TY - JOUR
T1 - Enabling Optimal Energy Management with Minimal IoT Requirements
T2 - A Legacy A/C Case Study
AU - Michailidis, Panagiotis
AU - Pelitaris, Paschalis
AU - Korkas, Christos
AU - Michailidis, Iakovos
AU - Baldi, S.
AU - Kosmatopoulos, Elias
PY - 2021
Y1 - 2021
N2 - The existing literature on energy saving focuses on large-scale buildings, wherein the energy-saving potential is substantially larger than smaller-scale buildings. However, the research intensity is significantly less for small-scale deployments and their capacities to regulate energy use individually, directly and without depreciating users’ comfort and needs. The current research effort focused on energy saving and user satisfaction, concerning a low-cost—yet technically sophisticated—methodology for controlling conventional residential HVAC units through cheap yet reliable actuation and sensing and auxiliary IoT equipment. The basic ingredients of the proposed experimental methodology involve a conventional A/C unit, an Arduino microcontroller, typical wireless IoT sensors and actuators, a configured graphical environment and a sophisticated, model-free, optimization-and-control algorithm (PCAO) that portrays the ground basis for achieving improved performance results in comparison with conventional methods. The main goal of this study was to produce a system that would adequately and expeditiously achieve energy savings by utilizing minimal hardware/equipment (affordability). The system was designed to be easily expandable in terms of new units or thermal equipment (expandability) and also to be autonomous, requiring zero user interventions at the experimental site (automation). The real-life measurements were collected over two different seasonal periods of the year (winter, summer) and concerned a conventional apartment in the city of Xanthi, Northern Greece, where summers and winters exhibit quite diverse climate characteristics. The final results revealed the increased efficiency of PCAO’s optimization in comparison with a conventional rule-based control strategy (RBC), as concerns energy savings and user satisfaction.
AB - The existing literature on energy saving focuses on large-scale buildings, wherein the energy-saving potential is substantially larger than smaller-scale buildings. However, the research intensity is significantly less for small-scale deployments and their capacities to regulate energy use individually, directly and without depreciating users’ comfort and needs. The current research effort focused on energy saving and user satisfaction, concerning a low-cost—yet technically sophisticated—methodology for controlling conventional residential HVAC units through cheap yet reliable actuation and sensing and auxiliary IoT equipment. The basic ingredients of the proposed experimental methodology involve a conventional A/C unit, an Arduino microcontroller, typical wireless IoT sensors and actuators, a configured graphical environment and a sophisticated, model-free, optimization-and-control algorithm (PCAO) that portrays the ground basis for achieving improved performance results in comparison with conventional methods. The main goal of this study was to produce a system that would adequately and expeditiously achieve energy savings by utilizing minimal hardware/equipment (affordability). The system was designed to be easily expandable in terms of new units or thermal equipment (expandability) and also to be autonomous, requiring zero user interventions at the experimental site (automation). The real-life measurements were collected over two different seasonal periods of the year (winter, summer) and concerned a conventional apartment in the city of Xanthi, Northern Greece, where summers and winters exhibit quite diverse climate characteristics. The final results revealed the increased efficiency of PCAO’s optimization in comparison with a conventional rule-based control strategy (RBC), as concerns energy savings and user satisfaction.
KW - building energy-management systems
KW - domestic automation
KW - centralized building optimization and control
KW - energy-sustainable buildings
KW - HVAC control
KW - IoT
UR - http://www.scopus.com/inward/record.url?scp=85119995110&partnerID=8YFLogxK
U2 - 10.3390/en14237910
DO - 10.3390/en14237910
M3 - Article
SN - 1996-1073
VL - 14
JO - Energies
JF - Energies
IS - 23
M1 - 7910
ER -