Design Of Net-zero Energy Buildings Research Articles

Optimization approaches and climates investigations in NZEB—A review

The conception of net zero energy buildings (NZEB) has been introduced to limit energy consumption and pollution emissions in buildings. Classification of NZEB is based on renewable energy (RE) supply options, energy measurement process, RE-sources location, and balances whether are energetic or exergetic. In general, it is traditionally agreed that there are three main steps to reach the NZEB performance, starting through the use of passive strategies, energy efficient technologies, and then RE generation systems. Then, these three steps could be accompanied with the smart integration of advanced efficient energy technologies. A state of the art shows that the main ZEB studies are related to: energy savings, reduce electric bills, energy independence, pollution reduction, and occupants comfort, in addition, others are more interested in the aesthetic aspect by combining modern technologies with innovations to achieve high energy and sustainability performance. Building optimization is a promising technique to evaluate NZEB design choices; it has been adopted to choose the perfect solution to reach the zero energy performance through the optimization of an objective function related to energy (thermal loads, RE generation, energy savings) and/or environment (CO2 emissions) and/or economy (life-cycle cost (LCC), net-present value (NPV), investment cost). This paper starts by presenting the global energetic and pollution challenges the world faces. Moreover, it shows, to the best to the author’s knowledge, the existing NZEB definitions and the corresponding case studies investigated in 8 different climatic zones (humid continental, humid subtropical, Mediterranean, moderate continental, moderate continental, marine west coast, tropical, semi-arid and hot), the paper also focus on the importance to treat each climate separately. Even in the same country, two or more climates may co-exist. NZEBs drawbacks are also presented. Furthermore, different optimization problems are reviewed in the last section. Building energy optimization methods are employed to obtain the ideal solution for specific objective functions which are either related to energy, and/or environment and/or economy. Optimization variables are distributed between passive and/or RE generation systems. Finally, a table summarizing the most commonly used electric and thermal RE applications which yield to the zero energy balance in each climate, as well as three flowcharts are presented to summarize the whole three-stage procedure, to reach NZEB, starting from building designing, passing through the optimization procedure, and lastly categorizing the zero energy balance.

Passive designs and renewable energy systems optimization of a net zero energy building in Embrun/France

Buildings’ optimization is a smart method to inspect the available design choices starting from passive strategies, to energy efficient systems and finally towards the adequate renewable energy system to be implemented. This paper outlines the methodology and the cost-effectiveness potential for optimizing the design of net-zero energy building in a French city; Embrun. The non-dominated sorting genetic algorithm is chosen in order to minimize thermal, electrical demands and life cycle cost while reaching the net zero energy balance; and thus getting the Pareto-front. Elimination and Choice Expressing the Reality decision making method is applied to the Pareto-front so as to obtain one optimal solution. A wide range of energy efficiency measures are investigated, besides solar energy systems are employed to produce required electricity and hot water for domestic purposes. The results indicate that the appropriate selection of the passive parameters is very important and critical in reducing the building energy consumption. The optimum design parameters yield to a decrease of building’s thermal loads and life cycle cost by 32.96% and 14.47% respectively.

Multi-objective optimization methodology for net zero energy buildings

The challenge in Net Zero Energy Building (NZEB) design is to find the best combination of design strategies that will face the energy performance problems of a particular building. This paper presents a methodology for the simulation-based multi-criteria optimization of NZEBs. Its main features include four steps: building simulation, optimization process, multi-criteria decision making (MCDM) and testing solution's robustness. The methodology is applied to investigate the cost-effectiveness potential for optimizing the design of NZEBs in different case studies taken as diverse climatic zones in Lebanon and France. The investigated design parameters include: external walls and roof insulation thickness, windows glazing type, cooling and heating set points, and window to wall ratio. Furthermore, the inspected RE systems include: solar domestic hot water (SDHW) and photovoltaic (PV) array. The proposed methodology is a useful tool to enhance NZEBs design and to facilitate decision making in early phases of building design. Specifically, the non-dominated sorting genetic algorithm (NSGA-II) is chosen in order to minimize thermal, electrical demands and life cycle cost (LCC) while reaching the net zero energy balance; thus getting the Pareto-front. A ranking decision making technique Elimination and Choice Expressing the Reality (ELECTRE III) is applied to the Pareto-front so as to obtain one optimal solution.

Expanding Heisler chart to characterize heat transfer phenomena in a building envelope integrated with phase change materials

Building envelope integrated with phase change material (PCM) can provide thermal energy storage (TES) distributed in its entire surface area and inhibit the need for enhanced thermal mass in lightweight buildings. Selecting the most appropriate PCM wallboard based on its thickness and thermo-physical properties is the main challenge in the design of net-zero energy buildings and high performance buildings; yet, there is a lack of an appropriate design tool. To develop a design tool, characterizing transient heat transfer phenomena of wallboards impregnated with PCM during charging procedure is required. Accordingly, this study focuses on the characterizing heat transfer of PCM wallboards, and to identify the influential parameters on the charging procedure of a PCM wallboard. The non-dimensionalized analysis was conducted, and the dimensionless numbers influencing the thermal behavior of a PCM wallboard were identified. Moreover, the correlations between the dimensionless parameters and the performance of the PCM wallboard were determined through a comprehensive parametric study. Consequently, a procedure was developed to expand Heisler chart application to study thermal behavior of PCM wallboards.

