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Demand-Response in Smart Buildings
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Demand-Response in Smart Buildings

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "G: Energy and Buildings".

Deadline for manuscript submissions: closed (20 May 2019) | Viewed by 39330

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Dionysia Kolokotsa

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Guest Editor
School of Environmental Engineering, Technical University of Crete, 731 00 Chania, Greece
Interests: energy management in the built environment; zero-energy buildings; integration of renewables in buildings and smart grids; solar energy applications; sustainable cities and communities; urban heat island and climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Gloria Pignatta

E-Mail Website
Guest Editor
School of Built Environment, University of New South Wales (UNSW) Sydney, Sydney, NSW 2052, Australia
Interests: sustainable building development; building energy efficiency; net-zero energy buildings; positive energy districts; climate adaptation and mitigation; energy transitions; energy poverty
Special Issues, Collections and Topics in MDPI journals
Dr. Kostas Gobakis

E-Mail
Guest Editor
Technical University of Crete, Department of Environmental Engineering, 73100 Khania, Greece
Interests: energy efficiency; built environment; energy management; renewable energy; smart building; power systems; building simulation; IoT

Special Issue Information

Dear Colleagues,

We would like to invite you to contribute to a Special Issue, entitled “Demand-Response in Smart Buildings”.

Demand response (DR) offers the capability to apply changes in the energy usage of consumers from their normal consumption patterns in response to changes in energy pricing over time. This leads to a lower energy demand during peak hours or during periods when an electricity grid’s reliability is put at risk. Therefore, demand response is a reduction in demand designed to reduce peak load or avoid system emergencies. Hence, demand response can be more cost-effective than adding generation capabilities to meet the peak and/or occasional demand spikes. The underlying objective of DR is to actively engage customers in modifying their consumption in response to pricing signals. Demand response is expected to increase energy market efficiency and security of supply, which will ultimately benefit customers by way of options for managing their electricity costs leading to reduced environmental impact. This Special Issue is focusing on the coupling of demand response with smart buildings and communities with the aim of covering alternative demand response approaches, case study analyses, research trends and necessary transformations in smart buildings and communities to be able to successfully implement demand response.

Prof. Dr. Denia Kolokotsa
Dr. Gloria Pignatta
Dr. Kostas Gobakis
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. Energies 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 2600 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.

Keywords

  • Demand response
  • Smart Grids
  • Building user behavior
  • Energy Management

Published Papers (5 papers)

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Research

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19 pages, 17439 KiB  
Article
Energy Retrofitting Effects on the Energy Flexibility of Dwellings
by Francesco Mancini and Benedetto Nastasi
Energies 2019, 12(14), 2788; https://doi.org/10.3390/en12142788 - 19 Jul 2019
Cited by 43 | Viewed by 21191
Abstract
Electrification of the built environment is foreseen as a main driver for energy transition for more effective, electric renewable capacity firming. Direct and on-time use of electricity is the best way to integrate them, but the current energy demand of residential building stock [...] Read more.
Electrification of the built environment is foreseen as a main driver for energy transition for more effective, electric renewable capacity firming. Direct and on-time use of electricity is the best way to integrate them, but the current energy demand of residential building stock is often mainly fuel-based. Switching from fuel to electric-driven heating systems could play a key role. Yet, it implies modifications in the building stock due to the change in the temperature of the supplied heat by new heat pumps compared to existing boilers and in power demand to the electricity meter. Conventional energy retrofitting scenarios are usually evaluated in terms of cost-effective energy saving, while the effects on the electrification and flexibility are neglected. In this paper, the improvement of the building envelope and the installations of electric-driven space heating and domestic hot water production systems is analyzed for 419 dwellings. The dwellings database was built by means of a survey among the students attending the Faculty of Architecture at Sapienza University of Rome. A set of key performance indicators were selected for energy and environmental performance. The changes in the energy flexibility led to the viable participation of all the dwellings to a demand response programme. Full article
(This article belongs to the Special Issue Demand-Response in Smart Buildings)
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23 pages, 1491 KiB  
Article
Intelligent Resource Allocation in Residential Buildings Using Consumer to Fog to Cloud Based Framework
by Sakeena Javaid, Nadeem Javaid, Tanzila Saba, Zahid Wadud, Amjad Rehman and Abdul Haseeb
Energies 2019, 12(5), 815; https://doi.org/10.3390/en12050815 - 01 Mar 2019
Cited by 19 | Viewed by 3546
Abstract
In this work, a new orchestration of Consumer to Fog to Cloud (C2F2C) based framework is proposed for efficiently managing the resources in residential buildings. C2F2C is a three layered framework consisting of cloud layer, fog layer and consumer layer. Cloud layer deals [...] Read more.
In this work, a new orchestration of Consumer to Fog to Cloud (C2F2C) based framework is proposed for efficiently managing the resources in residential buildings. C2F2C is a three layered framework consisting of cloud layer, fog layer and consumer layer. Cloud layer deals with on-demand delivery of the consumer’s demands. Resource management is intelligently done through the fog layer because it reduces the latency and enhances the reliability of cloud. Consumer layer is based on the residential users and their electricity demands from the six regions of the world. These regions are categorized on the bases of the continents. Two control parameters are considered: clusters of buildings and load requests, whereas four performance parameters are considered: Request Per Hour (RPH), Response Time (RT), Processing Time (PT) and cost in terms of Virtual Machines (VMs), Microgrids (MGs) and data transfer. These parameters are analysed by the round robin algorithm, equally spread current execution algorithm and our proposed algorithm shortest job first. Two scenarios are used in the simulations: resource allocation using MGs and resource allocation using MGs and power storage devices for checking the effectiveness of the proposed work. The simulation results of the proposed technique show that it has outperformed the previous techniques in terms of the above-mentioned parameters. There exists a tradeoff in the PT and RT as compared to cost of VM, MG and data transfer. Full article
(This article belongs to the Special Issue Demand-Response in Smart Buildings)
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22 pages, 6286 KiB  
Article
Development of Demand Response Energy Management Optimization at Building and District Levels Using Genetic Algorithm and Artificial Neural Network Modelling Power Predictions
by Nikos Kampelis, Elisavet Tsekeri, Dionysia Kolokotsa, Kostas Kalaitzakis, Daniela Isidori and Cristina Cristalli
Energies 2018, 11(11), 3012; https://doi.org/10.3390/en11113012 - 01 Nov 2018
Cited by 37 | Viewed by 4750
Abstract
Demand Response (DR) is a fundamental aspect of the smart grid concept, as it refers to the necessary open and transparent market framework linking energy costs to the actual grid operations. DR allows consumers to directly or indirectly participate in the markets where [...] Read more.
Demand Response (DR) is a fundamental aspect of the smart grid concept, as it refers to the necessary open and transparent market framework linking energy costs to the actual grid operations. DR allows consumers to directly or indirectly participate in the markets where energy is being exchanged. One of the main challenges for engaging in DR is associated with the initial assessment of the potential rewards and risks under a given pricing scheme. In this paper, a Genetic Algorithm (GA) optimisation model, using Artificial Neural Network (ANN) power predictions for day-ahead energy management at the building and district levels, is proposed. Individual building and building group analysis is conducted to evaluate ANN predictions and GA-generated solutions. ANN-based short term electric power forecasting is exploited in predicting day-ahead demand, and form a baseline scenario. GA optimisation is conducted to provide balanced load shifting and cost-of-energy solutions based on two alternate pricing schemes. Results demonstrate the effectiveness of this approach for assessing DR load shifting options based on a Time of Use pricing scheme. Through the analysis of the results, the practical benefits and limitations of the proposed approach are addressed. Full article
(This article belongs to the Special Issue Demand-Response in Smart Buildings)
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Review

