Sensitivity analysis and multi-objective optimization of energy consumption and thermal comfort by using interior light shelves in residential buildings

Ebrahimi‐Moghadam, Amir; Ildarabadi, Paria; Aliakbari, Karim; Fadaee, Faramarz

doi:10.1016/j.renene.2020.05.127

Cited by 69 publications

(30 citation statements)

References 27 publications

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“…Since optimization is a mathematical process for finding the minimum or maximum values of given functions and evaluating the design and decision options based on the 'best combination' of variables, it can complement the building performance simulation techniques and serve as a useful tool in the early stages of the architectural design of buildings to investigate design possibilities that yield the optimum objectives, as defined by project stakeholders [40]. Previous building energy and daylighting performance optimization studies have focused on variables such as window-to-wall ratio, glazing materials, shading types, materials, dimensions, and building orientation [41][42][43][44][45][46][47][48]. In Table 1, summarized the literature reviewed in the present study on multi-objective optimization for improving building performance.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Talaei

Mahdavinejad

Azari

et al. 2021

Journal of Building Engineering

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Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Talaei

Mahdavinejad

Azari

et al. 2021

Journal of Building Engineering

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“…The constraints are chosen to impose the limit of variables of any system so that updated values or positions always locate inside the boundary region while the optimization algorithm tries to achieve the desired objective function [220]- [222]. Commonly, the constraints are assigned to the maximum or minimum bounds of variables.…”

Section: B Optimization Constraintsmentioning

confidence: 99%

Intelligent Controllers and Optimization Algorithms for Building Energy Management Towards Achieving Sustainable Development: Challenges and Prospects

et al. 2021

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Buildings account for a significant amount of energy consumption leading to the issues of global emissions and climate change. Thus, energy management in a building is increasingly explored due to its significant potential in reducing the overall electricity expenses for the consumers and mitigating carbon emissions. In line with that, the greater control and optimization of energy management integrated with renewable energy resources is required to improve building energy efficiency while satisfying indoor environment comfort. Even though actions are being taken to reduce the energy consumption in buildings with several optimization and controller techniques, yet some issues remain unsolved. Therefore, this work provides a comprehensive review of the conventional and intelligent control methods with emphasis on their classification, features, configuration, benefits, and drawbacks. This review critically investigates the different optimization objectives and constraints with respect to comfort management, energy consumption, and scheduling. Furthermore, the review outlines the different methodological approaches to optimization algorithms used in building energy management. The contributions of controller and optimization in building energy management with the relation of sustainable development goals (SDGs) are explained rigorously. Discussions on the key challenges of the existing methods are presented to identify the gaps for future research. The review delivers some effective future directions that would be beneficial to the researchers and industrialists to design an efficiently optimized controller for building energy management toward targeting SDGs.INDEX TERMS Building energy management, controller, optimization, scheduling, sustainable development goals I. INTRODUCTIONPresently, buildings take the lead in consuming a substantial amount of energy, indicating about 40% of global energy consumption, which is responsible to release one-third of greenhouse gas (GHG) emissions [1], [2]. Another report demonstrates that buildings hold 49% of the total energy worldwide in which 60% of the energy is consumed for heating and cooling purposes [3], [4]. The poor management and ineffective control approach of appliances used in the building may result in a significant loss of energy in a

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“…The results show that the window to wall ratio (WWR), internal convective heat transfer coefficient, internal thermal mass level, and night mechanical air change rate are the biggest influential design parameters for night cooling. Amir et al [23] carried out SA in thermal comfort and building energy consumption to evaluate the effect of light shelves characteristics in residential buildings. They found that the optimum light shelves were able to decrease 11.38% electrical energy consumption of the building.…”

Section: Literature Review 21 Key Parameters For Building Performancementioning

confidence: 99%

“…Policymakers can be guided to formulate the energy codes by providing sufficient information in selecting and processing building parameters that control changes in the energy demand. On the other hand, engineers and designers need to know both building engineering and energy models to correctly choose the influential building parameters [23]. Thus, all of them need relevant research to provide guidance.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Sensitivity Analysis Method for Energy and Comfort Performance of an Office Building along the Chinese Coastline

Chen

Tsay

2021

Buildings

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This study aimed to evaluate the comprehensive percentage influence of input parameters on building energy and comfort performance by a new approach of sensitivity analysis (SA) and explore the most reliable and neutral sampling and sensitivity assessment method. The research combined 7 sampling methods with 13 SA methods to comprehensively integrate the percentage influence of 25 input parameters on building energy and comfort performance in 24 coastal cities of China. The results have found that the percentage influence of many important input parameters is affected by geographical position. Considering both energy and comfort performance of the building, the key parameters are heating setpoint, infiltration rate, cooling setpoint, roof U value, roof solar absorptance, window solar heat gain coefficient, equipment, and occupant density, all of which could comprehensively impact 70% of energy demand and comfort performance along the Chinese coastline. This is of great significance for policymakers to formulate relative building regulations. After comparing the F-test and the exceed percentage test, we recommended the Pearson with Quasi-random sampling method as the most reliable SA assessment method in building simulation, followed by the standardized regression coefficient in random sampling and Latin hypercube sampling methods, which can achieve data closest to the average value.

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Sensitivity analysis and multi-objective optimization of energy consumption and thermal comfort by using interior light shelves in residential buildings

Cited by 69 publications

References 27 publications

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Intelligent Controllers and Optimization Algorithms for Building Energy Management Towards Achieving Sustainable Development: Challenges and Prospects

An Integrated Sensitivity Analysis Method for Energy and Comfort Performance of an Office Building along the Chinese Coastline

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