Special Issue "Evaluation of Energy Efficiency and Flexibility in Smart Buildings"

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

Deadline for manuscript submissions: closed (30 April 2020).

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A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Alessia Arteconi
E-Mail Website
Guest Editor
Dipartimento di Ingegneria, Industriale e Scienze Matematiche, Università Politecnica delle Marche, via brecce bianche 1, 60131 Ancona, Italy
Department of Mechanical Engineering, KU Leuven, B-3000 Leuven, Belgium
Interests: demand side management; heat pumps; energy efficiency; renewable energy; energy transition
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Special Issue Information

Dear Colleagues,

On behalf of Energies, I would like to invite you to contribute to this Special Issue “Evaluation of Energy Efficiency and Flexibility in Smart Buildings”. Buildings’ energy demand and  huge energy flexibility potential make them a strategic instrument to improve the efficiency of the overall energy system. This potential impact of the built environment is not yet fully developed and exploited and we, as researchers, can contribute to increasing the general awareness on achievable benefits. In particular, energy efficiency and energy flexibility potential need to be quantified and possible means to unlock such potential need to be disclosed. Particularly relevant is research activity on devices and control strategies that make a building “behave in a smart manner”.

This Special Issue will include articles on, but not limited to, the following areas: energy efficient solutions, new refurbishment technologies, demand side management strategies, renewable energies integration, energy storage, and optimal control.

I look forward to receiving your contribution.

Prof. Alessia Arteconi
Guest Editor

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 papers will be 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.

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Keywords

  • energy efficiency
  • energy flexibility
  • optimal control
  • demand side management
  • smart buildings

Published Papers (21 papers)

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Research

Open AccessArticle
Coloured BIPV Technologies: Methodological and Experimental Assessment for Architecturally Sensitive Areas
Energies 2020, 13(17), 4506; https://doi.org/10.3390/en13174506 - 01 Sep 2020
Cited by 7 | Viewed by 802
Abstract
Energy flexibility in buildings is gaining momentum with the introduction of new European directives that enable buildings to manage their own energy demand and production, by storing, consuming or selling electricity according to their need. The transition towards a low-carbon energy system, through [...] Read more.
Energy flexibility in buildings is gaining momentum with the introduction of new European directives that enable buildings to manage their own energy demand and production, by storing, consuming or selling electricity according to their need. The transition towards a low-carbon energy system, through the promotion of on-site energy production and enhancement of self-consumption, can be supported by building-integrated photovoltaics (BIPV) technologies. This paper investigates the aesthetic and technological integration of hidden coloured PV modules in architecturally sensitive areas that seem to be the best possibility to favour a balance between conservation and energy issues. First, a multidisciplinary methodology for evaluating the aesthetic and technical integration of PV systems in architecturally sensitive area is proposed, referring to the technologies available on the market. Second, the experimental characterisation of the technical performance specific BIPV modules and their comparison with standard modules under standard weather condition are analysed, with the aim of acquiring useful data for comparing the modules’ integration properties and performance. For this purpose, new testbeds have been set up to investigate the aesthetic integration and the energy performances of innovative BIPV products. The paper describes the analyses carried out to define the final configuration of these experimental testbeds. Finally, the experimental characterisation at standard test conditions of two coloured BIPV modules is presented and the experimental design for the outdoor testing is outlined. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Extending the Application of the Smart Readiness Indicator—A Methodology for the Quantitative Assessment of the Load Shifting Potential of Smart Districts
Energies 2020, 13(13), 3507; https://doi.org/10.3390/en13133507 - 07 Jul 2020
Cited by 2 | Viewed by 769
Abstract
In 2018, the revised Energy Performance of Buildings Directive (EPBD) included for the first time the application of a smart readiness indicator (SRI). Based on the fact that load shifting in and across buildings plays an increasingly important role to improve efficiency and [...] Read more.
