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Assessment and optimisation of energy consumption in building communities using an innovative co-simulation tool
Abstract
Energy efficiency in building sector is attracting an increasing interest in the scientific community, due to its strong impact in terms of greenhouse gas emissions. In this context, the REMOURBAN H2020 project has carried out a pilot deep refurbishing work on a small cluster of 10 homes, implementing energy saving measures and a hybrid energy-supply system to satisfy the heating and domestic hot water demand. The system aims to achieve near-zero-energy homes level of performance at reasonable cost by offsetting the energy consumption with local energy microgeneration. It is designed as a local low temperature district heating system and includes ground source heat pumps, photovoltaic panels, electric and thermal energy storage devices. The management of the complex hybrid system requires a suitable control strategy to optimise the energy consumption and consequently running cost. With this purpose a co-simulation tool has been developed, coupling a model of the energy system built using Dymola-Modelica and the EnergyPlus model of the buildings. This allows to develop different control strategies aiming to reduce the energy consumption from the grid, maximize the self-consumption of photovoltaic energy and ultimately move away from fossil fuel to sustainable energy resources.
... In the past, projects like REMOURBAN have implemented measures such as retrofitting homes, installing ground source heat pumps, thermal storage, batteries, and PV, but have not yet achieved net zero emissions. The previous research conducted by the authors has demonstrated that there is still potential for achieving net zero emissions, even after implementing energy efficient measures such as retrofitting homes, installing ground source heat pumps, thermal storage, batteries, and PV, as the current emissions reduction is at 78% [3,[12][13][14]. The author considers the incorporation of locally generated wind and solar energy as an innovative approach to achieving net-zero emissions (Fig. 2). ...
... The heating system has been completely changed, the gas boilers have been removed, and replaced by a new, low-temperature heating system. The cluster of houses is now configured as a micro-low-temperature district heating (LTDH) network [13,12,26,27]. ...
... Using the co-simulation tool, the authors evaluated the performance of the retrofitted homes. The results demonstrated significant energy consumption reductions post-refurbishment [25]. ...
In developed nations, there's a growing concern for sustainable energy management, particularly regarding enhancing energy efficiency in both existing and new buildings. The methodology presented considers the energy modelling and simulation of manufacturing buildings through thermal and electrical loads calculations using Dymola/Modelica software. The thermal model is built with the primary components of Dymola along with available models to calculate the heating and cooling loads, whereas the electrical model was calculated using consumption patterns, then the total model was validated against real measurements where the error percentage was 9.96 %. The yearly heating load baseline was 6295 kWh/y and for cooling 46276 kWh/y., the exciting potential for energy- savings and load flexibility, and some suggestions for improving consumption were pointed out and identified. It found that the highest influence on the thermal load reduction was using the double glaze with shading with 61% of the energy-saving options, then replacing the fluorescent with LED with 30%, and finally, the roof insulation was the least influence with 9.5%. For the total consumption, the highest percentage was for replacing the fluorescent with LED with 78% of energy-saving options, then double glaze with shading, and finally the lowest is for the roof insulation.
... For example, Díaz Pérez et al. determined that indoor heating and domestic hot water (DHW) in hotel buildings worldwide result in an average CO2 emission of 20.6 kg per overnight stay [9]. Meanwhile, IEA states that approximately 40 % of total CO2 emissions are attributed to residential buildings and the construction sector [7,8,10,11]. Like this, numerous studies highlight the significant carbon footprint from heating and hot water systems in buildings. ...
... • Standard interface coupling: Submodels communicate through a standardized interface for co-simulation, which allows for direct coupling between any software that implements the interface. The Functional Mock-up Interface (FMI) and the High-Level Architecture (HLA) are well-known examples of standardized co-simulation interfaces [50,72,104,105]. Co-simulation standards include rules and specifications for model initialization and synchronization. ...
... Cucca and Ianakiev [60] 2020 Development of the co-simulation tool coupling the model of a building energy system with Dymola/Modelica and EnergyPlus. Co-simulation with EnergyPlus. ...
Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas emissions, which may significantly impact climate change. Heating, ventilation, and air-conditioning (HVAC) systems are among the most significant contributors to global primary energy consumption and carbon gas emissions. Furthermore, HVAC energy demand is expected to rise in the future. Therefore, advancements in HVAC systems’ performance and design would be critical for mitigating worldwide energy and environmental concerns. To make such advancements, energy modeling and model predictive control (MPC) play an imperative role in designing and operating HVAC systems effectively. Building energy simulations and analysis techniques effectively implement HVAC control schemes in the building system design and operation phases, and thus provide quantitative insights into the behaviors of the HVAC energy flow for architects and engineers. Extensive research and advanced HVAC modeling/control techniques have emerged to provide better solutions in response to the issues. This study reviews building energy modeling techniques and state-of-the-art updates of MPC in HVAC applications based on the most recent research articles (e.g., from MDPI’s and Elsevier’s databases). For the review process, the investigation of relevant keywords and context-based collected data is first carried out to overview their frequency and distribution comprehensively. Then, this review study narrows the topic selection and search scopes to focus on relevant research papers and extract relevant information and outcomes. Finally, a systematic review approach is adopted based on the collected review and research papers to overview the advancements in building system modeling and MPC technologies. This study reveals that advanced building energy modeling is crucial in implementing the MPC-based control and operation design to reduce building energy consumption and cost. This paper presents the details of major modeling techniques, including white-box, grey-box, and black-box modeling approaches. This paper also provides future insights into the advanced HVAC control and operation design for researchers in relevant research and practical fields.
... This was achieved by programming a TRNSYS component performing cradle-to-cradle life cycle assessment studies. Cucca et al. [18] developed a co-simulation tool coupling both Dymola-Modelica for energy systems and EnergyPlus building simulations. Communication between simulators had been processed using a FMU block providing, to Dymola, weather data, building heat demand and photovoltaic power production. ...
Building models and their connected subsystems are often simulated as standalone entities. However, in order to monitor a system′s reactions to changing parameters and to assess its energy efficiency, it must be exposed to the actual dynamic context of the building under study. Hence, frameworks assessing co-operative simulation of buildings and their subsystems should be used. In this study, the Building Control Virtual Test Bed (BCVTB) framework was used for co-simulation of a small-scale building (EEBLab) connected to an Earth-to-air heat exchanger (EAHE). The EnergyPlus tool was used to simulate the indoor air temperature variations within the EEBLab, and MATLAB was used to model the EAHE system and to calculate its performance based on various parameters. The HOLSYS internet of things platform was deployed to monitor and collect the experimental data from the sensors to validate the simulations. A favorable agreement between the experimental and simulation results was obtained, showing the contribution of the small-scale EAHE system in maintaining a comfortable indoor temperature range inside EEBLab. Moreover, it demonstrated the effectiveness and accuracy of the proposed approach for integrated building co-simulation and performance evaluation.
... The optimization dimensions show the adopted optimization algorithm by each study and whether its associated optimization problem is single-objective or multiobjective. Evaluation and ranking of building upgrading solutions using parametric analysis and simulation tools Cucca and Ianakiev (2020) Develop control strategies to maximize the use of sustainable energy resources rather than those using fossil fuels using an innovative co-simulation tool ...
Because existing buildings occupy most of our built environment, there is an urgent need to upgrade them considering building sustainability criteria. Therefore, many optimization models were proposed to find the optimum upgrading solution that improves the building sustainability while minimizing its costs using traditional sustainability rating tools [e.g., Leadership in Energy and Environmental Design(LEED) (US), Building Research Establishment Environmental Assessment Methodology (BREEAM) (UK), and others]. The variations among these tools hinder their application outside their original countries, calling for global tools. Therefore, this study contributes to the knowledge by developing a novel multiobjective optimization model to solve the life cycle cost (LCC)-sustainability trade-off for building upgrading using a generic sustainability rating tool. This tool includes seven sustainability criteria and 29 subcriteria, resulting in 134 decision variables. The proposed model finds the near-optimum upgrading solutions that minimize their LCC while improving the building sustainability using the multiobjective artificial immune system algorithm. The model was applied to a real case study of a large building in Montreal, Canada. The obtained solutions covered almost all the ratings ranges from pass to outstanding and showed the trade-offs between the building sustainability and LCC. This research is a step toward adopting a global sustainability rating tool to find the optimum building upgrading solutions that can address the regional limitations of the traditional rating tools.
... Co-simulation has been used for the analysis of systems. Cucca & Ianakiev (2020) coupled a model of a district heating system built using Dymola-Modelica with the EnergyPlus model of the buildings, allowing for the development and evaluation of different control strategies. Hinkelman et al. (2022) present a systematic methodology for Modelica modelling and simulation of district cooling systems. ...
