Uncertainty-based life-cycle analysis of near-zero energy buildings for performance improvements

Near-zero energy buildings( nZEBs) are considered as an effective solution to mitigating CO_2 emissions and reducing the energy usage in the building sector. A proper sizing of the nZEB systems( e. g. HVAC systems,energy supply systems,energy storage systems, etc.) is essential for achieving the desired annual energy balance,thermal comfort,and grid independence. Two significant factors affecting the sizing of nZEB systems are the uncertainties confronted by the building usage condition and weather condition,and the degradation effects in nZEB system components. The former factor has been studied by many researchers; however,the impact of degradation is still neglected in most studies. Degradation is prevalent in energy components of nZEB and inevitably leads to the deterioration of nZEB life-cycle performance. As a result,neglecting the degradation effects may lead to a system design which can only achieve the desired performance at the beginning several years. This paper,therefore,proposes a life-cycle performance analysis( LCPA) method for investigating the impact of degradation on the longitudinal performance of the nZEBs. The method not only integrates the uncertainties in predicting building thermal load and weather condition,but also considers the degradation in the nZEB systems. Based on the proposed LCPA method,a two-stage method is proposed to improve the sizing of the nZEB systems.The study can improve the designers "understanding of the components"degradation impacts and the proposed method is effective in the life-cycle performance analysis and improvements of nZEBs. It is the first time that the impacts of degradation and uncertainties on nZEB LCP are analysed. Case studies showthat an nZEB might not fulfil its definition at all after some years due to component degradation,while the proposed two-stage design method can effectively alleviate this problem.

eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

Building energy performance is a function of numerous building parameters.In this study,sensitivity analysis on twenty parameters is performed to determine the top three parameters that have the most significant impact on the energy performance of buildings.Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in the Quick Energy Simulation Tool(eQUEST).The model is calibrated using the Normalized Mean Bias Error(NMBE)and Coefficient of Variation of Root Mean Square Error(CV(RMSE))method.The model satisfies the NMBE and CV(RMSE)criteria set by the American Society of Heating,Refrigeration,and Air-Conditioning(ASHRAE)Guideline 14,Federal Energy Management Program(FEMP),and International Performance Measurement and Verification Protocol(IPMVP)for building energy model calibration.The values of the parameters are varied in two levels,and then the percentage change in output is calculated.Fractional factorial analysis on eight parameters with the highest percentage change in energy performance is performed at two levels in a statistical software JMP.For building A,the top 3 parameters from the percentage change method are:Heating setpoint,cooling setpoint and server room.From fractional factorial design,the top 3 parameters are:heating setpoint(p-value=0.00129),cooling setpoint(p-value=0.00133),and setback control(p-value=0.00317).For building B,the top 3 parameters from both methods are:Server room(pvalue=0.0000),heating setpoint(p-value=0.00014),and cooling setpoint(p-value=0.00035).If the best values for all top three parameters are taken simultaneously,energy efficiency improves by 29%for building A and 35%for building B.

Effect of building energy efficiency standards on carbon emission efficiency in commercial buildings

The building sector plays a crucial role in the worldwide shift toward achieving net-zero emissions.Building energy efficiency standards(BEESs)are highly effective policies for reducing carbon emissions.Therefore,exploring the provincial variations in carbon emission efficiency(CEE)in the building sector and identifying the effect of BEESs on CEE is crucial.This study focuses on commercial buildings in China and applies a difference in differences model to evaluate the impact of BEESs on the CEE of commercial buildings.The slacks-based measure–data envelopment analysis model is employed to assess the CEE of commercial buildings in 30 Chinese provinces from 2000 to 2019.Furthermore,heterogeneous tests are used to explore how climate characteristics and economic conditions affect the efficiency of BEESs.The results indicate that BEESs positively influence the CEE of commercial buildings.Specifically,a 1%increase in the intensity of BEESs causes a 0.1484%increase in the CEE of commercial buildings.Moreover,the impact of BEESs is particularly pronounced in the southern and western provinces.This study provides valuable scientific evidence for governments to enhance BEESs implementation.

