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.