Rapidly developing economies of countries in hot climates face the risk of a significant increase in CO2 emissions. This study developed strategies for low energy cooling and ventilation for Indian residences (LECaVIR). Ventilation and cooling techniques were developed and tested for India’s four climatic zones. The analysis shows that natural ventilation is possible in typical residential buildings for about 20–40% of the year. Using an enhanced natural ventilation mode with appropriately sized openable windows and controls, the total number of hours for which natural ventilation is able to offer satisfactory conditions for occupants can be extended by a further 13 percentage points, leading to a potential reduction of 46% in the mechanical cooling hours for residences. Dynamic thermal simulation models, coupled with control software, were used to test the most promising natural ventilation strategies as part of a mixed-mode approach to ensure year-round comfort at minimal energy cost. The simulation shows that energy savings of up to 55% are possible.
... By using simulation software, the comprehensive energy performance integrating all kinds of energy systems could be simulated to show the energysaving potential after retrofitting. Building energy simulations have been demonstrated to be efficient tools throughout a building's lifecycle to analyze the energy performance in complex scenarios [45][46][47]. By constructing a "typical office building", the researchers characterized the general office in terms of its space, form and thermal properties, which helps to guide energy-efficient design for this type of building. ...
Energy-efficient retrofitting has emerged as a primary strategy for reducing the energy consumption of buildings. Buildings in China account for about 40% of total national energy consumption. Large office buildings account for the most. Less than 5% of the building area of existing office buildings is energy efficient. Energy-efficient retrofitting for sustainable buildings is a complicated system that involves various sustainable dimensions and operational technical schemes. Making multi-criteria decisions becomes a challenging problem for stakeholders. Based on the theory of sustainability, this paper establishes a sustainable analysis framework to guide stakeholders to select an optimal technical combination of energy-efficient retrofit measures for large office buildings. Based on empirical data collected in Beijing, a number of energy efficiency measures are selected, tailored and applied to a virtual model of a typical large office building. Technical features and the energy performance are simulated accordingly. The energy consumption, energy-saving ratio and lifecycle costs are derived to identify the optimal configuration. The outcome of this research offers a feasible technical plan for stakeholders relating to technical design and design making. The study finds that an LED lighting system and frequency conversion device for the cooling water chiller cannot only sufficiently reduce the building’s energy consumption but also perform economically. Different thermal insulation materials for reconstructing the building envelope have no obvious effect on the thermal performance in comprehensive simulations of technology combinations. The sustainable analysis framework offers theoretical and practical support and can be used as a reference for the other types of buildings in future research.
... A co-simulation tool was reported to couple the energy system model by Dymola-Modelica and the building model by EnergyPlus. It aimed to investigate the optimal control of a HAVC system with thermal comfort and minimum energy consumption [20]. Another co-simulation method is built between En-ergyPlus Functional Mockup Units (FMUs) with the Python environment to investigate the operations of the ground source heat pump. ...
In this study, a collaborative simulation method is proposed to predict dynamic variations of the thermal environment in an air-conditioned room. The room thermal environment was predicted and analyzed by varying the structural and control parameters of the air conditioner considering the dynamic coupling effect. Connections and regularities were established between the applicable parameters and evaluation indices of the thermal environment. The simulation results demonstrated the interactions among the system structural parameters, control parameters, and the thermal environment. Within a certain parameter range, the evaporator structure exhibited a significant effect on temperature uniformity and vertical air temperature difference, followed by predicted mean vote (PMV) and draught rate (DR). The associated evaluation indices were sensitive to fin spacing, tube spacing, and tube outer diameter, in the same order, which were structural parameters of the evaporator. The effect of the air supply angle on the vertical air temperature difference was evident; however, its influence on the PMV, DR, and temperature uniformity did not indicate consistent variations.