In 2018, the revised Energy Performance of Buildings Directive (EPBD) included for the first time the application of a smart readiness indicator (SRI). Based on the fact that load shifting in and across buildings plays an increasingly important role to improve efficiency and alleviate the integration of renewable energy systems, the SRI is also aimed at providing an indication of how well buildings can interact with the energy grids. With the clustering of buildings into larger entities, synergies related to the integration of renewable energy and load shifting can be efficiently exploited. However, current proposals for the SRI focus mainly on qualitative appraisals of the smartness of buildings and do not include the wider context of the districts. Quantitative approaches that can be easily applied at an early planning stage are still mostly missing. To optimize infrastructure decisions on a larger scale, a quantifiable perspective beyond the building level is necessary to evaluate and leverage the larger load shifting capacities. This article builds on a previously published methodology for smart buildings with the aim to provide a numerical model-based approach on the assessment of whole districts based on their overall energy storage capacity, load shifting potential and their ability to actively interact with the energy grids. It also delivers the equivalent CO2 savings potential compared to a non-interactive system. The methodology is applied to theoretical use cases for validation. The results highlight that the proposed quantitative model can provide a meaningful and objective assessment of the load shifting potentials of smart districts. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Determination of the Energy Performance of a Solar Low Energy House with Regard to Aspects of Energy Efficiency and Smartness of the House
Energies 2020, 13(12), 3232; https://doi.org/10.3390/en13123232 - 22 Jun 2020
Cited by 1 | Viewed by 518
Abstract
The paper shows how difficult it is to prove technically that a building really is both low energy and smart, and that all aspects of energy efficiency have been treated equally. Regulations connected to the determination of the energy performance of residential buildings [...] Read more.
The paper shows how difficult it is to prove technically that a building really is both low energy and smart, and that all aspects of energy efficiency have been treated equally. Regulations connected to the determination of the energy performance of residential buildings take into account only space and hot water heating energy consumption and define the indices of maximal primary energy consumption, but not energy needs based on the architecture of the building. A single family house designed and constructed as a low energy solar house in Warsaw’s suburbs is considered. Availability of solar energy and its influence on the architecture of the house is analyzed. A specific solar passive architectural concept with solar southern and cold northern buffer spaces incorporated into the interior of the house is presented. Parameters of the building’s structure, construction materials, as well as operation parameters of equipment and heating systems based on active use of solar energy, ground energy (via a heat pump) and waste heat from a ventilation system are described. Results of calculations give values of final and primary energy consumption index levels of 11.58 kWh/m2 and 25.77 kWh/m2, respectively. However, the official methodology for determination of energy performance does not allow for presenting how energy efficient and smart the building really is. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Using Residential and Office Building Archetypes for Energy Efficiency Building Solutions in an Urban Scale: A China Case Study
Energies 2020, 13(12), 3210; https://doi.org/10.3390/en13123210 - 20 Jun 2020
Cited by 4 | Viewed by 697
Abstract
Building energy consumption accounts for 36% of the overall energy end use worldwide and is growing rapidly as developing countries continue to urbanize. Understanding the energy use at urban scale will lay the foundation for identification of energy efficiency opportunities to be deployed [...] Read more.
Building energy consumption accounts for 36% of the overall energy end use worldwide and is growing rapidly as developing countries continue to urbanize. Understanding the energy use at urban scale will lay the foundation for identification of energy efficiency opportunities to be deployed at speed. China has almost half of global new constructions and plays an important role in building suitability. However, an open source national building energy consumption database is not available in China. To provide data support for building energy consumptions, this paper used a simulation method to develop an urban building energy consumption database for a pilot city in Wuhan, China. First, residential, small, and large office building archetype energy models were created in EnergyPlus to represent typical building energy consumption in Wuhan. The baseline reference model simulation results were further validated using survey data from the literature. Second, stochastic simulations were conducted to consider different design parameters and occupants’ energy usage intensity scenarios, such as thermal properties of the building envelope, lighting power density, equipment power density, HVAC (heating, ventilation and air conditioning) schedule, etc. A building energy consumption database was generated for typical building archetypes. Third, data-driven regression analysis was conducted to support quick building energy consumption prediction using key high- level building information inputs. Finally, a web-based urban energy platform and an interface were developed to support further third-party application development. The research is expected to provide fast energy efficiency building design solutions for urban planning, new constructions as well as building retrofits. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessFeature PaperArticle
Performance Assessment of Data-Driven and Physical-Based Models to Predict Building Energy Demand in Model Predictive Controls
Energies 2020, 13(12), 3125; https://doi.org/10.3390/en13123125 - 16 Jun 2020
Cited by 6 | Viewed by 629
Abstract
The implementation of model predictive controls (MPCs) in buildings represents an important opportunity to reduce energy consumption and to apply demand side management strategies. In order to be effective, the MPC should be provided with an accurate model that is able to forecast [...] Read more.
