TY - GEN
T1 - Energy Consumption Cost Benefits through Smart Home Energy Management in Residential Buildings
T2 - 1st IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022
AU - Yelisetti, Srinivas
AU - Saini, Vikash Kumar
AU - Kumar, Rajesh
AU - Lamba, Ravita
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Energy is a crucial prerequisite for personal activities and civilization since it fuels important everyday services and infrastructure. The primary source of pollution is global energy usage. Buildings have the second-highest power consumption in the world. As a consequence, increasing buildings' energy efficiency will help both the economy and the environment. Home Energy Management Systems (HEMS) are often applied in buildings to monitor actual consumption and schedule device operation to cut energy costs. Heating, Ventilation, and Air Conditioning (HVAC) systems, light loads, and other appliances used to improve indoor comfort have a significant impact on energy consumption. All interior heats have been considered while running the HVAC system. The lighting system in the proposed model can operate efficiently by considering outdoor illuminance. This article analyses energy consumption performance in five Indian metro cities: Chennai, Kolkata, Mumbai, Delhi, and Jaipur residential buildings using four meta-heuristic techniques. From the statistical and boxplot analysis, Hill Climbing (HC) has shown its effectiveness when compared to the other three techniques: Sine Cosine Algorithm (SCA), Modified Sine Cosine Algorithm (MSCA), and Arithmetic Optimization Algorithm (AOA). , HC outperforms AOA by 0.15%, while HC outperforms SCA and MSCA by approximately 30%.
AB - Energy is a crucial prerequisite for personal activities and civilization since it fuels important everyday services and infrastructure. The primary source of pollution is global energy usage. Buildings have the second-highest power consumption in the world. As a consequence, increasing buildings' energy efficiency will help both the economy and the environment. Home Energy Management Systems (HEMS) are often applied in buildings to monitor actual consumption and schedule device operation to cut energy costs. Heating, Ventilation, and Air Conditioning (HVAC) systems, light loads, and other appliances used to improve indoor comfort have a significant impact on energy consumption. All interior heats have been considered while running the HVAC system. The lighting system in the proposed model can operate efficiently by considering outdoor illuminance. This article analyses energy consumption performance in five Indian metro cities: Chennai, Kolkata, Mumbai, Delhi, and Jaipur residential buildings using four meta-heuristic techniques. From the statistical and boxplot analysis, Hill Climbing (HC) has shown its effectiveness when compared to the other three techniques: Sine Cosine Algorithm (SCA), Modified Sine Cosine Algorithm (MSCA), and Arithmetic Optimization Algorithm (AOA). , HC outperforms AOA by 0.15%, while HC outperforms SCA and MSCA by approximately 30%.
KW - Heating
KW - Home Energy Management System
KW - Lighting System
KW - Ventilation and Air Conditioning System
UR - http://www.scopus.com/inward/record.url?scp=85138919914&partnerID=8YFLogxK
U2 - 10.1109/GlobConET53749.2022.9872487
DO - 10.1109/GlobConET53749.2022.9872487
M3 - Conference contribution
AN - SCOPUS:85138919914
T3 - 2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022
SP - 930
EP - 935
BT - 2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 20 May 2022 through 22 May 2022
ER -