Low-Cost Insulation for Energy Efficient Buildings in Terai Region of Nepal

There is a huge amount of energy savings potential in public building sector that has yet to be realized.By prioritizing energy efficiency in its own buildings and thus promoting the development of required knowledge in terms of new technology and construction methods,the public sector will lead the way in efforts to increase the rate of renovations.The low-cost insulation strategies and a comparison of cost with existing insulation materials has been described in this study.We have repeatedly faced energy crises and will continue to do so in the future if appropriate action is not taken in a timely manner.Properly implementing energy-saving initiatives in for achieving thermal comfort in buildings as well as reducing the energy costs would undoubtedly inspire the residential sector,resulting in significant reductions in energy usage.Simulations were carried out to study insulation layers on various building components like exterior walls,floor and roofs,generating different scenarios for a building as a base model,which were then compared and analysed to verify the literature used to develop the cases.The proposed recommendations,which have been validated,are certain to increase building energy efficiency,achieve thermal comfort in low cost than what is currently being used.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.

A New Dynamic and Vertical Photovoltaic Integrated Building Envelope for High-Rise Glaze-Facade Buildings

Substantially glazed facades are extensively used in contemporary high-rise buildings to achieve attractive architectural aesthetics.Inherent conflicts exist among architectural aesthetics,building energy consumption,and solar energy harvesting for glazed facades.In this study,we addressed these conflicts by introducing a new dynamic and vertical photovoltaic integrated building envelope(dvPVBE)that offers extraordinary flexibility with weather-responsive slat angles and blind positions,superior architectural aesthetics,and notable energy-saving potential.Three hierarchical control strategies were proposed for different scenarios of the dvPVBE:power generation priority(PGP),natural daylight priority(NDP),and energy-saving priority(ESP).Moreover,the PGP and ESP strategies were further analyzed in the simulation of a dvPVBE.An office room integrated with a dvPVBE was modeled using EnergyPlus.The influence of the dvPVBE in improving the building energy efficiency and corresponding optimal slat angles was investigated under the PGP and ESP control strategies.The results indicate that the application of dvPVBEs in Beijing can provide up to 131%of the annual energy demand of office rooms and significantly increase the annual net energy output by at least 226%compared with static photovoltaic(PV)blinds.The concept of this novel dvPVBE offers a viable approach by which the thermal load,daylight penetration,and energy generation can be effectively regulated.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Post-war Sustainability-Driven School Buildings: A Review of the Literature

The Safe Schools Declaration of 2015 is an inter-governmental political agreement signed by several countries designed to protect the schooling of the school-aged population during armed conflicts.Yet,in countries where civil war erupted,schools were demolished.Several school-aged children were either forcibly recruited by governments or coerced by rebel groups to serve in armed fights.As a result,several children were deprived of their education and have remained suffering from deep psychological scars.The central question of the study is:What kind of sustainability-driven school buildings can be initiated in countries that are now enduring peace so that the learning environments are more comfortable and improve the well-being of the war-impacted children and school employees?After reviewing the literature,a strategic conceptual framework that incorporated the synergistic relationship between economic,social,and environmental aspects of sustainability was initiated to map out sustainable school buildings.In short,the conceptual framework proposed to construct school buildings in some of the war-affected developing countries includes assembling cost-efficiency and eco-effectiveness inputs,using renewable energy sources powered by natural sunlight,collecting rainwater in mud cisterns,reducing emissions of carbon oxides,and empowering the local community to be the main actors to design sustainable buildings during the preconstruction,construction,and post-construction stages to serve as learning spaces for the war-affected occupants and their neighborhoods.

Integrating Virtual Reality and Energy Analysis with BIM to Optimize Window-to-Wall Ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall Ratio (WWR), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWR, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWR and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual Reality (VR), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

Application of Key Technologies in Green School Buildings: Taking Sino-German Future City Primary School as an Example

Green building is a manifestation of the response to the national“dual carbon”strategy.With the large-scale promotion of green buildings,the country has successively issued multiple evaluation standards for green buildings.Schools are places for preaching,teaching,and solving doubts,and the campus environment plays an important role in improving students’learning efficiency and promoting their physical and mental health.This article is based on the“Green Building Evaluation Standards”GB/T 50378-2019,analyzing and exploring the integration and application of key technologies in green schools,providing reference for green building designers.