The implementation of model predictive controls (MPCs) in buildings represents an important opportunity to reduce energy consumption and to apply demand side management strategies. In order to be effective, the MPC should be provided with an accurate model that is able to forecast the actual building energy demand. To this aim, in this paper, a data-driven model realized with an artificial neural network is compared to a physical-based resistance–capacitance (RC) network in an operative MPC. The MPC was designed to minimize the total cost for the thermal demand requirements by unlocking the energy flexibility in the building envelope, on the basis of price signals. Although both models allow energy cost savings (about 16% compared to a standard set-point control), a deterioration in the prediction performance is observed when the models actually operate in the controller (the root mean square error, RMSE, for the air zone prediction is about 1 °C). However, a difference in the on-time control actions is noted when the two models are compared. With a maximum deviation of 0.5 °C from the indoor set-point temperature, the physical-based model shows better performance in following the system dynamics, while the value rises to 1.8 °C in presence of the data-driven model for the analyzed case study. This result is mainly related to difficulties in properly training data-driven models for applications involving energy flexibility exploitation. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Solar+ Optimizer: A Model Predictive Control Optimization Platform for Grid Responsive Building Microgrids
Energies 2020, 13(12), 3093; https://doi.org/10.3390/en13123093 - 15 Jun 2020
Cited by 1 | Viewed by 1035
Abstract
With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries [...] Read more.
With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this paper, we present the “Solar+ Optimizer” (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Sensitivity Analysis of Window Frame Components Effect on Thermal Transmittance
Energies 2020, 13(11), 2957; https://doi.org/10.3390/en13112957 - 09 Jun 2020
Viewed by 415
Abstract
Standard ISO 10077-2 gives the procedure to calculate thermal transmittances of window frames in 2D numerical simulations. It also introduces some examples of frame geometrical models with all necessary input data and the solutions so as to perform validation of the applied numerical [...] Read more.
Standard ISO 10077-2 gives the procedure to calculate thermal transmittances of window frames in 2D numerical simulations. It also introduces some examples of frame geometrical models with all necessary input data and the solutions so as to perform validation of the applied numerical tools. In the present paper, the models prepared with a commercial finite volume software of a PVC window frame were first positively validated with the results given in the Standard. An experimental test was then implemented to confirm the simulated data, with satisfactory agreement. The numerical code was used on one of the frames provided by the Standard to perform a sensitivity analysis of all the components and boundary conditions playing a role on the definition of the frame thermal transmittance, such as surface heat transfer coefficients, values of the solid thermal conductivity, emissivity and insulation properties of air gaps. Results demonstrate that the air gap properties represent the most influential parameters for the definition of the PVC window frames thermal transmittance, followed by the surface heat transfer coefficients and the PVC thermal conductivity. The rubber and the steel properties show a negligible effect on the whole frame performance. This procedure could constitute a design tool to guide the efforts of window manufacturers for the achievement of high performance products. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Cost-Aware Design and Simulation of Electrical Energy Systems
Energies 2020, 13(11), 2949; https://doi.org/10.3390/en13112949 - 08 Jun 2020
Cited by 2 | Viewed by 593
Abstract
One fundamental dimension in the design of an electrical energy system (EES) is the economic analysis of the possible design alternatives, in order to ensure not just the maximization of the energy output but also the return on the investment and the possible [...] Read more.