The construction industry contributes to approximately 30% of global energy consumption and carbon dioxide emissions, necessitating urgent measures to mitigate carbon emissions and address climate problems. This study focuses on the underexplored realm of Non-domestic Building Stock (NDBS), which constitutes 8% of global energy consumption and 11% of worldwide carbon emissions. Due to the long lifecycle of buildings, a comprehensive assessment of the NDBS is imperative to achieve the goal of net-zero carbon buildings by 2050. The current NDBS studies can be categorised into two groups based on the geographic location and type of building being studied. Each of these two different building stocks demonstrates different research and analysis tools, but specific comparisons have not yet been made between them. In addition, existing literature reviews of NDBS have mainly emphasised the technical aspects and neglected their social aspects. This study aims to critically review the energy and carbon footprint related efforts in NDBS research, assess the current state of research, and propose potential research trends. Based on inclusion and exclusion criteria, 99 out of 906 articles are fully reviewed. Utilising and adapting the Social-Technical Systems (STS) approach, this study analyses the data requirements, research methods, and research objectives of NDBS studies concerning energy consumption and carbon footprint from five perspectives, namely infrastructure, technology, processes, goals, and people. Results demonstrate that geo-stock and type-stock approaches, while focusing on different aspects of building stock, can share data and analysis methods to improve research efficiency and model accuracy. Additionally, findings highlight that incorporating socio-economic factors into technical models can enhance model robustness and output reliability, thereby supporting effective policy-making and energy management strategies. This study provides a new multidimensional approach to evaluate the development of NDBS energy and carbon footprint research, and helps to incorporate socio-economic analysis into NDBS physics-based models to improve the efficiency and reliability of such models for future research and practice.
Building energy simulations can be effective in the real world only if the building energy model is appropriately tuned, i.e., calibrated. Whatever the purpose, from detailed energy design to energy audits or HVAC system control strategies, building energy simulations can provide accurate results only if the energy model itself is accurately developed. The aim of this article is to review and analyze the current methodologies and approaches used when assessing building energy performance through simulations, focusing on the need for a calibrated model to enhance the simulation’s credibility. This literature review identifies novel and practical methodologies, focusing on data collection, energy modeling approaches, simulation software, and calibration techniques. Although several studies have focused on building energy simulation, partially covering the topics addressed in this review, a detailed analysis and comparison of methods through normalized scores to derive possible recurrences and reproducible methods have not yet been presented.
Article access: https://authors.elsevier.com/a/1ietP8MyS96b8z
Implementing an efficient control strategy for heating, ventilation, and air conditioning (HVAC) systems can lead to improvements in both energy efficiency and thermal performance in buildings. As HVAC systems and buildings are complicated dynamic systems, the effectiveness of both data-driven and model-based control methods has been widely investigated by researchers. However, the main challenges that impede the practical application of model-based methods in real buildings are their reliance on the precision of control-oriented models and the dependence of data-based systems on the quantity and quality of input–output data. The objectives of this study are: (1) To present an overview of the prevalent thermal modelling strategies used as control-oriented models or virtual environments in model-based and data-based control methods, addressing the main requirements of thermal models; (2) the state-of-the-art of MPC and RL control techniques; (3) the data requirements for thermal models. The findings emphasise the need for unified guidelines to validate and verify the proposed control methods, ensuring their practical implementation in real buildings. Moreover, the inclusion of occupancy forecasts in models presents challenges due to the intricate nature of accurately predicting human behaviour, occupancy patterns, and their effects on thermal dynamics. Balancing thermal comfort and energy efficiency in HVAC systems with a supervisory controller remains a difficult task, but combining data-driven and physics-based models can help overcome challenges. Further research is needed to compare the effectiveness of MPC and RL approaches, and accurately measuring the impact of human behaviour and occupancy remains a significant obstacle.
Current approaches for simulating the energy performance of buildings on a large scale are limited by numerous assumptions and simplifications, which can lead to inaccurate estimations. While new tools and procedures are emerging to improve accuracy, there remains a need for more user-friendly methods. This study proposes a new tool based on online maps to create the geometry of districts in a simple way. The tool also enables an automatic evaluation of all buildings through dynamic hourly simulations, using a building simulation software and allowing to consider different weather conditions. To illustrate the procedure, a district at risk of energy poverty in Seville (Spain) is modeled, where hourly temperature data for a whole year are available to demonstrate the need for building improvements. The tool is used to evaluate the energy demands of the district under several retrofitting alternatives, and free-floating simulations are also performed to evaluate the improvement of thermal comfort without air-conditioning systems. The aim is not to discuss the actual values for this particular case, but rather to identify the correct direction for large-scale studies, so as to make them more easily conducted. Overall, it may be concluded that the results provided by comprehensive tools, such as the one proposed in this study, enable easy yet accurate evaluations of buildings on a large scale with significant time savings, as well as the identification of locations where retrofitting interventions would have the greatest impact.
