Optimizing the integration of renewable energy in existing buildings

被引:19
作者
Hassan, Ahmed A. [1 ]
El-Rayes, Khaled [1 ]
机构
[1] Univ Illinois, Dept Civil & Environm Engn, 3112 Newmark Civil Engn Bldg,205 N Mathews, Urbana, IL 61801 USA
关键词
Renewable energy; Building segmentation; Optimization; Federal buildings; Building-integrated photovoltaics; Genetic algorithm; Building energy consumption; Building upgrade; MULTIOBJECTIVE OPTIMIZATION; DESIGN; SYSTEMS; MODEL; SIMULATION; MULTISTAGE; TOOLS; MIX;
D O I
10.1016/j.enbuild.2021.110851
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper presents the development of a novel optimization model for optimizing the use of RE measures in existing buildings to satisfy an owner-specified target reduction in energy consumption while minimizing the required building upgrade costs. The model performance was evaluated using a real life case study of an educational building with a total area of 20,717 m(2). The optimization model was used to identify an optimal combination of RE technologies that minimize the upgrade cost for this case study while satisfying its specified 80% energy reduction goal. The model minimized the building upgrade cost by making a number of optimal selections, such as locating the majority of solar RE technologies in building segments facing south due to their higher exposure to the sun radiations. The results of this analysis highlight the original contributions of the model in identifying an optimal set of RE measures that minimize the building upgrade cost while satisfying all owner-specified requirements, providing a detailed description of the optimal building integration plan of RE technologies, and complying with practical functional requirements, and constructability constraints. These capabilities are expected to support building owners and decision-makers in their efforts to integrate cost-effective RE measures in existing buildings. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:17
相关论文
共 53 条
[1]  
Abdallah M., 2014, CONSTR RES C, V2014, P140, DOI [10.1061/9780784413517.176, DOI 10.1061/9780784413517.176]
[2]   Multiobjective Optimization Model for Maximizing Sustainability of Existing Buildings [J].
Abdallah, Moatassem ;
El-Rayes, Khaled .
JOURNAL OF MANAGEMENT IN ENGINEERING, 2016, 32 (04)
[3]  
[Anonymous], 1995, ISO 8608
[4]  
[Anonymous], SUN EXT
[5]   Optimization of building envelope design for nZEBs in Mediterranean climate: Performance analysis of residential case study [J].
Ascione, Fabrizio ;
De Masi, Rosa Francesca ;
de Rossi, Filippo ;
Ruggiero, Silvia ;
Vanoli, Giuseppe Peter .
APPLIED ENERGY, 2016, 183 :938-957
[6]   Multi-objective optimization of the renewable energy mix for a building [J].
Ascione, Fabrizio ;
Bianco, Nicola ;
De Masi, Rosa Francesca ;
De Stasio, Claudio ;
Mauro, Gerardo Maria ;
Vanoli, Giuseppe Peter .
APPLIED THERMAL ENGINEERING, 2016, 101 :612-621
[7]   Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality [J].
Ascione, Fabrizio ;
Bianco, Nicola ;
De Stasio, Claudio ;
Mauro, Gerardo Maria ;
Vanoli, Giuseppe Peter .
APPLIED ENERGY, 2016, 174 :37-68
[8]   Optimised model for community-based hybrid energy system [J].
Ashok, S. .
RENEWABLE ENERGY, 2007, 32 (07) :1155-1164
[9]   Passive cooling techniques for building and their applicability in different climatic zones-The state of art [J].
Bhamare, Dnyandip K. ;
Rathod, Manish K. ;
Banerjee, Jyotirmay .
ENERGY AND BUILDINGS, 2019, 198 :467-490
[10]   A review of methods to match building energy simulation models to measured data [J].
Coakley, Daniel ;
Raftery, Paul ;
Keane, Marcus .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 37 :123-141