One fundamental dimension in the design of an electrical energy system (EES) is the economic analysis of the possible design alternatives, in order to ensure not just the maximization of the energy output but also the return on the investment and the possible profits. Since the energy output and the economic figures of merit are intertwined, for an accurate analysis it is necessary to analyze these two aspects of the problem concurrently, in order to define effective energy management policies. This paper achieves that objective by tracking and measuring the energy efficiency and the cost effectiveness in a single modular framework. The two aspects are modeled separately, through the definition of dedicated simulation layers governed by dedicated virtual buses that elaborate and manage the information and energy flows. Both layers are simulated concurrently within the same simulation infrastructure based on SystemC-AMS, so as to recreate at runtime the mutual influence of the two aspects, while allowing the use of different discrete time scales for the two layers. Thanks to the tight coupling provided by the single simulation engine, our method enables a quick estimation of various cost metrics (net costs, annualized costs, and profits) of any configuration of EES under design, via an informed exploration of the alternatives. To prove the effectiveness of this approach, we apply the proposed strategy to two EES case studies, we explored various management strategies and the presence of different types and numbers of power sources and energy storage devices in the EES. The analysis proved to allow the identification of the optimal profitable solutions, thereby improving the standard design and simulation flow of EES. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Seasonal Energy Flexibility Through Integration of Liquid Sorption Storage in Buildings
Energies 2020, 13(11), 2944; https://doi.org/10.3390/en13112944 - 08 Jun 2020
Viewed by 541
Abstract
The article estimates energy flexibility provided to the electricity grid by integration of long-term thermal energy storage in buildings. To this end, a liquid sorption storage combined with a compression heat pump is studied for a single-family home. This combination acts as a [...] Read more.
The article estimates energy flexibility provided to the electricity grid by integration of long-term thermal energy storage in buildings. To this end, a liquid sorption storage combined with a compression heat pump is studied for a single-family home. This combination acts as a double-stage heat pump comprised of a thermal and an electrical stage. It lowers the temperature lift to be overcome by the electrical heat pump and thus increases its coefficient of performance. A simplified model is used to quantify seasonal energy flexibility by means of electric load shifting evaluated with a monthly resolution. Results are presented for unlimited and limited storage capacity leading to a total seasonal electric load shift of 631.8 kWh/a and 181.7 kWh/a, respectively. This shift, referred to as virtual battery effect, provided through long-term thermal energy storage is large compared to typical electric battery capacities installed in buildings. This highlights the significance of building-integrated long-term thermal energy storage for provision of energy flexibility to the electricity grid and hence for the integration of renewables in our energy system. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Steady-State Predictive Optimal Control of Integrated Building Energy Systems Using a Mixed Economic and Occupant Comfort Focused Objective Function
Energies 2020, 13(11), 2922; https://doi.org/10.3390/en13112922 - 06 Jun 2020
Viewed by 654
Abstract
Control of energy systems in buildings is an area of expanding interest as the importance of energy efficiency, occupant health, and comfort increases. The objective of this study was to demonstrate the effectiveness of a novel predictive steady-state optimal control method in minimizing [...] Read more.
Control of energy systems in buildings is an area of expanding interest as the importance of energy efficiency, occupant health, and comfort increases. The objective of this study was to demonstrate the effectiveness of a novel predictive steady-state optimal control method in minimizing the economic costs associated with operating a building. Specifically, the cost of utility consumption and the cost of loss productivity due to occupant discomfort were minimized. This optimization was achieved through the use of steady-state predictions and component level economic objective functions. Specific objective functions were developed and linear models were identified from data collected from a building on Texas A&M University’s campus. The building consists of multiple zones and is serviced by a variable air volume, chilled water air handling unit. The proposed control method was then co-simulated with MATLAB and EnergyPlus to capture effects across multiple time-scales. Simulation results show improved comfort performance and decreased economic cost over the currently implemented building control, minimizing productivity loss and utility consumption. The potential for more serious consideration of the economic cost of occupant discomfort in building control design is also discussed. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Experimental Study on Energy Efficiency of Multi-Functional BIPV Glazed Façade Structure during Heating Season
Energies 2020, 13(11), 2772; https://doi.org/10.3390/en13112772 - 01 Jun 2020
Cited by 4 | Viewed by 633
Abstract
Building integrated photovoltaics (BIPV) is technology that can significantly increase the share of renewable energy in final energy supply and are one of essential technologies for the nearly zero-energy buildings (nZEB), new build and refurbished. In the article (a) an experimental semitransparent BIPV [...] Read more.