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16 pages, 1311 KiB  
Review
Smart Energy Management Policy in India—A Review
by Komali Yenneti, Riya Rahiman, Adishree Panda and Gloria Pignatta
Energies 2019, 12(17), 3214; https://doi.org/10.3390/en12173214 - 21 Aug 2019
Cited by 10 | Viewed by 5885
Abstract
India accounts for six per cent of the world’s primary energy consumption. Rapid urbanization and rapid urban population growth have had a serious impact on energy consumption and subsequent carbon emissions. In particular, cities face a complex and interrelated set of challenges across [...] Read more.
India accounts for six per cent of the world’s primary energy consumption. Rapid urbanization and rapid urban population growth have had a serious impact on energy consumption and subsequent carbon emissions. In particular, cities face a complex and interrelated set of challenges across different sectors (building environment, mobility, water and waste management and public services). Re-examining these challenges by integrating smart energy management (SEM) principles is critical for sustainable and low-carbon urban development. In addition, managing energy footprint is one of the most challenging goals for cities, and as existing cities evolve and transform into smart cities, SEM becomes an integral part of the urban transformation. This article comprehensively reviews the different SEM technologies for different sectors (construction, transportation, public services, water and waste), the policies, and the current challenges and opportunities for SEM policy governance in India. Making urban energy smart can manage a city’s energy footprint and have a positive impact on future carbon emissions. Full article
(This article belongs to the Special Issue Demand-Response in Smart Buildings)
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18 pages, 4446 KiB  
Review
Energy Resources, Load Coverage of the Electricity System and Environmental Consequences of the Energy Sources Operation in the Slovak Republic—An Overview
by Martin Lieskovský, Marek Trenčiansky, Andrea Majlingová and Július Jankovský
Energies 2019, 12(9), 1701; https://doi.org/10.3390/en12091701 - 06 May 2019
Cited by 6 | Viewed by 2807
Abstract
According to the current circumstances that are related to the effectiveness of the tightened European Union (EU) environmental legislation, which sets minimum requirements for the heat and power sources of energy that are part of the Slovak Electricity System (SES) source mix, an [...] Read more.
According to the current circumstances that are related to the effectiveness of the tightened European Union (EU) environmental legislation, which sets minimum requirements for the heat and power sources of energy that are part of the Slovak Electricity System (SES) source mix, an article was prepared to summarize the information regarding energy and environmental legislation, which is in force as in the EU as in Slovakia. This information was completed with a description on the current situation and requirements for the safety and reliability of the “new” mix of sources and technologies of electricity production within the SES in terms of energy and economic efficiency and environmental consequences. Full article
(This article belongs to the Special Issue Demand-Response in Smart Buildings)
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