Simultaneous optimization of fuel type and exterior walls insulation attributes for residential buildings using a swarm intelligence

Abstract

A significant portion of energy sources in many countries is devoted to the residential sector requirements. A considerable part of this energy is used for heating residential buildings. Minimizing the total heating cost of these buildings has a significant impact on reducing the economic burden and energy consumption. The deterministic parameters in the computation of total heating cost are the fuel type, insulation material and insulation thickness. Since these parameters are not linearly independent from each other, in the current study for a more comprehensive approach, a simultaneous multi-variable optimization model including both discrete and continuous design variables is developed. To solve the acquired model, the recently developed non-deterministic swarm-based approach so-called Interactive Search Algorithm is applied as the optimization method. The degree-day values dependent on the climatic conditions of seven different cities of Turkey are considered as case studies. Subsequently, achieved numeric outcomes are reported as the optimal total heating cost, fuel type (i.e., the sequential integer that indicates the type of fuel) and insulation layer’s material and thickness for each selected climate condition. Moreover, the resultant payback period and saving cost for the acquired optimal condition is calculated and announced. In all studied cities, a combination of natural gas for fuel type and glass wool for insulation material is obtained as the optimal state. The acquired optimal total heating cost values are consistent with the conventional approach results by an average deviation of 6.67e−3%, which reveals the proposed methodology works well in solving the problem.