Building integrated photovoltaics (BIPV) is technology that can significantly increase the share of renewable energy in final energy supply and are one of essential technologies for the nearly zero-energy buildings (nZEB), new build and refurbished. In the article (a) an experimental semitransparent BIPV glazed façade structure with 60% of PV cell coverage is shown; (b) energy efficiency indicators were developed based on identified impact parameters using experimental data; and (c) multi-parametric models of electricity generation, preheating of air for space ventilation, and dynamic thermal insulation features that enable prediction of solar energy utilization in different climate conditions are shown. The modeled efficiency of electricity production of BIPV was in the range between 8% and 9.5% at daily solar radiation above 1500 Wh/day, while low impact of outdoor air temperature and ventilation air flow rate on PV cell cooling was noticed. Between 35% and 75% of daily solar radiation can be utilized by preheating the air for space ventilation, and 4.5% to 7.5% of daily solar radiation can be utilized in the form of heat gains through opaque envelope walls. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools
Energies 2020, 13(10), 2598; https://doi.org/10.3390/en13102598 - 20 May 2020
Viewed by 732
Abstract
A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building [...] Read more.
A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building operators on the leading edge of technology adoption use FDD tools to enable median whole-building portfolio savings of 8%. Although FDD tools can inform operators of operational faults, currently an action is always required to correct the faults to generate energy savings. A subset of faults, however, such as biased sensors, can be addressed automatically, eliminating the need for staff intervention. Automating this fault “correction” can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention. Doing so is expected to advance the usability and technical and economic performance of FDD technologies. This paper presents the development of nine innovative fault auto-correction algorithms for Heating, Ventilation, and Air Conditioning pi(HVAC) systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables to implement the intended changes. It also discusses the implementation of the auto-correction algorithms in commercial FDD software products, the integration of these strategies with building automation systems and their preliminary testing. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Flattening the Electricity Demand Profile of Office Buildings for Future-Proof Smart Grids
Energies 2020, 13(9), 2357; https://doi.org/10.3390/en13092357 - 08 May 2020
Cited by 2 | Viewed by 770
Abstract
The built environment has the potential to contribute to maintaining a reliable grid at the demand side by offering flexibility services to a future Smart Grid. In this study, an office building is used to demonstrate forecast-driven building energy flexibility by operating a [...] Read more.
The built environment has the potential to contribute to maintaining a reliable grid at the demand side by offering flexibility services to a future Smart Grid. In this study, an office building is used to demonstrate forecast-driven building energy flexibility by operating a Battery Electric Storage System (BESS). The objective of this study is, therefore, to stabilize/flatten a building energy demand profile with the operation of a BESS. First, electricity demand forecasting models are developed and assessed for each individual load group of the building based on their characteristics. For each load group, the prediction models show Coefficient of Variation of the Root Mean Square Error (CVRMSE) values below 30%, which indicates that the prediction models are suitable for use in engineering applications. An operational strategy is developed aiming at meeting the flattened electricity load shape objective. Both the simulation and experimental results show that the flattened load shape objective can be met more than 95% of the time for the evaluation period without compromising the thermal comfort of users. Accurate energy demand forecasting is shown to be pivotal for meeting load shape objectives. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
A Smart Hybrid Energy System Grid for Energy Efficiency in Remote Areas for the Army
Energies 2020, 13(9), 2279; https://doi.org/10.3390/en13092279 - 05 May 2020
Cited by 5 | Viewed by 1251
Abstract
The current energy inefficiencies in relocatable temporary camps of the Armed Force troops create logistic challenges associated with fuel supply. The energy needs of these camps are primarily satisfied by diesel engine generators, which imply that a significant amount of fuel needs to [...] Read more.
