Development of an Energy Saving Strategy Model for Retrofitting Existing Buildings: A Korean Case Study

The building sector accounts for approximately 40% of national energy consumption, contributing to the environmental crisis of global warming. Using energy saving measures (e.g., improved thermal insulation, highly energy-efficient electrical and mechanical systems) provides opportunities to reduce energy consumption in existing buildings. Furthermore, if the life cycle cost (i.e., installation, operation and maintenance cost) of the measures is considered with their energy saving potential, it is possible to establish a cost-effective energy retrofit plan. Therefore, this research develops an energy saving strategy model considering its saving potential and life cycle cost of the measures for reducing energy consumption in existing buildings. To test the validity of the proposed model, a case study is carried out on an educational facility in South Korea, in response to its overconsumption of energy. The results demonstrate that in terms of energy saving and life cycle cost, the optimal energy retrofit plan is more cost-effective than the existing plan. Also, the break-even point for the optimal energy retrofit plan is within five years, and then revenue from energy saving continually occurs until 2052. For energy retrofit of existing buildings, using the proposed model would enable building owners to maximize energy savings while minimizing the life cycle cost.

[1]  Daniel Castro-Lacouture,et al.  GA-based decision support system for housing condition assessment and refurbishment strategies , 2009 .

[2]  Douglass J. Wilde,et al.  Foundations of Optimization. , 1967 .

[3]  Brenda Vale,et al.  A LIFE CYCLE ENERGY COMPARISON OF THREE WORLD EXPO BUILDINGS , 2011 .

[4]  Edmundas Kazimieras Zavadskas,et al.  Multi-criteria decision-making system for sustainable building assessment/certification , 2015 .

[5]  Thomas Olofsson,et al.  Environmental Performance Measures to Assess Building Refurbishment from a Life Cycle Perspective , 2019, Energies.

[6]  A. Pasanisi,et al.  A multi-criteria decision tool to improve the energy efficiency of residential buildings , 2008 .

[7]  Manfred Morari,et al.  Importance of occupancy information for building climate control , 2013 .

[8]  Baker Nick,et al.  The Handbook of Sustainable Refurbishment: Non-Domestic Buildings , 2009 .

[9]  Lu Aye,et al.  Environmentally sustainable development: a life-cycle costing approach for a commercial office building in Melbourne, Australia , 2000 .

[10]  Rasmus Lund Jensen,et al.  Early stage decision support for sustainable building renovation – A review , 2016 .

[11]  Liu Yang,et al.  Thermal comfort and building energy consumption implications - A review , 2014 .

[12]  Kristel de Myttenaere,et al.  Towards a comprehensive life cycle energy analysis framework for residential buildings , 2012 .

[13]  Tullie Circle,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATING AND AIR-CONDITIONING , 2013 .

[14]  Philip Crowther,et al.  Design for Disassembly , 1999 .

[15]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[16]  Sanghyo Lee,et al.  Analyzing the Finishing Works Service Life Pattern of Public Housing in South Korea by Probabilistic Approach , 2018, Sustainability.

[17]  Kari Alanne,et al.  Selection of renovation actions using multi-criteria “knapsack” model , 2004 .

[18]  Kleanthis Sirakoulis,et al.  The effectiveness of resource levelling tools for Resource Constraint Project Scheduling Problem , 2009 .

[19]  Subramaniam Ganesan,et al.  Condition based maintenance: a survey , 2012 .

[20]  M. Ramachandran,et al.  Application of multi-criteria decision making to sustainable energy planning--A review , 2004 .

[21]  Yong Han Ahn,et al.  Analyzing the Long-Term Service Life of MEP Using the Probabilistic Approach in Residential Buildings , 2018, Sustainability.

[22]  Per Anker Jensen,et al.  Value based building renovation - A tool for decision-making and evaluation , 2015 .

[23]  Jeff H. Rankin,et al.  Detailed Analysis of the Construction, Operating, Maintenance, and Rehabilitation Costs of Green Toronto Schools , 2013 .

[24]  Ola Eriksson,et al.  Life Cycle Assessment of Building Renovation Measures–Trade-off between Building Materials and Energy , 2019, Energies.

[25]  Igal M. Shohet,et al.  Decision support model for semi-automated selection of renovation alternatives , 1999 .

[26]  Edmundas Kazimieras Zavadskas,et al.  Method and system for Multi-Attribute Market Value Assessment in analysis of construction and retrofit projects , 2011, Expert Syst. Appl..

[27]  Paula Femenias,et al.  Unveiling the Process of Sustainable Renovation , 2012 .

[28]  Taehoon Hong,et al.  Energy-Saving Techniques for Reducing CO 2 Emissions in Elementary Schools , 2012 .

[29]  Philip Crowther Design for Disassembly to Recover Embodied Energy , 1999 .

[30]  Kwonsik Song,et al.  Energy efficiency-based course timetabling for university buildings , 2017 .

[31]  John Palmer,et al.  Energy performance indoor environmental quality retrofit — a European diagnosis and decision making method for building refurbishment , 2000 .