KIEE - The Transactions of the Korean Institute of Electrical Engineers

Ministry of Environment, Mar. 2021, 2021 Ministry of Environment Carbon Neutral Implementation Plan,

Y. Kim, Sep. 2021, Nationally Determined Contribution and Carbon Neutral Policy Measures in the Building Sector, Planning and policy (Korea Research Institute for Human Settlements), vol. 479, pp. 12-19

3

L. Pérez-Lombard, J. Ortiz, C. Pout, 2008, A review on buildings energy consumption information, Energy and buildings, vol. 40, no. 3, pp. 394-398

4

M. Ostadijafari, A. Dubey, Sep. 2020, Tube-based model predictive controller for building’s heating ventilation and air conditioning (HVAC) system, IEEE Systems Journal, vol. 15, no. 4, pp. 4735-4744

5

Z. Jiang, M. J. Risbeck, V. Ramamurti, S. Murugesan, J. Amores, C. Zhang, Y. M. Lee, K. H. Drees, May 2021, Building HVAC control with reinforcement learning for reduction of energy cost and demand charge, Energy and Buildings, vol. 239, Article 110833

6

N. S. Raman, K. Devaprasad, P. Barooah, Jul. 2019, MPC-based building climate controller incorporating humidity, American Control Conference (ACC), pp. 253-260

7

D. Ormandy, V. Ezratty, Oct. 2012, Health and thermal comfort: From WHO guidance to housing strategies, Energy Policy, vol. 49, pp. 116-121

8

D. Li, C. C. Menassa, V. R. Kamat, Oct. 2018, Non-intrusive interpretation of human thermal comfort through analysis of facial infrared thermography, Energy and Buildings, vol. 176, pp. 246-261

9

ANSI, ASHRAE, 2020, Thermal Environmental Conditions for Human Occupancy, Atlanta

10

ISO, 2005, ISO 7730: Ergonomics of the thermal environment- Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria,

11

J. Wu, X. Li, Y. Lin, Y. Yan, J. Tu, Jun. 2020, A PMV-based HVAC control strategy for office rooms subjected to solar radiation, Building and Environment, vol. 177, Article 106863

12

J. Park, H. Choi, D. Kim, T. Kim, Dec. 2021, Development of novel PMV-based HVAC control strategies using a mean radiant temperature prediction model by machine learning in Kuwaiti climate, Building and Environment, vol. 206, Article 108357

13

E. Z. Conceição, A. F. Sousa, J. M. Gomes, A. E. Ruano, Jan. 2019, HVAC systems applied in university buildings with control based on PMV and aPMV indexes, Inventions, vol. 4, no. 1, 3

14

P. Satrio, T. M. I. Mahlia, N. Giannetti, K. Saito, Oct. 2019, Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm, Sustainable Energy Technologies and Assessments, vol. 35, pp. 48-57

15

C. Karmann, S. Schiavon, E. Arens, Apr. 2018, Percentage of commercial buildings showing at least 80% occupant satisfied with their thermal comfort, 10th Windsor Conference: Rethinking Comfort

16

G. Gao, J. Li, Y. Wen, May 2020, DeepComfort: Energy-efficient thermal comfort control in buildings via reinforcement learning, IEEE Internet of Things Journal, vol. 7, no. 9, pp. 8472-8484

17

T. Chaudhuri, Y. C. Soh, H. Li, L. Xie, Jul. 2017, Machine learning based prediction of thermal comfort in buildings of equatorial Singapore, 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC), pp. 72-77

18

J. H. Choi, D. Yeom, Aug. 2017, Study of data-driven thermal sensation prediction model as a function of local body skin temperatures in a built environment, Building and Environment, vol. 121, pp. 130-147

19

X. Zhang, W. Shi, B. Yan, A. Malkawi, N. Li, 2017, Decentralized and distributed temperature control via HVAC systems in energy efficient buildings, arXiv preprint arXiv:1702.03308

20

N. Radhakrishnan, Y. Su, R. Su, K. Poolla, Jul. 2015, Token based scheduling of HVAC services in commercial buildings, American Control Conference (ACC), pp. 262-269

21

N. S. Raman, A. M. Devraj, P. Barooah, S. P. Meyn, Jul. 2020, Reinforcement learning for control of building HVAC systems, American Control Conference (ACC), pp. 2326-2332

22

L. Yu, Y. Sun, Z. Xu, C. Shen, D. Yue, T. Jiang, X. Guan, Jan. 2020, Multi-agent deep reinforcement learning for HVAC control in commercial buildings, IEEE Transactions on Smart Grid, vol. 12, no. 1, pp. 407-419

23

Korea Meteorological Administration Meteorological Data Open Portal, , https://data.kma.go.kr/data/grnd/selectAsosRltmList. do?pgmNo=36, , pp. -

24

Korea Electric Power Corporation, , https://home.kepco.co.kr/kepco/ EN/F/htmlView/ENFBHP00103.do?menuCd=EN060201, , pp. -

25

G. Paliaga, 2012, Dual maximum VAV box control logic, Ashrae Journal, vol. 54, no. 12, pp. 16-24

26

Korea Energy Economics Institute, , https://home.kepco.co.kr/kepco/ EN/F/htmlView/ENFBHP00103.do?menuCd=EN060201, , pp. -