Identifying Key Decisions for Net-Zero Energy Building Early Design Process Through Process Mapping Techniques

The lack of a structured approach to help the Architecture, Engineering, and Construction (AEC) industry in making informed decisions (Korkmaz et al. 2007) for the Net-Zero Energy Building (NZEB) context establishes the need to evaluate the argumentation of the NZEB design decision process (Author, 2014). This research qualitatively analyzes the early design process of NZEB case studies that informs decision-making in the early design phase. The four components that were studied in the early design phases included key stakeholders involved (roles played), phases of assessments (design approach), processes (key processes, sub-processes, and design activities affecting performance) and technology (knowledge type and flow).

Using sensitivity analysis to improve the efficiency of a Net-Zero Energy vaccine warehouse design

A critical step in the design of a Net-Zero Energy building is the reduction of energy consumption, so that consumption can be cost-effectively offset by renewable energy production. In this paper, we present a method to inform the design of Net-Zero Energy buildings through the identification of influential energy efficiency measures. A regression-based global sensitivity analysis is used to quantify the relative importance of both individual design parameters and bilinear interactions between parameters. This allows for the identification of the specific two-way interactions between parameter pairs, rather than an evaluation of the influence of interactions for each parameter in a lumped manner as is commonly used in building performance simulation. The relative importance of both building control and architectural design parameters are assessed, and are used to help evaluate the importance of utilizing an integrated design method for reducing building energy consumption. The case-study building investigated is a primary vaccine warehouse, a vital part of the vaccine cold chain in the developing world. As this building type has not received adequate attention in the field of building performance simulation, this paper makes a significant contribution towards an improved understanding of the energy efficient design of these warehouses.

노원에코센터(제로에너지건물) 연간 에너지모니터링 결과 분석 연구

Among world's effort to take action to the effect of climate change, a district in Korea with a progressive mind took its first step in realizing a net-zero energy ecological center. The concept of net-zero energy building design can only be stated as a fact if the simulated energy demand and the actual monitored usage can be reflected upon its variances. Hence, in this research, the quantitative data sets of simulated and monitored usages were analyzed by comparison and to determine its specific occurrence of variances. From the simulation report, energy demand and the consumption were compared and analyzed based on the data collected from March 2012 to February 2013, through the monitoring system in the subject building. The comparison between the demand and consumption was made in following categories: heating and cooling energy consumption and the energy production from geo-thermal heat pump, lighting energy demand and electricity consumption for lighting, and hot water demand and the energy gained by solar heating. The original programming had changed during actual residence and increased the energy demand, which became the source of error between the simulated data and the monitored consumption. Since this research is based on monitoring of the project building per annum, there could be error occurring form the profile change, weather patterns, or the energy usage patterns by the occupants. Therefore, the further research must be followed with the accumulated data in long-run.

Achieving informed decision-making for net zero energy buildings design using building performance simulation tools

Building performance simulation (BPS) is the basis for informed decision-making of Net Zero Energy Buildings (NZEBs) design. This paper aims to investigate the use of building performance simulation tools as a method of informing the design decision of NZEBs. The aim of this study is to evaluate the effect of a simulation-based decision aid, ZEBO, on informed decision-making using sensitivity analysis. The objective is to assess the effect of ZEBO and other building performance simulation tools on three specific outcomes: (i) knowledge and satisfaction when using simulation for NZEB design; (ii) users’ decision-making attitudes and patterns, and (iii) performance robustness based on an energy analysis. The paper utilizes three design case studies comprising a framework to test the use of BPS tools. The paper provides results that shed light on the effectiveness of sensitivity analysis as an approach for informing the design decisions of NZEBs.

Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design

This paper summarizes a study undertaken to reveal potential challenges and opportunities for integrating optimization tools in net zero energy buildings (NZEB) design. The paper reviews current trends in simulation-based building performance optimization (BPO) and outlines major criteria for optimization tools selection and evaluation. This is based on analyzing user's needs for tools capabilities and requirement specifications. The review is carried out by means of a literature review of 165 publications and interviews with 28 optimization experts. The findings are based on an inter-group comparison between experts. The aim is to assess the gaps and needs for integrating BPO tools in NZEB design. The findings indicate a breakthrough in using evolutionary algorithms in solving highly constrained envelope, HVAC and renewable optimization problems. Simple genetic algorithm solved many design and operation problems and allowed measuring the improvement in the optimality of a solution against a base case. Evolutionary algorithms are also easily adapted to enable them to solve a particular optimization problem more effectively. However, existing limitations including model uncertainty, computation time, difficulty of use and steep learning curve. Some future directions anticipated or needed for improvement of current tools are presented.