The current energy inefficiencies in relocatable temporary camps of the Armed Force troops create logistic challenges associated with fuel supply. The energy needs of these camps are primarily satisfied by diesel engine generators, which imply that a significant amount of fuel needs to be continuously provided to these camps, often built in remote areas. This paper presents an alternative solution, named Smart Hybrid Energy System (SHES), aiming towards significantly reducing the amount of fuel needed and minimizing transportation logistics while meeting camp energy demands. The SHES combines the existing diesel generators with solar power generation, energy storage, and waste heat recovery technologies, all connected to a microgrid, ensuring uninterrupted electricity and hot water supplies. All components are controlled by an energy management system that prioritizes output and switches between different power generators, ensuring operation at optimum efficiencies. The SHES components have been selected to be easily transportable in standard shipping 20 ft containers. The modularity of the solution, scalable from the base camp for 150 people, is designed according to available on-site renewable sources, allowing for energy optimization of different camp sizes in different climates. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
The Effect of Deep Energy Retrofit on The Hourly Power Demand of Finnish Detached Houses
Energies 2020, 13(7), 1773; https://doi.org/10.3390/en13071773 - 07 Apr 2020
Cited by 4 | Viewed by 798
Abstract
This study examines how the energy renovation of old detached houses affects the hourly power consumption of heating and electricity in Finland. As electrification of heating through heat pumps becomes more common, the effects on the grid need to be quantified. Increased fluctuation [...] Read more.
This study examines how the energy renovation of old detached houses affects the hourly power consumption of heating and electricity in Finland. As electrification of heating through heat pumps becomes more common, the effects on the grid need to be quantified. Increased fluctuation and peak power demand could increase the need for fossil-based peaking power plants or call for new investments to the distribution infrastructure. The novelty in this study is the focus on hourly power demand instead of just annual energy consumption. Identifying the influence of building energy retrofits on the instantaneous power demand can help guide policy and investments into building retrofits and related technology. The work was done through dynamic building simulation and utilized building configurations obtained through multi-objective optimization. Deep energy retrofits decreased both the total and peak heating power consumption. However, the use of air-source heat pumps increased the peak power demand of electricity in district heated and wood heated buildings by as much as 100%. On the other hand, peak power demand in buildings with direct electric heating was reduced by 30 to 40%. On the building stock level, the demand reduction in buildings with direct electric heating could compensate for the increase in the share of buildings with ground-source heat pumps, so that the national peak electricity demand would not increase. This prevents the increase of demand for high emission peaking power plants as heat pump penetration rises. However, a use is needed for the excess solar electricity generated by the optimally retrofitted buildings, because much of the solar electricity cannot be utilized in the single-family houses during summer. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization
Energies 2020, 13(6), 1309; https://doi.org/10.3390/en13061309 - 11 Mar 2020
Cited by 5 | Viewed by 833
Abstract
In many regions, the heat used for space heating is a basic item in the energy balance of a building and significantly affects its operating costs. The accuracy of the assessment of heat consumption in an existing building and the determination of the [...] Read more.
In many regions, the heat used for space heating is a basic item in the energy balance of a building and significantly affects its operating costs. The accuracy of the assessment of heat consumption in an existing building and the determination of the main components of heat loss depends to a large extent on whether the energy efficiency improvement targets set in the thermal upgrading project are achieved. A frequent problem in the case of energy calculations is the lack of complete architectural and construction documentation of the analyzed objects. Therefore, there is a need to search for methods that will be suitable for a quick technical analysis of measures taken to improve energy efficiency in existing buildings. These methods should have satisfactory results in predicting energy consumption where the input is limited, inaccurate, or uncertain. Therefore, the aim of this work was to test the usefulness of a model based on Rough Set Theory (RST) for estimating the thermal energy consumption of buildings undergoing an energy renovation. The research was carried out on a group of 109 thermally improved residential buildings, for which energy performance was based on actual energy consumption before and after thermal modernization. Specific sets of important variables characterizing the examined buildings were distinguished. The groups of variables were used to estimate energy consumption in such a way as to obtain a compromise between the effort of obtaining them and the quality of the forecast. This has allowed the construction of a prediction model that allows the use of a fast, relatively simple procedure to estimate the final energy demand rate for heating buildings. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Study of the Improvement on Energy Efficiency for a Building in the Mediterranean Area by the Installation of a Green Roof System
Energies 2020, 13(5), 1246; https://doi.org/10.3390/en13051246 - 07 Mar 2020
Cited by 5 | Viewed by 870
Abstract
Rooftop gardens ona building have proved to be a good way to improve its storm water management, but many other benefits can be obtained from the installation of these systems, such as reduction of energy consumption, decrease of the heat stress, abatement on [...] Read more.
