Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings Irlanda Ceballos-Fuentealba a , Eduardo Álvarez-Miranda b,e, ⁎ , Carlos Torres-Fuchslocher b,d , María Luisa del Campo-Hitschfeld c,d , John Díaz-Guerrero d a MSc Programme in Operations Management, Department of Industrial Engineering, Faculty of Engineering, Universidad de Talca, Campus Curicó, Chile b Department of Industrial Engineering, Faculty of Engineering, Universidad de Talca, Campus Curicó, Chile c Department of Construction Engineering and Management, Faculty of Engineering, Universidad de Talca, Campus Curicó, Chile d Centro Tecnológico Kipus, Faculty of Engineering, Universidad de Talca, Campus Curicó, Chile e Instituto Sistemas Complejos de Ingeniería (ISCI), Chile HIGHLIGHTS • Develops an energy simulation tool for commercial or institutional buildings. • The tool estimates the building’s thermal load due to climatisation. • The tool evaluates energy efficiency measures for the building envelope. • Achieves acceptable prediction accuracies for a case study building. • The solar gain estimates’ accuracy strongly influences the tool’s accuracy. ARTICLE INFO Keywords: Building energy simulation Building retrofit Energy efficiency ABSTRACT The global stock of buildings account for more than 40% of global energy consumption. Improving their energy behaviour thus offers tremendous potential for promoting sustainable development. While new buildings can be benefited from new construction methods and techniques for ensuring a sustainable operation, a sustainable operation of existing buildings is only possible by retrofitting. However, the later represent the larger portion of the total stock, so effective retrofitting is fundamental for global improvement of energy efficiency. This article develops a methodological framework for predicting (i) the energy consumed in heating and cooling an existing commercial or institutional building, and (ii) the potential impact of different energy conservation measures that could be implemented on a given building. The proposed tool incorporates a simulation model and an algorithm strategy for parameter optimization. The framework is implemented in the JAVA programming language and evaluated in a case study of a 500 [m 2 ] institutional building located in Puerto Montt, Chile. The results of this implementation show that the tool is competitive with the state-of-the art commercial simulation tool DesignBuilder. More importantly, it successfully estimated the savings obtained from different combinations of energy conservation measures for the building and proved to be computationally efficient, the algorithm re- quiring only 2.5 h to complete the simulation. 1. Introduction and motivation One of the greatest challenges of the 21st century is the consump- tion of primary energy and its impact on climate change [1]. This reality underlines the significance of the fact that the world’s stock of buildings account for some 40% of total energy consumption and emit one-third of the total amount of greenhouse gases [2]. Minimizing this source of energy demand is thus essential for reducing consumption in the global energy supply chain and achieving sustainability in buildings [3]. In the literature on reducing energy consumption in the construc- tion industry, a distinction is drawn between buildings in the planning stage and those that already exist. The former category constitutes a small percentage of the total, and with the application of new https://doi.org/10.1016/j.apenergy.2019.113953 Received 6 May 2019; Received in revised form 22 September 2019; Accepted 30 September 2019 ⁎ Corresponding author. E-mail addresses: iceballos11@alumnos.utalca.cl (I. Ceballos-Fuentealba), ealvarez@utalca.cl (E. Álvarez-Miranda), ctorres@utalca.cl (C. Torres-Fuchslocher), mdelcampo@utalca.cl (M.L. del Campo-Hitschfeld), johndiaz@utalca.cl (J. Díaz-Guerrero). Applied Energy 256 (2019) 113953 0306-2619/ © 2019 Elsevier Ltd. All rights reserved. T