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

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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.

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Abbreviations

C :

Energy cost per unit surface ($/m2)

E :

Energy need per unit surface (J/m2year)

g :

Inflation rate (%)

H u :

Lower heating value of the fuel (J/kg, J/m3)

i :

Interest rate (%)

k :

Thermal conductivity (W/mK)

N :

Life time (year)

Pp:

Payback period (year)

q :

Heat loss per unit surface (W/m2)

R :

Thermal resistance (m2K/W)

S :

Saved energy for annual heating ($/m2year)

T :

Temperature (K)

U :

Total heat transfer coefficient (W/m2K)

x :

Insulation thickness (m

BEW:

Building external wall

CGB:

Conventional gradient-based

EPS:

Expanded polystyrene

HDD:

Heating degree-day

ISA:

Interactive search algorithm

LPG:

Liquefied petroleum gas

PWF:

Present worth factor

SV:

Single-variable

SMV:

Simultaneous multi-variable

THC:

Total heating cost

XPS:

Extruded polystyrene

a:

Annual

c:

Cement based

f:

Fuel

h:

Heating

i:

Inside

ins.:

Insulation

L:

Lime based

m:

Material of insulation

o:

Outside

opt:

Optimum

t:

Total

w:

Wall

η :

Efficiency of the combustion system

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Acknowledgements

The authors wish to thank all who assisted in conducting this work.

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No financial funds have been received.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Ege University, Izmir, Turkey

    M. Moloodpoor

  2. Graduate School of Natural and Applied Sciences, Ege University, Izmir, Turkey

    A. Mortazavi

Authors
  1. M. Moloodpoor
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  2. A. Mortazavi
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Correspondence to M. Moloodpoor.

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Editorial responsibility: Samareh Mirkia.

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Moloodpoor, M., Mortazavi, A. Simultaneous optimization of fuel type and exterior walls insulation attributes for residential buildings using a swarm intelligence. Int. J. Environ. Sci. Technol. 19, 2809–2822 (2022). https://doi.org/10.1007/s13762-021-03323-0

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  • DOI: https://doi.org/10.1007/s13762-021-03323-0

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