scholarly journals Methodology for Energy Efficiency on Lighting and Air Conditioning Systems in Buildings Using a Multi-Objective Optimization Algorithm

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3303
Author(s):  
Suzane A. Monteiro ◽  
Flávia Monteiro ◽  
Maria E. Tostes ◽  
Carminda Carvalho
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Incremental Cost ◽  
Air Conditioning ◽  
Fitness Function ◽  
Efficiency Coefficient ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The North ◽  
Conditioning Equipment

The purpose of this article is to develop a methodology to apply to multi-objective optimization algorithms aimed at energy efficiency in buildings, considering aspects such as incremental cost, energy consumption, greenhouse gas emissions and energy efficiency levels of lighting and air conditioning system, according to the mandatory technical regulation in public buildings in Brazil. Presenting a solution to assist in the decision making of engineers, architects or building managers for the optimal arrangements’ choice for lighting and air conditioning equipment, considering each built environment and project profile. For the validation process, a basic building was created with 15 rooms spread over three floors, according to the most common construction parameters in the North of Brazil. First, different combinations of objective-function candidates were investigated to compose the multi-objective algorithm fitness function, analyzing its performance in two central scenarios: (1) adding some “baits” in air conditioning equipment files, and (2) without this inclusion. Thus, it was found that considering only three objective functions—incremental cost, energy consumption and the air conditioning energy efficiency coefficient—it is possible to get optimal non-dominated solutions in both scenarios, thus highlighting the robustness of the proposed methodology.

Air Conditioning Units Optimize Control Strategy Based on Multi-Objective Optimization Evolutionary Algorithms

2014 ◽  
Vol 513-517 ◽  
pp. 3568-3571
Author(s):  
Bing Xu ◽  
Cheng Qian Xu ◽  
Zhong Jin Shi ◽  
Bao Guo Zheng ◽  
Xue Han Zhu
Keyword(s):  
Energy Consumption ◽  
Evolutionary Algorithms ◽  
Energy Saving ◽  
Control Strategy ◽  
Air Conditioning ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Control ◽  
Saving Effect ◽  
Air Conditioning Systems

In order to reduce the energy consumption of air conditioning systems, the best running model is adjusting the humiture according to actual needs of environment and groups.This paper take out a control strategy based on the Multi-objective Optimization Evolutionary Algorithms.With cntrol simulation, it achieve the energy saving effect in air conditioning units groups, proposed multi-objective optimization control strategy.

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.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

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.

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