Methodology for Preliminary Design of Buildings Using Multi-Objective Optimization Based on Performance Simulation

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Bruno Ramos Zemero ◽  
Maria Emília de Lima Tostes ◽  
Ubiratan Holanda Bezerra ◽  
Vitor dos Santos Batista ◽  
Carminda Célia M. M. Carvalho
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Optimization Model ◽  
Building Design ◽  
Building Energy ◽  
Design Guidelines ◽  
Building Envelope ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Multi Objective

Buildings' energy consumption has a great energetic and environmental impact worldwide. The architectural design has great potential to solve this problem because the building envelope exerts influence on the overall system performance, but this is a task that involves many objectives and constraints. In the last two decades, optimization studies applied to energy efficiency of buildings have helped specialists to choose the best design options. However, there is still a lack of optimization approaches applied to the design stage, which is the most influential stage for building energy efficiency over its entire life cycle. Therefore, this article presents a multi-objective optimization model to assist designers in the schematic building design, by means of the Pareto archived evolutionary strategies (PAES) algorithm with the EnergyPlus simulator coupled to evaluate the solutions. The search process is executed by a binary array where the array components evolve over the generations, together with the other building components. The methodology aims to find optimal solutions (OSs) with the lowest constructive cost associated with greater energy efficiency. In the case study, it was possible to simulate the process of using the optimization model and analyze the results in relation to: a standard building; energy consumption classification levels; passive design guidelines; usability and accuracy, proving that the tool serves as support in building design. The OSs reached an average of 50% energy savings over typical consumption, 50% reduction in CO2 operating emissions, and investment return less than 3 years in the four different weathers.

scholarly journals Application of Urban Scale Energy Modelling and Multi-Objective Optimization Techniques for Building Energy Renovation at District Scale

2021 ◽  
Vol 13 (20) ◽  
pp. 11554
Author(s):  
Fahad Haneef ◽  
Giovanni Pernigotto ◽  
Andrea Gasparella ◽  
Jérôme Henri Kämpf
Keyword(s):  
Energy Efficiency ◽  
Building Energy ◽  
Energy Performance ◽  
Building Envelope ◽  
Optimization Techniques ◽  
Multi Objective Optimization ◽  
Building Stock ◽  
Energy Efficiency Measures ◽  
Multi Objective ◽  
Efficiency Measures

Nearly-zero energy buildings are now a standard for new constructions. However, the real challenge for a decarbonized society relies in the renovation of the existing building stock, selecting energy efficiency measures considering not only the energy performance but also the economic and sustainability ones. Even if the literature is full of examples coupling building energy simulation with multi-objective optimization for the identification of the best measures, the adoption of such approaches is still limited for district and urban scale simulation, often because of lack of complete data inputs and high computational requirements. In this research, a new methodology is proposed, combining the detailed geometric characterization of urban simulation tools with the simplification provided by “building archetype” modeling, in order to ensure the development of robust models for the multi-objective optimization of retrofit interventions at district scale. Using CitySim as an urban scale energy modeling tool, a residential district built in the 1990s in Bolzano, Italy, was studied. Different sets of renovation measures for the building envelope and three objectives —i.e., energy, economic and sustainability performances, were compared. Despite energy savings from 29 to 46%, energy efficiency measures applied just to the building envelope were found insufficient to meet the carbon neutrality goals without interventions to the system, in particular considering mechanical ventilation with heat recovery. Furthermore, public subsidization has been revealed to be necessary, since none of the proposed measures is able to pay back the initial investment for this case study.

scholarly journals Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm

Buildings ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 88
Author(s):  
Shobhit Chaturvedi ◽  
Elangovan Rajasekar ◽  
Sukumar Natarajan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Design Optimization ◽  
Building Design ◽  
Building Energy ◽  
Global South ◽  
Efficiency Measure ◽  
Nsga Ii ◽  
Multi Objective ◽  
Energy Efficiency Measure