Green building is a concept in sustainable development which aims to reduce energy consumption and carbon emission of buildings. This study attempts to design and introduce a novel green HVAC system which reduces both energy consumption and carbon production of buildings. This system uses solar absorption chillers to provide the cooling demands of buildings. In addition, biofuel (biogas) fired boilers are also added to provide the heating demands. By using the novel approach of the study, such HVAC system can be coupled with other renewable technologies like photovoltaics and develop green buildings. In order to design, model and simulate the operation of this system, famous energy modeling tools are compared with each other and Design Builder software is chosen as the appropriate one. The paper also introduces a plan for establishment of such systems which is applicable to any locations. The results of modeling this green HVAC system for 10 various climates indicated considerable advantages of this system over traditional systems. The green HVAC system can save the maximum energy of 50 MWh per year in a four stories building. The maximum amount of 31 tons carbon can also be saved if the said building is equipped with this novel HVAC system. The results also made it clear that the solar cooling system is a great choice for providing cooling needs in hot climates. By coupling this kind of cooling system with biofuel heaters, the sustainable HVAC system can develop green buildings even in cold or cool climates. Adding green electricity producers like photovoltaic panels to this system and the building was successful. The maximum produced green energy in buildings was calculated as the amount of 17.9 MWh/yr.
In the low-carbon transition process of urban energy systems, synergistic planning with different sectors faces challenges in terms of modeling complexity, optimization accuracy and computational cost due to inconsistent granularity of models and methods. This study proposes a hierarchical coupled optimization method for cross-sectoral synergistic planning for supply and demand sides of urban energy systems. It integrates thermal load simulation of different demand-side energy-saving retrofits based on state space method with mixed integer linear programming of whole energy systems. This method enables reduced-order description of the time-varying multidimensional process while preserving the dynamic characteristics of demand-side to solve the problems of precision and scale difference in simulation and optimization. The case study shows that the optimal demand-side strategy enables 48.20% building energy-saving, while the optimal supply-side technology enables 36.77% emission reduction throughout the year. The emission reduction rate of the whole systems can be further increased by 6.16%∼30.42% after the combination of passive and active energy-saving means. Meanwhile, compared with the baseline scenario, the synergistic optimization solutions in this case results in a 24.22% decrease in net present value of cost and a 50.35% decrease in total carbon emission. This means that the energy-saving and emission reduction potential of the integrated systems can be further exploited through the integration of multiple building retrofit strategies and renewable technologies. This hierarchical approach helps to design effective cross-sector synergistic solutions that achieve a reasonable trade-off of economic benefits and environmental sustainability of the whole systems. Overall, this study integrates different models and approaches of the supply and demand sectors to provide flexible and integrated solutions for low-carbon design and operation management of urban energy systems with building energy-saving retrofit.
The development of deep learning (DL) technology provides an opportunity for accurate prediction and effective control of complex building systems. However, despite the high prediction performance of the DL models, few studies integrate DL with the model predictive control (MPC) algorithm for improving building management. In this study, a DL-based MPC framework using encoder-decoder recurrent neural network is developed for real-time control of building thermal environment to exploit the advantage of both DL and MPC algorithms. In addition, to simulate the dynamic interaction between indoor airflow and HVAC systems, a co-simulation platform by integrating HVAC simulator and CFD model is developed to provide an effective solution for evaluating the proposed building control strategy. Two case studies including a confined space with mixing ventilation and an office room subjected to solar radiation are used for validation of the proposed method. The performance of the DL-based MPC algorithm for building thermal environment control is compared with the traditional proportion-integration-differentiation (PID) controller and the adaptive PID controller. Approximately 4% and 7% energy savings are achieved on average through DL-based MPC compared with the conventional PID control and adaptive PID control respectively. Our study demonstrates that the proposed DL-based MPC framework has significant application potential for building automation and control by exploiting the advantage of both deep learning and MPC algorithms.