Rooftop gardens ona building have proved to be a good way to improve its storm water management, but many other benefits can be obtained from the installation of these systems, such as reduction of energy consumption, decrease of the heat stress, abatement on CO2 emissions, etc. In this paper, the effect from the presence of these rooftop gardens on abuilding’s energy consumption has been investigated by experimental campaigns using a green roof ona public building in a Mediterranean location in Spain. The obtained results demonstrate a substantial improvement by the installation of the green roof onthe building’s cooling energy demand for a standard summer day, in the order of 30%, and a reduction, about 15%, in the heating energy demand for a winter day. Thus, given the longer duration of the summer conditions along the year, a noticeable reduction on energy demand could be obtained. Simulation analysis, using commercial software TRNSYS code, previously calibrated using experimental data for typical summer and winter days, allows for the extrapolation to the entire year of these results deducing noticeable improvement in energy efficiency, in the order of 19%, but with an increase of 6% in the peak power during the winter period. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Novel Simulation Algorithm for Modeling the Hysteresis of Phase Change Materials
Energies 2020, 13(5), 1200; https://doi.org/10.3390/en13051200 - 05 Mar 2020
Cited by 5 | Viewed by 908
Abstract
Latent heat thermal energy storage (LHTES) using phase change materials (PCM) is one of the most promising ways for thermal energy storage (TES), especially in lightweight buildings. However, accurate control of the phase transition of PCM is not easy to predict. For example, [...] Read more.
Latent heat thermal energy storage (LHTES) using phase change materials (PCM) is one of the most promising ways for thermal energy storage (TES), especially in lightweight buildings. However, accurate control of the phase transition of PCM is not easy to predict. For example, neglecting the hysteresis or the effect of the speed of phase change processes reduces the accuracy of simulations of TES. In this paper, the authors propose a new software module for EnergyPlus™ that aims to simulate the hysteresis of PCMs during the phase change. The new module is tested by comparing simulation results with experimental tests done in a climatic chamber. A strong consistency between experimental and simulation results was obtained, while a discrepancy error of less than 1% was obtained. Moreover, in real conditions, as a result of quick temperature changes, only a partial phase transformation of the material is often observed. The new model also allows the consideration of the case with partial phase changes of the PCM. Finally, the simulation algorithm presented in this article aims to represent a better way to model LHTES with PCM. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System
Energies 2020, 13(3), 530; https://doi.org/10.3390/en13030530 - 21 Jan 2020
Cited by 2 | Viewed by 715
Abstract
The energy consumption of air-conditioning systems is a major part of energy consumption in buildings. Optimal control strategies have been increasingly developed in building heating, ventilation, and air-conditioning (HVAC) systems. In this paper, a load forecast fuzzy (LFF) control strategy was proposed. The [...] Read more.
The energy consumption of air-conditioning systems is a major part of energy consumption in buildings. Optimal control strategies have been increasingly developed in building heating, ventilation, and air-conditioning (HVAC) systems. In this paper, a load forecast fuzzy (LFF) control strategy was proposed. The predictive load based on the SVM method was used as the input parameter of the fuzzy controller to perform feedforward fuzzy control on the HVAC system. This control method was considered as an effective way to reduce energy consumption while ensuring indoor comfort, which can solve the problem of hysteresis and inaccuracy in building HVAC systems by controlling the HVAC system in advance. The case study was conducted on a ground source heat pump system in Tianjin University to validate the proposed control strategy. In addition, the advantages of the LFF control strategy were verified by comparing with two feedback control strategies, which are the supply water temperature (SWT) control strategy and the room temperature fuzzy (RTF) control strategy. Results show that the proposed LFF control strategy is capable not only to ensure the minimum indoor temperature fluctuations but also decrease the total energy consumption. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Energy Performance Investigation of a Direct Expansion Ventilation Cooling System with a Heat Wheel
Energies 2019, 12(22), 4267; https://doi.org/10.3390/en12224267 - 08 Nov 2019
Cited by 2 | Viewed by 639
Abstract
Climate change is continuously bringing hotter summers and because of this fact, the use of air-conditioning systems is also extending in European countries. To reduce the energy demand and consumption of these systems, it is particularly significant to identify further technical solutions for [...] Read more.