Plus Energy Buildings:A Numerical Case Study

The feasibility of Plus Energy Building for a sample relevant case is investigated.After a literature review aimed to identify key aspects of this type of buildings,a preliminary evaluation of the thermal performance of a building constructed using conventional material is presented together with a parametric analysis of the impact of typical influential parameters.Solar domestic hot water(SDHW)and photovoltaic systems(PV)are considered in the study.Numerical simulations indicate that for the examined sample case(Beirut in Lebanon)the total annual energy need of conventional building is 87.1 kWh/y.m^(2).About 49%of energy savings can be achieved by improving the building envelope and installing energy efficient technologies.Moreover,about 90%of energy savings in domestic hot water production can be achieved by installing a SDHW system composed of two solar collectors connected in series.Finally,the addition of a grid connected PV array system can significantly mitigate the energy needs of the building leading to an annual excess of energy.

Deep Learning for Multivariate Prediction of Building Energy Performance of Residential Buildings

In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest energy.Therefore,effective design and planning for estimating heating load(HL)and cooling load(CL)for energy saving have become paramount.In this vein,efforts have been made to predict the HL and CL using a univariate approach.However,this approach necessitates two models for learning HL and CL,requiring more computational time.Moreover,the one-dimensional(1D)convolutional neural network(CNN)has gained popularity due to its nominal computa-tional complexity,high performance,and low-cost hardware requirement.In this paper,we formulate the prediction as a multivariate regression problem in which the HL and CL are simultaneously predicted using the 1D CNN.Considering the building shape characteristics,one kernel size is adopted to create the receptive fields of the 1D CNN to extract the feature maps,a dense layer to interpret the maps,and an output layer with two neurons to predict the two real-valued responses,HL and CL.As the 1D data are not affected by excessive parameters,the pooling layer is not applied in this implementation.Besides,the use of pooling has been questioned by recent studies.The performance of the proposed model displays a comparative advantage over existing models in terms of the mean squared error(MSE).Thus,the proposed model is effective for EPB prediction because it reduces computational time and significantly lowers the MSE.

Determination of Effectiveness of Energy Management System in Buildings

Building Energy Management Systems(BEMS)are computer-based systems that aid in managing,controlling,and monitoring the building technical services and energy consumption by equipment used in the building.The effectiveness of BEMS is dependent upon numerous factors,among which the operational characteristics of the building and the BEMS control parameters also play an essential role.This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS.The simulation tool gives the user the flexibility to understand the potential energy savings by employing specific BEMS control and help in making intelligent decisions.The simulation is developed using Visual Basic Application(VBA)in Microsoft Excel,based on discrete-event Monte Carlo Simulation(MCS).The simulation works by initially calculating the energy required for space cooling and heating based on current building parameters input by the user in the model.Further,during the second simulation,the user selects all the BEMS controls and improved building envelope to determine the energy required for space cooling and heating during that case.The model compares the energy consumption from the first simulation and the second simulation.Then the simulation model will provide the rating of the effectiveness of BEMS on a continuous scale of 1 to 5(1 being poor effectiveness and 5 being excellent effectiveness of BEMS).This work is intended to facilitate building owner/energy managers to analyze the building energy performance concerning the efficacy of their energy management system.

Benchmarking of energy efficiency standards for residential buildings in China

In order to benchmark the energy efficiency standards for residential buildings in China,the Hong Kong building environment assessment method（HK-BEAM）is chosen as the compliance criteria for assessment.The annual energy consumption and the overall thermal transfer value（OTTV）of a baseline residential building prescribed in the Chinese codes and the HK-BEAM are evaluated and compared by the energy budget approach.The results show that in the Chinese codes,the OTTV of the residential building is lower,but the annual energy consumption and the cooling load are higher than those in the HK-BEAM.The annual energy use difference amounts to 13.4%.All the compliance criteria except the ventilation rate and the equipment power in the Chinese codes are set higher than those in the HK-BEAM.However,the compliance criteria of the ventilation rate and the equipment power,especially the ventilation rate,result in much energy consumption,which ultimately induces a high energy budget for residential buildings.

Optimum Energy Management of the Central Air-Conditioning System in Intelligent Buildings

An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.

