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Energies
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Building, District, and Community Energy Systems Optimization
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Building, District, and Community Energy Systems Optimization

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 September 2021) | Viewed by 10791

Special Issue Editors

Dr. Fuzhan Nasiri

E-Mail Website
Guest Editor
Department of Building, Civil, and Environmental Engineering (BCEE), Concordia University, Montreal, Quebec H3G 1M8, Canada
Interests: facilities management; environmental engineering; energy systems engineering; risk, resilience and reliability analysis; critical infrastructure management; smart and sustainable cities and communities; life cycle analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammad Sameti

E-Mail Website
Guest Editor
Energy Institute, School of Chemical and Bioprocess Engineering, University College Dublin, Dublin, Ireland
Interests: renewable energy; energy storage; energy efficiency; optimization; energy systems

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue of the journal Energies on the topic of Building and District Energy System Optimization.

Buildings account for a major share of energy consumption in today’s highly urbanized societies. Reducing carbon emissions and enhancing energy security have provoked increasing interest in energy conservation, energy efficiency, and renewable energy technologies. At the building scale, the attention has been on passive strategies, including emerging building insulation technologies, natural lighting, heating and cooling, as well as energy storage and recovery. Active strategies such as building-integrated renewables have also been pursued to opt for clean sources in the absense of conservation and efficiency measures. In doing so, to improve the economy of scale when it comes to promoting passive or active strategies in buildings, district heating and cooling systems are designed and configured to connect several buildings with a collective generation, distribution, and control mechanism to achieve the most energy-efficient performance.

The design, operation, and control of energy systems at the building or district scale is a complex task involving many decisions related to the choice of technologies, sizing, configuration, scheduling, maintenance, and occupants’ preferences. The purpose of this Special Issue is to try to fill the knowledge gap that presently exists on the use of optimization models to adress these decisions in an integrated manner. We invite original contributions regarding recent developments and novel ideas in applications of whole system models and optimization techniques. Potential topics include but are not limited to design and operation of mechanical systems for energy conversion, distribution, and storage; building refurbishment decisions; renewable energy integration in buildings; combined heat and power systems, control systems (real-time and predictive); energy recovery; environmentally-frienly designs, fault disgnostics, and maintenance management; and emerging applications of data analytics and machine learning in building and district energy systems.      

Prof. Dr. Fuzhan Nasiri
Dr. Mohammad Sameti
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

  • Buildings
  • District energy systems
  • Energy conversion and conservation
  • Renewable energies
  • Optimization
  • Optimal control
  • Smart (thermal) grid
  • Maintenanace management
  • Building occupants
  • Energy storage and recovery
  • Machine learning
  • Data analyics

Published Papers (5 papers)