Sustainable building renovation is an important way to address energy and environmental problems. The paper uses CiteSpace, a visualized method to present a literature review based on 1090 papers from Web of Science core collection database. Overall, it analyzes the trends in the number of papers, contributing authors, countries and journals. Besides, it employs document citation analysis, keywords and time zone analysis to explore the hotspots and frontier topics. The results show that:1) There are many isolated nodes in the networks of authors and countries, indicating that the cooperation in the field is still insufficient; 2) The most cited papers mainly focus on technology of building renovation, energy efficiency of building retrofit and decision making for building retrofit; 3) Renovation building performance is the hottest research issues, followed by model and energy efficiency; 4) In general, the research frontiers evolve from technology (building information extracting and modeling) to management issues (mainly include human experience, multi-objective optimization and multi-participant interests). Accordingly, some suggestions for further research are put forward.
The accurate simulation of energy performance is fundamental to design low energy buildings – newly-built or after refurbishment – and thus to promote sustainability. However, this is an involved task requiring high complexity in modeling and simulation. Most accurate building energy simulation tools are not user-friendly for building professionals, thereby hindering a widespread use of effective methodologies – developed by researchers – for the transition to nearly- or net-zero energy buildings. This study tries to solve such an issue by proposing a novel, accurate but user-friendly tool for building modeling and energy simulation. The tool is denoted as EMAR because it is based on the advanced coupling between ENergyplus and MAtlab® addressing Residential buildings, which are a major part of the existing stocks. EMAR completely works under MATLAB® environment and only needs around 60 numerical inputs to generate simplified building models and perform accurate energy simulations. The available outputs are numerous referring to energy and economic performance as well as thermal comfort. No drawings, no schemes of energy systems, no deep modeling expertise are required but only few numbers. EMAR is validated against detailed EnergyPlus models of an ASHRAE test building and of two typical European buildings. The discrepancies are lower than 10% as concerns thermal and primary energy needs, and in most cases are lower than 5%, but the modeling complexity and computational burden are drastically reduced. Thus, EMAR can be a precious tool to perform user-friendly but accurate building energy modeling and simulations.
Accurate prediction of building energy consumption is crucial for building energy management. However, the building energy consumption is affected by many factors and shows obvious nonlinear characteristics in the time series, which is difficult to predict. In this work, a novel hybrid model is proposed for predicting short-term building energy consumption. In this model, the raw data is decomposed into multiple smooth datasets using complete ensemble empirical mode decomposition with adaptive noise, and the building energy consumption is predicted by the traditional extreme gradient boosting. Taking the daily energy consumption of the City of Bloomington Intake Tower as the simulation object, the results show that the mean absolute percentage error of the proposed model is 4.85%, which is much lower than that of five benchmark models. The proposed model is also applied to the prediction of other parameters related to the energy consumption of the intake tower, and shows good prediction performance. Moreover, the influences of the sliding window length and data attributes on the prediction results are also discussed.
Nowadays, there is growing interest in all the smart technologies that provide us with information and knowledge about the human environment. In the energy field, thanks to the amount of data received from smart meters and devices and the progress made in both energy software and computers, the quality of energy models is gradually improving and, hence, also the suitability of Energy Conservation Measures (ECMs). For this reason, the measurement of the accuracy of building energy models is an important task, because once the model is validated through a calibration procedure, it can be used, for example, to apply and study different strategies to reduce its energy consumption in maintaining human comfort. There are several agencies that have developed guidelines and methodologies to establish a measure of the accuracy of these models, and the most widely recognized are: ASHRAE Guideline 14-2014, the International Performance Measurement and Verification Protocol (IPMVP) and the Federal Energy Management Program (FEMP). This article intends to shed light on these validation measurements (uncertainty indices) by focusing on the typical mistakes made, as these errors could produce a false belief that the models used are calibrated.
This paper is based on a recently completed feasibility research – report of the Passivhaus standard retrofitting innovation activities – for the EU Horizon 2020 project REMOURBAN (REgeneration MOdel for accelerating the smart URBAN transformation). REMOURBAN is a major Future Cities demonstrator project supported by an investment of EU Lighthouse project scheme [1]. A block of terraced houses, which is one of the eight archetypes to be retrofitted at Nottingham demo site, will be cost-effectively retrofitted to a high energy-efficiency standard. Both static and dynamic simulation results play important roles in identifying appropriate retrofit standards and practice to achieve expected energy savings for such a major investment project. This paper aims to explore the building simulation effect on predicting the improvement potential in terms of energy savings under various refurbishment scenarios in the early project stage. The current feasibility study ushers the next project phases of implementation and real-time field monitoring, when detailed simulations are also expected to play important roles.
