Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Grey Wolf algorithmic framework for building energy optimization in India's Köppen-Geiger climatic zones

Grey Wolf algorithmic framework for building energy optimization in India's Köppen-Geiger... Grey Wolf Optimization (GWO) is an emerging evolutionary metaheuristic technique capable of solving challenging engineering problems. Despite its growing popularity, GWO's suitability for building design problems remains unexplored. This paper presents a novel algorithmic framework using EnergyPlus, EPLauncher and Matlab to implement a single and bi-objective GWO for building energy optimization. The goal is to identify optimal wall and window type, orientation, air conditioner's operational profiles and cooling setpoints consistent with minimum annual and peak cooling energy demands for a residential apartment building in five Köppen-Geiger climate zones across India. In place of testing the entire parametric space involving 5,76,000 possibilities, GWO identifies the optimal solutions inside 1250 trials (∼99% run reduction). The single and bi-objective GWO produces (83-97)% and (75-95)% annual and peak cooling demand reductions than a typical construction and operation scenario in the five climate zones. The optimized solutions recommend low thermal transmittance-high capacitance wall sections, 10–15% window-to-wall ratios and double glazed windows with a low solar gain coefficient. Further, optimal air conditioner operational parameters (setpoint and duration) are identified. The presented algorithmic framework is highly robust and can integrate can incorporate upcoming metaheuristic algorithms to perform single and multiobjective building energy optimizations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Advances in Building Energy Research Taylor & Francis

Grey Wolf algorithmic framework for building energy optimization in India's Köppen-Geiger climatic zones

Download PDF
26 pages

Grey Wolf algorithmic framework for building energy optimization in India's Köppen-Geiger climatic zones

Abstract

Grey Wolf Optimization (GWO) is an emerging evolutionary metaheuristic technique capable of solving challenging engineering problems. Despite its growing popularity, GWO's suitability for building design problems remains unexplored. This paper presents a novel algorithmic framework using EnergyPlus, EPLauncher and Matlab to implement a single and bi-objective GWO for building energy optimization. The goal is to identify optimal wall and window type, orientation, air conditioner's...
Loading next page...
 
/lp/taylor-francis/grey-wolf-algorithmic-framework-for-building-energy-optimization-in-RWEgnj0ToU
Publisher
Taylor & Francis
Copyright
© 2023 Informa UK Limited, trading as Taylor & Francis Group
ISSN
1756-2201
eISSN
1751-2549
DOI
10.1080/17512549.2023.2184422
Publisher site
See Article on Publisher Site

Abstract

Grey Wolf Optimization (GWO) is an emerging evolutionary metaheuristic technique capable of solving challenging engineering problems. Despite its growing popularity, GWO's suitability for building design problems remains unexplored. This paper presents a novel algorithmic framework using EnergyPlus, EPLauncher and Matlab to implement a single and bi-objective GWO for building energy optimization. The goal is to identify optimal wall and window type, orientation, air conditioner's operational profiles and cooling setpoints consistent with minimum annual and peak cooling energy demands for a residential apartment building in five Köppen-Geiger climate zones across India. In place of testing the entire parametric space involving 5,76,000 possibilities, GWO identifies the optimal solutions inside 1250 trials (∼99% run reduction). The single and bi-objective GWO produces (83-97)% and (75-95)% annual and peak cooling demand reductions than a typical construction and operation scenario in the five climate zones. The optimized solutions recommend low thermal transmittance-high capacitance wall sections, 10–15% window-to-wall ratios and double glazed windows with a low solar gain coefficient. Further, optimal air conditioner operational parameters (setpoint and duration) are identified. The presented algorithmic framework is highly robust and can integrate can incorporate upcoming metaheuristic algorithms to perform single and multiobjective building energy optimizations.

Journal

Advances in Building Energy Research – Taylor & Francis

Published: Mar 4, 2023

Keywords: Building energy optimization; Grey Wolf optimization; EnergyPlus; EP Launcher; Cooling energy demand

References

  • Multi-Objective optimization of passive energy efficiency measures for Net-Zero energy building in Morocco
  • Multi-Objective optimization of building envelope design for life cycle environmental performance
  • Application of PSO and GA Stochastic algorithms to select optimum building envelope and Air conditioner size - A case of a residential building prototype
  • Application of a probabilistic LHS-PAWN approach to assess building cooling energy demand uncertainties
  • Multi-Objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms
  • Multiobjective optimization of building energy consumption based on BIM-DB and LSSVM-NSGA-II
  • Energy optimization of high-rise commercial buildings integrated with photovoltaic facades in urban context
  • Multi-Objective approach to the optimization of shape and envelope in building energy design
  • Optimal sizing of hybrid solar/Wind/Hydroelectric pumped storage energy system in Egypt based on different meta-heuristic techniques
  • A review of computational optimisation methods applied to sustainable building design
  • A multi-objective optimization model for energy-efficiency building envelope retrofitting plan with rooftop PV system installation and maintenance
  • Energy management for user’s thermal and power needs: A survey
  • Building energy optimization using Grey Wolf Optimizer (GWO)
  • Epluslauncher: An API to perform complex energyplus simulations in MATLAB® and C#
  • Optimal modification of heating, ventilation, and Air conditioning system performances in residential buildings using the integration of metaheuristic optimization and neural computing
  • Passive design optimization of Low energy buildings in different climates
  • Energy performance optimization of existing buildings: A literature review
  • Ten questions on urban building energy modeling
  • Design optimization of energy efficient residential buildings in Tunisia
  • A novel optimization method combining metaheuristics and machine learning for daily optimal operations in building energy and storage systems
  • Optimal renewable energy supply choices for Net-Zero ready buildings: A life cycle thinking approach under uncertainty
  • A review on optimization methods applied in energy-efficient building geometry and envelope design
  • Modeling and optimization of the smart grid ecosystem
  • Optimization of a building energy performance by a multi-objective optimization, using sustainable energy combinations
  • Design optimization of office building envelope configurations for energy conservation
  • Algorithms for optimization of building design: A review
  • Energy management in microgrids including smart homes: A multi-objective approach
  • A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis
  • Integrated optimisation of photovoltaic and battery storage systems for UK commercial buildings
  • A performance comparison of multi-objective optimization-based approaches for Calibrating White-Box building energy models
  • Grey Wolf optimizer
  • Multi-Objective Grey Wolf optimizer: A novel algorithm for multi-criterion optimization
  • A review on simulation-based optimization methods applied to building performance analysis
  • Planning and operational energy optimization solutions for smart buildings
  • Shading devices optimization to enhance thermal comfort and energy performance of a residential building in Morocco
  • A review on building energy efficient design optimization Rom the perspective of architects
  • Ineffectiveness of optimization algorithms in building energy optimization and possible causes
  • Performance indices and evaluation of algorithms in building energy efficient design optimization
  • Building energy optimization tools and their applicability in architectural conceptual design stage
  • Genetic-Algorithm based approach to optimize building envelope design for residential buildings
  • Multi-Objective optimization of energy performance for a detached residential building with a sunspace using the NSGA-II Genetic algorithm
  • Energy & buildings building energy optimization : An extensive benchmark of global search algorithms
  • Impact of adjustment strategies on building design process in different climates oriented by multiple performance
  • Estimating thermal parameters of a commercial building: A meta-heuristic approach
  • Two neural-metaheuristic techniques based on vortex search and backtracking search algorithms for predicting the heating load of residential buildings
  • Teaching–Learning-based metaheuristic scheme for modifying neural computing in appraising energy performance of building