need to promote the integration of green energy to reduce energy use costs by balancing regional loads. Further, the timely production of delay-tolerant working loads and the management of thermal storage at data centers has been analyzed in this research. In addition, differences in bandwidth rates between users and data centers are taken into account and analyzed at a lab scale using SSPD-HG for energy-saving costs and managing a balanced workload. Full article
(This article belongs to the Special Issue Green Energy and Smart Systems)
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14 pages, 2828 KiB  
Article
Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources
by Ronggang Zhang, Sathishkumar V E and R. Dinesh Jackson Samuel
Sustainability 2020, 12(8), 3115; https://0-doi-org.brum.beds.ac.uk/10.3390/su12083115 - 13 Apr 2020
Cited by 44 | Viewed by 3909
Abstract
This article provides a fuzzy expert system for efficient energy smart home management systems (FES-EESHM), demand management, renewable energy management, energy storage, and microgrids. The suggested fuzzy expert framework is utilized to simplify designing smart microgrids with storage systems, renewable sources, and controllable [...] Read more.
This article provides a fuzzy expert system for efficient energy smart home management systems (FES-EESHM), demand management, renewable energy management, energy storage, and microgrids. The suggested fuzzy expert framework is utilized to simplify designing smart microgrids with storage systems, renewable sources, and controllable loads on resources. Further, the fuzzy expert framework enhances energy and storage to utilize renewable energy and maximize the microgrid’s financial gain. Moreover, the fuzzy expert system utilizes insolation, electricity price, wind speed, and load energy controllably and unregulated as input variables to enable energy management. It uses input variables including insolation, electrical quality, wind, and the power of uncontrollable and controllable loads to allow energy management. Furthermore, these input data can be calculated, imported, or predicted directly via grid measurement using any prediction process. In this paper, the input variables are fuzzified, a series of rules are specified by the expert system, and the output is de-fuzzified. The findings of the expert program are discussed to explain how to handle microgrid power consumption and production. However, the decisions on energy generated, controllable loads, and own consumption are based on three outputs. The first production is for processing, selling, or consuming the energy produced. The second output is used for controlling the load. The third result shows how to produce for prosumer’s use. The expert method can be checked via the hourly input of variable values. Finally, to confirm the findings, the method suggested is compared to other available approaches. Full article
(This article belongs to the Special Issue Green Energy and Smart Systems)
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14 pages, 2709 KiB  
Article
Hybridized Intelligent Home Renewable Energy Management System for Smart Grids
by Yonghong Ma and Baixuan Li
Sustainability 2020, 12(5), 2117; https://0-doi-org.brum.beds.ac.uk/10.3390/su12052117 - 09 Mar 2020
Cited by 36 | Viewed by 9147
Abstract
The incorporation of renewable energies and power storage at distribution facilities are one of the important features in the smart grid. In this paper, a hybridized intelligent home renewable energy management system (HIHREM) that combines solar energy and energy storage services with the [...] Read more.
The incorporation of renewable energies and power storage at distribution facilities are one of the important features in the smart grid. In this paper, a hybridized intelligent home renewable energy management system (HIHREM) that combines solar energy and energy storage services with the smart home is planned based on the demand response and time of consumption pricing is applied to programs that offer discounts to consumers that reduce their energy consumption during high demand periods. The system is designed and handled with minimal energy requirements at home through installation of renewable energy, preparation, and arrangement of power stream during peak and off-peak periods. The best energy utilization of residential buildings with various overlapping purposes is one of the most difficult issues correlated with the implementation of intelligent micro-network systems. A major component of the smart grid, the domestic energy control system (HIHREM) provides many benefits, such as power bill reductions, reduction in wind generation, and demand compliance. This showed that the proposed energy scheduling method minimizes the energy consumption by 48% and maximizes the renewable energy consumed at the rate 65% of the total energy generated. A new model for smart homes with renewable energies is introduced in this report. The proposed HIHREM method achieves high performance and reduces cost-utility. Full article
(This article belongs to the Special Issue Green Energy and Smart Systems)
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