The development of adaptive building envelope technologies, and particularly of switchable glazing, can make significant contributions to decarbonisation targets. It is therefore essential to quantify their effect on building energy use and indoor environmental quality when integrated into buildings. The evaluation of their performance presents new challenges when compared to conventional “static” building envelope systems, as they require design and control aspects to be evaluated together, which are also mutually interrelated across thermal and visual physical domains.
In this paper, a rural residential model located in Shenyang is established by simulation software DesignBuilder. Simulation process is divided into the following conditions, variety of thermal performance walls, roofs and windows. Building energy consumption was simulated through EnergyPlus under different conditions. The information of EnergyPlus and modelling process are referred. Impact of envelope heat consumption for various thermal performance and the energy saving potential are analysed. This research provides technical support and theoretical guidance for new energy efficient building and renovation projects.
Fast-growing carbon emissions from the residential building sector are a hindrance for China to achieve its 2030 emission peak goal. To identify future low carbon roadmaps of residential buildings, this study is the first to assess the historical carbon mitigation and simulate the energy and emission peaks of China’s residential building sector using a dynamic emission scenario. It shows that the emission mitigation of the residential building sector during 2000–2015 is 1.817 (± 0.643) billion tons of carbon dioxide (BtCO2), and the normal distribution-based scenario simulation demonstrates that the residential building sector will achieve its carbon emission peak in 2037 (± 4) with a peak value of 1.419 (± 0.081) BtCO2. The sensitivity analysis reveals that the impacts of floor space per capita and energy intensity of urban residential buildings are the most significant for the uncertainty of emission peaks. A strict energy demand benchmark of the residential building sector suggests a control at 0.661 billion tons of standard coal equivalent (Btce), and its peaking time is estimated for 2035, which is 5 years ahead of the business-as-usual scenario, with energy savings of 0.042 Btce. For the earliest peaking time, if the residential building sector aims to achieve its emission peak before 2030, the emission peak should be controlled at 1.258 BtCO2. Overall, this paper can assist the government in more accurate and feasible building emission mitigation strategies. Moreover, the results provide a more powerful decision-making reference in issuing targeted and feasible strategies for future residential building emission mitigation.
Building activity is the sector that affects for the most part the anthropogenic climate change. Indeed, even if differences can be found among countries, according to the level of development and climates, buildings require about 30–40% of the overall energy demand, with similar share concerning the greenhouse emissions. According to the more recent EU Directives in matter of energy efficiency in energy use, a great attention has to be paid to energy refurbishments of existing buildings. Indeed, the turnover rate of the EU building stock is generally low in fully-developed countries, so that the energy retrofits are also more important compared to new nearly zero-energy buildings. The proposed investigation concerns the demonstrative role of the public hand, whose necessity is underlined by the EU Directives 2010/31/EU and 2012/27/EU, through a multi-step and multi-objective optimization of an educational building of an Italian University. All preliminary investigations aimed at a reliable modelling, the iterative method that combines genetic algorithms and transient energy simulations tailored on calibrated numerical models make the investigation complete and repeatable. All levers of energy efficiency have been pressed, and thus the refurbishment of building envelope, HVAC systems, integration of energy supply by renewables. The multi objective optimisation concerns costs, incentives, indoor comfort, energy demands for heating and cooling and a novel approach is proposed for choosing the best configuration of retrofit. It is resulted that the most profitable energy efficiency measures involve the modernization of energy systems, even if also the retrofit of the building envelope can be profitable under favourable financial conditions. The cost-effective refurbishment reduces the primary energy demand up to a value of 12 kWh/m²a, so that the building can be surely considered as nZEB.
How to predict building energy performance with low computational times and good reliability? The study answers this question by employing artificial neural networks (ANNs) to assess energy consumption and occupants' thermal comfort for any member of a building category. Two families of ANNs are generated: the first one addresses the existing building stock (as is), the second one addresses the renovated stock in presence of energy retrofit measures (ERMs). The ANNs are generated in MATLAB® by using the outcomes of EnergyPlus simulations as targets for networks' training and testing. A preliminary ‘Simulation-based Large-scale sensitivity/uncertainty Analysis of Building Energy performance’ (SLABE) is conducted to optimize the ANNs' generation. It allows to identify the networks' inputs and to properly select the ERMs. The developed ANNs can replace standard building performance simulation tools, thereby producing a substantial reduction of computational efforts and times. This can allow a wide diffusion of rigorous approaches for retrofit design, which are currently hampered by the excessive computational burden. As case study, office buildings built in South Italy during 1920–1970 are investigated. Comparing the ANNs' predictions with EnergyPlus targets, the regression coefficient is between 0.960 and 0.995 and the average relative error is between 2.0% and 11%.