Climate change is continuously bringing hotter summers and because of this fact, the use of air-conditioning systems is also extending in European countries. To reduce the energy demand and consumption of these systems, it is particularly significant to identify further technical solutions for direct cooling. In this research work, a field study is carried out on the cooling energy performance of an existing, operating ventilation system placed on the flat roof of a shopping center, located in the city of Eger in Hungary. The running system supplies cooled air to the back office and storage area of a shop and includes an air-to-air rotary heat wheel, a mixing box element, and a direct expansion cooling coil connected to a variable refrigerant volume outdoor unit. The objective of the study was to investigate the thermal behavior of each component separately, in order to make clear scientific conclusions from the point of view of energy consumption. Moreover, the carbon dioxide cross-contamination in the heat wheel was also analyzed, which is the major drawback of this type heat recovery unit. To achieve this, an electricity energy meter was installed in the outdoor unit and temperature, humidity, air velocity, and carbon dioxide sensors were placed in the inlet and outlet section of each element that has an effect on the cooling process. To provide continuous data recording and remote monitoring of air handling parameters and energy consumption of the system, a network monitor interface was developed by building management system-based software. The energy impact of the heat wheel resulted in a 624 kWh energy saving and 25.1% energy saving rate for the electric energy consumption of the outdoor unit during the whole cooling period, compared to the system without heat wheel operation. The scale of CO2 cross-contamination in the heat wheel was evaluated as an average value of 16.4%, considering the whole cooling season. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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Open AccessArticle
Triggering Optimal Control of Air Conditioning Systems by Event-Driven Mechanism: Comparing Direct and Indirect Approaches
Energies 2019, 12(20), 3863; https://doi.org/10.3390/en12203863 - 12 Oct 2019
Cited by 1 | Viewed by 554
Abstract
Real-time optimal control of air conditioning (AC) is important, and should respond to the condition changes for an energy efficient operation. The traditional optimal control triggering mechanism is based on the “time clock” (called time-driven), and has certain drawbacks (e.g., delayed or unnecessary [...] Read more.
Real-time optimal control of air conditioning (AC) is important, and should respond to the condition changes for an energy efficient operation. The traditional optimal control triggering mechanism is based on the “time clock” (called time-driven), and has certain drawbacks (e.g., delayed or unnecessary actions). Thus, an event-driven optimal control (EDOC) was proposed. In previous studies, the part-load ratio (PLR) of chiller plants was used as events to trigger optimal control actions. However, PLR is an indirect indicator of operation efficiency, which could misrepresent the system coefficient of performance (SCOP). This study thus proposes to directly monitor the SCOP deviations from the desired SCOP values. Two events are defined based on transient and cumulative SCOP deviations, which are systematically investigated in terms of energy performance and robustness. The PLR-based and SCOP-based EDOC are compared, in which energy saving and optimal control triggering time are analyzed. Results suggest that SCOP-based EDOC has better energy performance compared with PLR-based EDOC, but the frequent event triggering might happen due to the parameter uncertainty. For actual applications, the SCOP-based EDOC can be recommended when the ideal SCOP model is available with the properly-handled uncertainty. Nevertheless, the PLR-based EDOC could still be a more practical option to replace the traditional TDOC considering its acceptable energy performance and better robustness. Full article
(This article belongs to the Special Issue Evaluation of Energy Efficiency and Flexibility in Smart Buildings)
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