Analyses of influence of residential buildings' space organization on heating energy consumption in Lhasa

The heating load simulation models of the residential buildings in Lhasa are established for enhancing the space organization’s adaptability to climate and radiation and improving its energy saving performance.The space organization items a e analyzed for both the existing buildings without insulation and new buildings with good insulation.The items include orientation design,south a d north balcony design,the north and south partition wall’s position design,storey height design and window-wall ratio design.Simulation results show that orientation is the key design element for energy saving design,and adverse orientation can obviouslyincrease heating energy consumption;south and north balconies can reduce winter heating energy consumption;partition walls move to the north,which means that the south room’s big depth design leads to less heating energy consumption,but the effect is not inconspicuous;smaier storey height results in less heating load.For the existing buildings,the window-wall ratio of south side has a balance point for energy saving design in the calculation condition.For the new buildings with good insulation,enlarging the south window-wal ratio can continuously reduce heating energy consumption,but the energy saving rate between models gets smaier.The heating energy consumption comparison study between the common model and optimal space design model demonstrates that the energy saving design can significantly reduce heating energy consumption

Energy consumption prediction model of typical buildings in hot summer and cold winter zone of China

To overcome the shortcomings of the energyconsumption prediction models in the application during thedesign stage, a quick prediction model for energy consumptionis proposed based on the decoupling method. Taking typicalresidential and office buildings in hot summer and cold winterzones as research objects, the influence factors on buildingenergy consumption are classified into intrinsic factors andoperational factors on the basis of the heat transfer principle.Then, using the intrinsic factors as the fundamental variablesand operational factors as the modified variables, the quickprediction model for the buildings in typical cold and hot zonesis proposed based on the decoupling method and the accuracyof the proposed model is verified. The results show thatcompared to the simulation results of EnergyPlus, the relativeerror of the prediction model is less than 1.5% ; comparedwith the real operating data of the building, the relative erroris 13.14% in 2011 and 8.56% in 2012 due to the fact that thecoincidence factor becomes larger than the design value about16% in 2011 and 13% in 2012. The finding reveals that theproposed model has the advantages of rapid calculationcompared with EnergyPlus and Design Builder when predictingbuilding energy consumption in building designs. The energyconsumption prediction model is of great practical value inoptimal operation and building designs.

Low Carbon Building Design Optimization Based on Intelligent Energy Management System

The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.

Modeling and optimization of a multi-carrier renewable energy system for zero-energy consumption buildings

For the carbon-neutral,a multi-carrier renewable energy system(MRES),driven by the wind,solar and geothermal,was considered as an effective solution to mitigate CO2emissions and reduce energy usage in the building sector.A proper sizing method was essential for achieving the desired 100%renewable energy system of resources.This paper presented a bi-objective optimization formulation for sizing the MRES using a constrained genetic algorithm(GA)coupled with the loss of power supply probability(LPSP)method to achieve the minimal cost of the system and the reliability of the system to the load real time requirement.An optimization App has been developed in MATLAB environment to offer a user-friendly interface and output the optimized design parameters when given the load demand.A case study of a swimming pool building was used to demonstrate the process of the proposed design method.Compared to the conventional distributed energy system,the MRES is feasible with a lower annual total cost(ATC).Additionally,the ATC decreases as the power supply reliability of the renewable system decreases.There is a decrease of 24%of the annual total cost when the power supply probability is equal to 8%compared to the baseline case with 0%power supply probability.

Investigation the Correlation between Thermal Bridging and Geometries in Concrete Buildings

This article focuses on the investigation of the correlation between thermal bridging and various geometric configurations. The article employs QuickField software for conducting three-dimensional steady-state heat transfer simulations to investigate the thermal behaviors of diverse geometric shapes. Significantly, this study involves the simulation of four distinct geometries including concrete circular, square, rectangular, and triangular column through an insulated concrete layer while all geometries maintain the consistent surface areas. The simulations yield findings indicating that circular thermal bridging has the best thermal performance, while rectangular thermal bridging displays comparatively the lowest thermal efficiency. Furthermore, the results indicate that alterations in the perimeter of thermal bridge interfaces, while maintaining a constant area, exert a more pronounced influence on the thermal performance of the geometries compared to proportional changes in area while preserving the perimeter. The study’s findings aid building designers and architects in creating more energy-efficient structural and architectural elements by incorporating thermally efficient geometries and forms. .