The low energy retrofit of the UK existing building stock is an urgent matter after the government’s commitment to reduce carbon emissions by 80% until 2050. This research addressed the question of whether it is preferable to refurbish in an extensive way or to choose a retrofit strategy with lower capital cost, embodied energy and CO2, tackling issues of cost-effectiveness, embodied and operational energy throughout the lifecycle of an existing Victorian house in London. The indicator Cost per Ton carbon Saved (CTS) was used, which resulted in higher values for the EnerPHit retrofit model, rendering it a less viable alternative. It was also concluded that retrofitting, in general and especially the application of EnerPHit, is an appealing option only with rising gas prices, low discount rates and long lifespans. Those results were even more amplified when climate change was taken into account, a conclusion very important for the application of future legislation and the possible transfer of this study to other climates. It was deduced that a house’s remaining lifetime is a very significant factor to be taken into account, as investments of higher capital cost give higher benefit in long term.
Efficient HVAC devices are not sufficient to achieve high levels of building energy performance, since the regulation/control strategy plays a fundamental role. This study proposes a simulation-based model predictive control (MPC) procedure, consisting of the multi-objective optimization of operating cost for space conditioning and thermal comfort. The procedure combines EnergyPlus and MATLAB®, in which a genetic algorithm is implemented. The aim is to optimize the hourly set point temperatures with a day-ahead planning horizon, based on forecasts of weather conditions and occupancy profiles. The outcome is the Pareto front, and thus the set of non-dominated solutions, among which the user can choose according to his comfort needs and economic constraints. The critical issue of huge computational time, typical of simulation-based MPC, is overcome by adopting a reliable minimum run period. The procedure can be integrated in building automation systems for achieving a real-time optimized MPC. The methodology is applied to a multi-zone residential building located in the Italian city of Naples, considering a typical day of the heating season. Compared to a standard control strategy, the proposed MPC generates a reduction of operating cost up to 56%, as well as an improvement of thermal comfort.
Retrofitting of existing buildings offers significant opportunities for reducing global energy consumption and greenhouse gas emissions. This is being considered as one of main approaches to achieving sustainability in the built environment at relatively low cost and high uptake rates. Although there are a wide range of retrofit technologies readily available, methods to identify the most cost-effective retrofit measures for particular projects is still a major technical challenge. This paper provides a systematic approach to proper selection and identification of the best retrofit options for existing buildings. The generic building retrofit problem and key issues that are involved in building retrofit investment decisions are presented. Major retrofit activities are also briefly discussed, such as energy auditing, building performance assessment, quantification of energy benefits, economic analysis, risk assessment, and measurement and verification (M&V) of energy savings, all of which are essential to the success of a building retrofit project. An overview of the research and development as well as application of the retrofit technologies in existing buildings is also provided. The aim of this work is to provide building researchers and practitioners with a better understanding of how to effectively conduct a building retrofit to promote energy conservation and sustainability.
In this study, various energy conservation measures (ECMs) on heating, ventilating and air conditioning (HVAC) and lighting systems for a four-storied institutional building in sub-tropical (hot and humid climate) Queensland, Australia are evaluated using the simulation software called DesignBuilder (DB). Base case scenario of energy consumption profiles of existing systems are analysed and simulated first then, the simulated results are verified by on-site measured data. Three categories of ECMs, namely major investment ECMs (variable air volume (VAV) systems against constant air volume (CAV); and low coefficient of performance (COP) chillers against high COP chillers); minor investment ECMs (photo electric dimming control system against general lighting, and double glazed low emittance windows against single-glazed windows) and zero investment ECMs (reset heating and cooling set point temperatures) are evaluated. It is found that the building considered in this study can save up to 41.87% energy without compromising occupancies thermal comfort by implementing the above mentioned ECMs into the existing system.
Directive (EU) 2018/2002 OF the EUROPEAN parliament and of the council
- European Commission
Energy efficiency of buildings: a nearly zero-energy future?
- Sajn
DesignBuilder Software Ltd - Home
- Ltd Designbuilder Software
The Government’s standard assessment procedure for energy rating of dwellings
- BRE