Investment decision-making optimization of energy efficiency retrofit measures in multiple buildings under financing budgetary restraint

Abstract Regarding to energy efficiency retrofit investment to numerous buildings, which buildings should be invested and which of the retrofit measures should be implemented for investable buildings are challenging tasks. The current literature have studied on choosing energy efficiency retrofit measures in single building, relatively little attention has been paid to the retrofit investment decision-making in multiple buildings. In addition, the existing studies almost put the retrofit cost as an objective that need to be minimized, and the retrofit capital budget is not taken into consideration. This paper proposes a decision-making optimization framework for energy efficiency retrofit investment in numerous buildings under financing budgetary restraint. A multi-objective optimization model with the economic goals being the net present value and time of return, and the environmental goals being the energy saving and emission reduction is presented, and then the intelligent optimization method combing particle swarm optimization and genetic algorithm is designed to search the retrofit investment strategy. The obtained investment strategy could determine which of the buildings should be invested to retrofit, and the combination of retrofitting measures for every investable building. An empirical study is conducted on 27 buildings of non-governmental organization in the state of Delaware in the United States, and the results indicate that the validity of the proposed framework. The findings indicate that the framework is an effective approach to assist the sustainability goal at regional level.

[1]  Alessandro Prada,et al.  Multi-objectives optimization of Energy Efficiency Measures in existing buildings , 2015 .

[2]  Manuela de Almeida,et al.  Cost effective energy and carbon emissions optimization in building renovation , 2012 .

[3]  Declan Butler,et al.  Architecture: Architects of a low-energy future , 2008, Nature.

[4]  Gerardo Maria Mauro,et al.  Energy retrofit of educational buildings: Transient energy simulations, model calibration and multi-objective optimization towards nearly zero-energy performance , 2017 .

[5]  Fausto Freire,et al.  Adaptive reuse of buildings: Eco-efficiency assessment of retrofit strategies for alternative uses of an historic building , 2017 .

[6]  Edmundas Kazimieras Zavadskas,et al.  Multivariant design and multiple criteria analysis of building refurbishments , 2005 .

[7]  João P. S. Catalão,et al.  A Decentralized Electricity Market Scheme Enabling Demand Response Deployment , 2018, IEEE Transactions on Power Systems.

[8]  Stephen Siu Yu Lau,et al.  Cost-effectiveness of active and passive design strategies for existing building retrofits in tropical climate: Case study of a zero energy building , 2018 .

[9]  Henk Visscher,et al.  Sustainable building energy efficiency retrofit for hotel buildings using EPC mechanism in China: Analytic Network Process (ANP) approach , 2015 .

[10]  Eugénio Rodrigues,et al.  A review on current advances in the energy and environmental performance of buildings towards a more sustainable built environment , 2017 .

[11]  Constantinos A. Balaras,et al.  Energy consumption and the potential of energy savings in Hellenic office buildings used as bank branches—A case study , 2011 .

[12]  Simon Roberts,et al.  Altering existing buildings in the UK , 2008 .

[13]  Luis Pérez-Lombard,et al.  A review on buildings energy consumption information , 2008 .

[14]  Edmundas Kazimieras Zavadskas,et al.  The concept model of sustainable buildings refurbishment , 2008 .

[15]  Laura Gabrielli,et al.  Evaluation of energy retrofit in buildings under conditions of uncertainty: The prominence of the discount rate , 2017 .

[16]  Rahman Saidur,et al.  Energy consumption, energy savings, and emission analysis in Malaysian office buildings , 2009 .

[17]  Jonathan A. Wright,et al.  Optimization of building thermal design and control by multi-criterion genetic algorithm , 2002 .

[18]  Baris Tan,et al.  Optimal selection of energy efficiency measures for energy sustainability of existing buildings , 2016, Comput. Oper. Res..

[19]  Olatz Pombo,et al.  The challenge of sustainable building renovation: assessment of current criteria and future outlook , 2015 .

[20]  Tingting Liu,et al.  Cost-benefit analysis for Energy Efficiency Retrofit of existing buildings: A case study in China , 2018 .

[21]  Bo Wang,et al.  Large-scale building energy efficiency retrofit: Concept, model and control , 2016 .

[22]  Ala Hasan,et al.  Applying a multi-objective optimization approach for Design of low-emission cost-effective dwellings , 2011 .

[23]  Juha Jokisalo,et al.  Cost-optimal energy performance renovation measures of educational buildings in cold climate , 2016 .

[24]  Gerardo Maria Mauro,et al.  A new methodology for cost-optimal analysis by means of the multi-objective optimization of building energy performance , 2015 .

[25]  Jaume Salom,et al.  Comfort and economic criteria for selecting passive measures for the energy refurbishment of residential buildings in Catalonia , 2016 .

[26]  Edward Morofsky,et al.  Effectiveness of single and multiple energy retrofit measures on the energy consumption of office bu , 2011 .

[27]  P. Zou,et al.  Role of financial mechanisms for accelerating the rate of water and energy efficiency retrofits in Australian public buildings: Hybrid Bayesian Network and System Dynamics modelling approach , 2018 .

[28]  Aristides Kiprakis,et al.  A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies , 2015 .

[29]  Jin Si,et al.  Assessment of building-integrated green technologies: A review and case study on applications of Multi-Criteria Decision Making (MCDM) method , 2016 .

[30]  Ulrich Filippi Oberegger,et al.  Energy retrofit and conservation of a historic building using multi-objective optimization and an analytic hierarchy process , 2017 .

[31]  Fausto Freire,et al.  Building retrofit addressing occupancy: An integrated cost and environmental life-cycle analysis , 2017 .

[32]  Pau Fonseca i Casas,et al.  Cost-effective analysis for selecting energy efficiency measures for refurbishment of residential buildings in Catalonia , 2016 .

[33]  Constantine E. Kontokosta.  Modeling the energy retrofit decision in commercial office buildings , 2016 .

[34]  Jerry Yudelson,et al.  Greening Existing Buildings , 2009 .

[35]  Vanessa Valentin,et al.  An optimization framework for building energy retrofits decision-making , 2017 .

[36]  Evangelos Grigoroudis,et al.  Performance study of a multi-objective mathematical programming modelling approach for energy decision-making in buildings , 2013 .

[37]  Philipp Geyer,et al.  Integrating requirement analysis and multi-objective optimization for office building energy retrofit strategies , 2014 .

[38]  Bo Wang,et al.  Improving building energy efficiency by multiobjective neighborhood field optimization , 2015 .

[39]  Vytautas Martinaitis,et al.  Evaluation of energy efficiency measures sustainability by decision tree method , 2014 .

[40]  Maurizio Cellura,et al.  Energy and environmental benefits in public buildings as a result of retrofit actions , 2011 .