Operational uncertainties play a critical role in determining potential pathways to reduce the building energy footprint in the Global South. This paper presents the application of a non-dominated sorting genetic (NSGA II) algorithm for multi-objective building design optimization under operational uncertainties. A residential building situated in a mid-latitude steppe and desert region (Köppen climate classification: BSh) in the Global South has been selected for our investigation. The annual building energy consumption and the total number of cooling setpoint unmet hours (h) were assessed over 13,122 different energy efficiency measures. Six Pareto optimal solutions were identified by the NSGA II algorithm. Robustness of Pareto solutions was evaluated by comparing their performance sensitivity over 162 uncertain operational scenarios. The final selection for the most optimal energy efficiency measure was achieved by formulating a robust multi-criteria decision function by incorporating performance, user preference, and reliability criteria. Results from this robust approach were compared with those obtained using a deterministic approach. The most optimal energy efficiency measure resulted in 9.24% lower annual energy consumption and a 45% lower number of cooling setpoint unmet h as compared to the base case.

scholarly journals Using Residential and Office Building Archetypes for Energy Efficiency Building Solutions in an Urban Scale: A China Case Study

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3210 ◽  
Author(s):  
Chao Ding ◽  
Nan Zhou
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Power Density ◽  
Building Design ◽  
Building Energy ◽  
Building Envelope ◽  
Stochastic Simulations ◽  
Office Building ◽  
Design Parameters ◽  
Building Energy Consumption

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.

Application of BIM Technology on Energy Efficiency Building Design

2014 ◽  
Vol 587-589 ◽  
pp. 283-286 ◽  
Author(s):  
Mei Zhang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Design Method ◽  
Building Design ◽  
Building Energy ◽  
Information Modeling ◽  
Building Energy Consumption ◽  
Analysis Software ◽  
Building Model

According to the current application situation and domestic energy of our current building energy efficiency design analysis software, in view of the current traditional energy-saving design method can't meet the need of practical problems, put forward the BIM (building information modeling) analysis technology and building energy consumption are combined, anew design method for energy saving building. Application of BIM technology to create virtual building model contains all the information architecture, the virtual building model into the building energy analysis software, identification, automatic conversion and analyzing a large number of construction data information includes in the model, which is convenient to get the building energy consumption analysis.

scholarly journals Energy Saving and Low-Cost-Oriented Design Processes of Blank’s Dimensions Based on Multi-Objective Optimization Model

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 811 ◽  
Author(s):  
Yongmao Xiao ◽  
Qingshan Gong ◽  
Xiaowu Chen
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Optimization Model ◽  
Low Cost ◽  
Minimum Cost ◽  
Processing Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Set Up

The blank’s dimensions are an important focus of blank design as they largely determine the energy consumption and cost of manufacturing and further processing the blank. To achieve energy saving and low cost during the optimization of blank dimensions design, we established energy consumption and cost objectives in the manufacturing and further processing of blanks by optimizing the parameters. As objectives, we selected the blank’s production and further processing parameters as optimization variables to minimize energy consumption and cost, then set up a multi-objective optimization model. The optimal blank dimension was back calculated using the parameters of the minimum processing energy consumption and minimum cost state, and the model was optimized using the non-dominated genetic algorithm-II (NSGA-II). The effect of designing blank dimension in saving energy and costs is obvious compared with the existing methods.

The Strategies of Passive Energy-Efficiency Design in Low Energy Building

2013 ◽  
Vol 368-370 ◽  
pp. 1318-1321
Author(s):  
Xin Bin Wang ◽  
Jia Ping Liu ◽  
Yu Fu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Conservation ◽  
Air Conditioning ◽  
Influence Factors ◽  
Building Design ◽  
Building Energy ◽  
Low Energy ◽  
Paper Briefly ◽  
Low Energy Consumption

This paper briefly analyzes the structure and conservation approaches of building energy consumption, analyzes the forming reason and influence factors of heating and air-conditioning energy consumption and proposes the passive energy conservation designing strategies of low energy consumption building. Through the passive methods of building design, envelop enclosure and planning landscape, the goal of last year building low energy conservation can be achieved.

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