A multiple objective optimization model for investment decision making in building energy efficiency projects

Abstract

The aim of this research is to formulate a multiple objective optimization model to help decision makers to make optimal decisions when investing in energy efficient building retrofitting. A building in South Africa with 25 energy inefficient facilities that can be retrofitted is considered as a case study. The objectives are to maximize the energy savings and minimize the payback period for a given fixed initial investment. The model guides the decision maker to select the most optimal retrofitting actions in order to achieve maximum energy savings and minimum payback periods. The model is formulated as a multi-objective optimization problem with the net present value (NPV), initial investment, energy target and payback period as constraints. The approach used in solving this optimization problem is the weighted sum approach where the two objectives are combined into a single objective. Because of the complexity of multi-objective optimization problems, the model is solved using genetic algorithms (GAs). GAs are computational models that work on the same principle as evolution. The model gives the optimal actions that must be taken in order to make an optimal decision. Six different cases with different initial investment are simulated and the results are compared. The sensitivity analysis is also performed by analyzing the influence of the changes in energy savings, cost savings, initial cost, interest rate and the quantity of the facilities. The results show that with certain initial investment it is not possible to satisfy all the constraints, and increasing the initial investment increases the energy savings but it does not necessarily decrease the payback period. The sensitivity analysis proves that the model is robust and is not negatively influenced by external parameters.