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Research

17 pages, 2848 KiB  
Article
Roof Color-Based Warm Roof Evaluation in Cold Regions Using a UAV Mounted Thermal Infrared Imaging Camera
by Kirim Lee, Jinhwan Park, Sejung Jung and Wonhee Lee
Energies 2021, 14(20), 6488; https://doi.org/10.3390/en14206488 - 10 Oct 2021
Cited by 2 | Viewed by 1990
Abstract
Existing studies on reducing urban heat island phenomenon and building temperature have been actively conducted; however, studies on investigating the warm roof phenomenon to in-crease the temperature of buildings are insufficient. A cool roof is required in a high-temperature region, while a warm [...] Read more.
Existing studies on reducing urban heat island phenomenon and building temperature have been actively conducted; however, studies on investigating the warm roof phenomenon to in-crease the temperature of buildings are insufficient. A cool roof is required in a high-temperature region, while a warm roof is needed in a low-temperature or cold region. Therefore, a warm roof evaluation was conducted in this study using the roof color (black, blue, green, gray, and white), which is relatively easier to install and maintain compared to conventional insulation materials and double walls. A remote sensing method via an unmanned aerial vehicle (UAV)-mounted thermal infrared (TIR) camera was employed. For warm roof evaluation, the accuracy of the TIR camera was verified by comparing it with a laser thermometer, and the correlation between the surface temperature and the room temperature was also confirmed using Pearson correlation. The results showed significant surface temperature differences ranging from 8 °C to 28 °C between the black-colored roof and the other colored roofs and indoor temperature differences from 1 °C to 7 °C. Through this study, it was possible to know the most effective color for a warm roof according to the color differences. This study gave us an idea of which color would work best for a warm roof, as well as the temperature differences from other colors. We believe that the results of this study will be helpful in heating load research, providing an objective basis for determining whether a warm roof is applied. Full article
(This article belongs to the Special Issue Building, District, and Community Energy Systems Optimization)
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17 pages, 2991 KiB  
Article
Applying Deep Learning to the Heat Production Planning Problem in a District Heating System
by Donghun Lee, Seok Mann Yoon, Jaeseung Lee, Kwanho Kim and Sang Hwa Song
Energies 2020, 13(24), 6641; https://doi.org/10.3390/en13246641 - 16 Dec 2020
Viewed by 1635
Abstract
District heating system is designed to minimize energy consumption and environmental pollution by employing centralized production facilities connected to demand regions. Traditionally, optimization based algorithms were applied to the heat production planning problem in the district heating systems. Optimization-based models provide near optimal [...] Read more.
District heating system is designed to minimize energy consumption and environmental pollution by employing centralized production facilities connected to demand regions. Traditionally, optimization based algorithms were applied to the heat production planning problem in the district heating systems. Optimization-based models provide near optimal solutions, while it takes a while to generate solutions due to the characteristics of the underlying solution mechanism. When prompt re-planning due to any parameter changes is necessary, the traditional approaches might be inefficient to generate modified solutions quickly. In this study, we developed a two-phase solution mechanism, where deep learning algorithm is applied to learn optimal production patterns from optimization module. In the first training phase, the optimization module generates optimal production plans for the input scenarios derived from operations history, which are provided to the deep learning module for training. In the second planning phase, the deep learning module with trained parameters predicts production plan for the test scenarios. The computational experiments show that after the training process is completed, it has the characteristic of quickly deriving results appropriate to the situation. By combining optimization and deep learning modules in a solution framework, it is expected that the proposed algorithm could be applied to online optimization of district heating systems. Full article
(This article belongs to the Special Issue Building, District, and Community Energy Systems Optimization)
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19 pages, 2979 KiB  
Article
Geometric Aspects of Assessing the Amount of Material Consumption in the Construction of a Designed Single-Family House
by Edwin Koźniewski and Karolina Banaszak
Energies 2020, 13(20), 5382; https://doi.org/10.3390/en13205382 - 15 Oct 2020
Cited by 3 | Viewed by 1570
Abstract
In this paper, we present a new approach for the analysis of the dependence of construction costs on the geometric shape of a building. Instead of difficult or even impossible-to-establish uniform prices and costs, we propose a cost analysis concerning the amount of [...] Read more.
In this paper, we present a new approach for the analysis of the dependence of construction costs on the geometric shape of a building. Instead of difficult or even impossible-to-establish uniform prices and costs, we propose a cost analysis concerning the amount of materials needed for construction. We show that the basic parameters are the base area of the building (plan), assumed in the study as the building area, and the area of the external walls of the building. The amount of consumption of most materials is proportional to the base area and the area of the external walls. The materials required for construction consume large amounts of energy during their manufacture. Therefore, shape optimization is not only economically significant for the investor but is also important in terms of the energy consumption, i.e., embodied energy. We propose a set of indicators to help a designer optimize the shape of the building at the initial design stage. Full article
(This article belongs to the Special Issue Building, District, and Community Energy Systems Optimization)
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18 pages, 3460 KiB  
Article
Optimal Configuration and Sizing of an Integrated Renewable Energy System for Isolated and Grid-Connected Microgrids: The Case of an Urban University Campus
by Navid Shirzadi, Fuzhan Nasiri and Ursula Eicker
Energies 2020, 13(14), 3527; https://doi.org/10.3390/en13143527 - 08 Jul 2020
Cited by 18 | Viewed by 3045
Abstract
Although renewable technologies are progressing fast, there are still challenges such as the reliability and availability of renewable energy sources and their cost issues due to capital intensity that hinder their broad adoption. This research aims at developing a configuration-sizing approach to enhance [...] Read more.
Although renewable technologies are progressing fast, there are still challenges such as the reliability and availability of renewable energy sources and their cost issues due to capital intensity that hinder their broad adoption. This research aims at developing a configuration-sizing approach to enhance the cost efficiency and sourcing reliability of renewable energies integrated in microgrids. To achieve this goal, various technologies were considered, such as solar PV, wind turbines, converters, and batteries for system configuration with minimization of net present cost (NPC) as the objective. Grid connection scenarios with up to 100% renewable contribution were analyzed. The results show that the integration of renewable technologies with some grid backup could reduce the levelized cost of energy (LCOE) to about half of the price of the electricity that the university purchases from the grid. Also, different kinds of solar tracker systems were studied. The outcome shows that by using a vertical axis solar tracker, the LCOE of the system could be reduced by more than 50 percent. This research can help the decision-maker to opt for the best scenarios for generating reliable and cost-efficient electricity. Full article
(This article belongs to the Special Issue Building, District, and Community Energy Systems Optimization)
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22 pages, 2746 KiB  
Article
Optimal Coordination Strategies for Load Service Entity and Community Energy Systems Based on Centralized and Decentralized Approaches
by Longxi Li
Energies 2020, 13(12), 3202; https://doi.org/10.3390/en13123202 - 19 Jun 2020
Cited by 5 | Viewed by 1730
Abstract
The energy interaction among a load service entity and community energy systems in neighboring communities leads to a complex energy generation, storage, and transaction problem. A load service entity is formed by a local electricity generation system, storage system, and renewable energy resources, [...] Read more.
The energy interaction among a load service entity and community energy systems in neighboring communities leads to a complex energy generation, storage, and transaction problem. A load service entity is formed by a local electricity generation system, storage system, and renewable energy resources, which can provide ancillary services to customers and the utility grid. This paper proposes two coordination schemes for the interaction of community-based energy systems and load service entities based on game-theoretic frameworks. The first one is a centralized coordination scheme with full cooperation, in which the load service entity and community energy systems jointly activate the local resources. The second one is set as a decentralized coordination scheme to obtain a relative balance of interests among the market participants in a Stackelberg framework. Two mathematical models are developed for the day-ahead decision-making of the above energy management schemes. The Shapley value method, Karush-Kuhn-Tucker conditions, and strong dual theory are applied to solve the complex coordination problems. Numerical study shows the effectiveness of the coordination strategies that all stakeholders benefit from the proposed coordination schemes and create a win–win situation. In addition, sensitivity analysis is conducted to study the effects of system configuration, energy demand, and energy prices on the economic performance of all stakeholders. The results can serve as references for business managers of the load service entity. Full article
(This article belongs to the Special Issue Building, District, and Community Energy Systems Optimization)
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