Multi-objective optimization of energy efficiency and thermal comfort in an existing office building using NSGA-II with fitness approximation: A case study

Ghaderian, Mohammadamin; Veysi, Farzad

doi:10.1016/j.jobe.2021.102440

Cited by 43 publications

(17 citation statements)

References 37 publications

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“…In particular, Yong et al [34] proposed a multi-objective particle swarm algorithm coupled to EnergyPlus to optimize the energy performance of residential buildings (Table 4). Similarly, Ghaderian and Veysi [35] developed an optimization procedure based on combining surrogate models linked to EnergyPlus engine with a GA. This was applied to the enhancement of the building's energy consumption and its occupants' thermal comfort, simultaneously.…”

Section: Matlab-based Workflowsmentioning

confidence: 99%

Multi-Objective Optimization Models to Design a Responsive Built Environment: A Synthetic Review

Manni

Nicolini

2022

Energies

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A synthetic review of the application of multi-objective optimization models to the design of climate-responsive buildings and neighbourhoods is carried out. The review focused on the software utilized during both simulation and optimization stages, as well as on the objective functions and the design variables. The hereby work aims at identifying knowledge gaps and future trends in the research field of automation in the design of buildings. Around 140 scientific journal articles, published between 2014 and 2021, were selected from Scopus and Web of Science databases. A three-step selection process was applied to refine the search terms and to discard works investigating mechanical, structural, and seismic topics. Meta-analysis of the results highlighted that multi-objective optimization models are widely exploited for (i) enhancing building’s energy efficiency, (ii) improving thermal and (iii) visual comfort, minimizing (iv) life-cycle costs, and (v) emissions. Reviewed workflows demonstrated to be suitable for exploring different design alternatives for building envelope, systems layout, and occupancy patterns. Nonetheless, there are still some aspects that need to be further enhanced to fully enable their potential such as the ability to operate at multiple temporal and spatial scales and the possibility of exploring strategies based on sector coupling to improve a building’s energy efficiency.

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Section: Matlab-based Workflowsmentioning

confidence: 99%

Multi-Objective Optimization Models to Design a Responsive Built Environment: A Synthetic Review

Manni

Nicolini

2022

Energies

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“…However, the genetic algorithms are modified to accommodate multiple objective functions for multi-objective optimization problems. There are different Multi-Objective Evolutionary algorithms (MOEA), including NSGA2 [ 41 , 42 , 43 , 44 ] and PESA-II [ 45 , 46 ]. In this work, we focused on NSGA-2 and MOEA/D algorithms for solving the constraint multi-objective optimization problem.…”

Section: Optimal Coverage Strategymentioning

confidence: 99%

Towards an Optimal Footprint Based Area Coverage Strategy for a False-Ceiling Inspection Robot

Pathmakumar

Sivanantham

Padmanabha

et al. 2021

Sensors

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False-ceiling inspection is a critical factor in pest-control management within a built infrastructure. Conventionally, the false-ceiling inspection is done manually, which is time-consuming and unsafe. A lightweight robot is considered a good solution for automated false-ceiling inspection. However, due to the constraints imposed by less load carrying capacity and brittleness of false ceilings, the inspection robots cannot rely upon heavy batteries, sensors, and computation payloads for enhancing task performance. Hence, the strategy for inspection has to ensure efficiency and best performance. This work presents an optimal functional footprint approach for the robot to maximize the efficiency of an inspection task. With a conventional footprint approach in path planning, complete coverage inspection may become inefficient. In this work, the camera installation parameters are considered as the footprint defining parameters for the false ceiling inspection. An evolutionary algorithm-based multi-objective optimization framework is utilized to derive the optimal robot footprint by minimizing the area missed and path-length taken for the inspection task. The effectiveness of the proposed approach is analyzed using numerical simulations. The results are validated on an in-house developed false-ceiling inspection robot—Raptor—by experiment trials on a false-ceiling test-bed.

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“…A population-based metaheuristic genetic algorithm transforms the population under the explicit rule of survival of the fittest to reach a desired state of the objective functions. Genetic algorithms can deal with the non-linearity in the optimization of building performance, and they also explore the global optimum solution and do not limit to local optimal points [22].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Techno-Economic Optimization of Design Parameters for Residential Buildings in Different Climate Zones

Usman

Frey

2021

Sustainability

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The comprehensive approach for a building envelope design involves building performance simulations, which are time-consuming and require knowledge of complicated processes. In addition, climate variation makes the selection of these parameters more complex. The paper aims to establish guidelines for determining a single-family household’s unique optimal passive design in various climate zones worldwide. For this purpose, a bi-objective optimization is performed for twenty-four locations in twenty climates by coupling TRNSYS and a non-dominated sorting genetic algorithm (NSGA-III) using the Python program. The optimization process generates Pareto fronts of thermal load and investment cost to identify the optimum design options for the insulation level of the envelope, window aperture for passive cooling, window-to-wall ratio (WWR), shading fraction, radiation-based shading control, and building orientation. The goal is to find a feasible trade-off between thermal energy demand and the cost of thermal insulation. This is achieved using multi-criteria decision making (MCDM) through criteria importance using intercriteria correlation (CRITIC) and the technique for order preference by similarity to ideal solution (TOPSIS). The results demonstrate that an optimal envelope design remarkably improves the thermal load compared to the base case of previous envelope design practices. However, the weather conditions strongly influence the design parameters. The research findings set a benchmark for energy-efficient household envelopes in the investigated climates. The optimal solution sets also provide a criterion for selecting the ranges of envelope design parameters according to the space heating and cooling demands of the climate zone.

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Multi-objective optimization of energy efficiency and thermal comfort in an existing office building using NSGA-II with fitness approximation: A case study

Cited by 43 publications

References 37 publications

Multi-Objective Optimization Models to Design a Responsive Built Environment: A Synthetic Review

Multi-Objective Optimization Models to Design a Responsive Built Environment: A Synthetic Review

Towards an Optimal Footprint Based Area Coverage Strategy for a False-Ceiling Inspection Robot

Multi-Objective Techno-Economic Optimization of Design Parameters for Residential Buildings in Different Climate Zones

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