Development of control algorithms for optimal thermal environment of double skin envelope buildings in summer

Jin Woo Moon, Jin Chul Park, Sooyoung Kim

Research output: Contribution to journalArticle

Abstract

This study examines diverse thermal control algorithms to control the openings and cooling systems of double skin envelope (DSE) buildings in summer. In order to examine the system performance of control algorithms, five control algorithms combining a conventional rule-based algorithm and four proposed algorithms including fuzzy logic (FL), artificial neural network (ANN), and two adaptive neuro-fuzzy inference systems (ANFIS) were developed. The system performance of the algorithms was compared to those from field measurements to validate prediction accuracy. Further simulations were performed for the DSE building by using the five validated control algorithms. The results indicate that the algorithm employing FL to operate cooling systems created the most acceptable and stable indoor temperature in which 99.98% of the test period was within the target indoor temperature with the narrowest ranges. Compared to other algorithms, the FL-based control algorithm for cooling system can potentially improve building energy efficiency demonstrating an amount of reduction in heat removal up to 49.4%. The ANN-based and ANFIS-based algorithms operated the cooling system more stably and effectively reduced the number of times that the cooling system was turned on and off.

Original languageEnglish
Pages (from-to)657-672
Number of pages16
JournalBuilding and Environment
Volume144
DOIs
Publication statusPublished - 2018 Oct 15

Fingerprint

skin
Skin
building
summer
Cooling systems
cooling
fuzzy mathematics
Fuzzy logic
Fuzzy inference
logic
neural network
artificial neural network
Hot Temperature
Neural networks
energy efficiency
heat
performance
Energy efficiency
temperature
energy

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction

Cite this

@article{1782cc8cbacb4434a3c2c2e86fe61550,
title = "Development of control algorithms for optimal thermal environment of double skin envelope buildings in summer",
abstract = "This study examines diverse thermal control algorithms to control the openings and cooling systems of double skin envelope (DSE) buildings in summer. In order to examine the system performance of control algorithms, five control algorithms combining a conventional rule-based algorithm and four proposed algorithms including fuzzy logic (FL), artificial neural network (ANN), and two adaptive neuro-fuzzy inference systems (ANFIS) were developed. The system performance of the algorithms was compared to those from field measurements to validate prediction accuracy. Further simulations were performed for the DSE building by using the five validated control algorithms. The results indicate that the algorithm employing FL to operate cooling systems created the most acceptable and stable indoor temperature in which 99.98{\%} of the test period was within the target indoor temperature with the narrowest ranges. Compared to other algorithms, the FL-based control algorithm for cooling system can potentially improve building energy efficiency demonstrating an amount of reduction in heat removal up to 49.4{\%}. The ANN-based and ANFIS-based algorithms operated the cooling system more stably and effectively reduced the number of times that the cooling system was turned on and off.",
author = "Moon, {Jin Woo} and Park, {Jin Chul} and Sooyoung Kim",
year = "2018",
month = "10",
day = "15",
doi = "10.1016/j.buildenv.2018.08.011",
language = "English",
volume = "144",
pages = "657--672",
journal = "Building and Environment",
issn = "0360-1323",
publisher = "Elsevier BV",

}

Development of control algorithms for optimal thermal environment of double skin envelope buildings in summer. / Moon, Jin Woo; Park, Jin Chul; Kim, Sooyoung.

In: Building and Environment, Vol. 144, 15.10.2018, p. 657-672.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Development of control algorithms for optimal thermal environment of double skin envelope buildings in summer

AU - Moon, Jin Woo

AU - Park, Jin Chul

AU - Kim, Sooyoung

PY - 2018/10/15

Y1 - 2018/10/15

N2 - This study examines diverse thermal control algorithms to control the openings and cooling systems of double skin envelope (DSE) buildings in summer. In order to examine the system performance of control algorithms, five control algorithms combining a conventional rule-based algorithm and four proposed algorithms including fuzzy logic (FL), artificial neural network (ANN), and two adaptive neuro-fuzzy inference systems (ANFIS) were developed. The system performance of the algorithms was compared to those from field measurements to validate prediction accuracy. Further simulations were performed for the DSE building by using the five validated control algorithms. The results indicate that the algorithm employing FL to operate cooling systems created the most acceptable and stable indoor temperature in which 99.98% of the test period was within the target indoor temperature with the narrowest ranges. Compared to other algorithms, the FL-based control algorithm for cooling system can potentially improve building energy efficiency demonstrating an amount of reduction in heat removal up to 49.4%. The ANN-based and ANFIS-based algorithms operated the cooling system more stably and effectively reduced the number of times that the cooling system was turned on and off.

AB - This study examines diverse thermal control algorithms to control the openings and cooling systems of double skin envelope (DSE) buildings in summer. In order to examine the system performance of control algorithms, five control algorithms combining a conventional rule-based algorithm and four proposed algorithms including fuzzy logic (FL), artificial neural network (ANN), and two adaptive neuro-fuzzy inference systems (ANFIS) were developed. The system performance of the algorithms was compared to those from field measurements to validate prediction accuracy. Further simulations were performed for the DSE building by using the five validated control algorithms. The results indicate that the algorithm employing FL to operate cooling systems created the most acceptable and stable indoor temperature in which 99.98% of the test period was within the target indoor temperature with the narrowest ranges. Compared to other algorithms, the FL-based control algorithm for cooling system can potentially improve building energy efficiency demonstrating an amount of reduction in heat removal up to 49.4%. The ANN-based and ANFIS-based algorithms operated the cooling system more stably and effectively reduced the number of times that the cooling system was turned on and off.

UR - http://www.scopus.com/inward/record.url?scp=85053074194&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85053074194&partnerID=8YFLogxK

U2 - 10.1016/j.buildenv.2018.08.011

DO - 10.1016/j.buildenv.2018.08.011

M3 - Article

VL - 144

SP - 657

EP - 672

JO - Building and Environment

JF - Building and Environment

SN - 0360-1323

ER -