Embedded Model Predictive Control of Tankless Gas Water Heaters to Enhance Users' Comfort

被引:0
|
作者
Conceicao, Cheila [1 ]
Quinta, Andre [1 ,2 ,3 ]
Ferreira, Jorge A. F. [1 ,2 ,3 ]
Martins, Nelson [1 ,2 ,3 ]
dos Santos, Marco P. Soares [1 ,2 ,3 ]
机构
[1] Univ Aveiro, Dept Mech Engn, P-3810193 Aveiro, Portugal
[2] Univ Aveiro, TEMA Ctr Mech Technol & Automat, P-3810193 Aveiro, Portugal
[3] LASI Intelligent Syst Associate Lab, P-4800058 Guimaraes, Portugal
关键词
tankless gas water heater; domestic hot water; thermal comfort; model predictive control; hardware-in-the-loop simulation; low-cost embedded control; PERFORMANCE; ALGORITHM; ENERGY; MPC; GENERATION; PUMP;
D O I
10.3390/machines11100951
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Water heating is a significant part of households' energy consumption, and tankless gas water heaters (TGWHs) are commonly used. One of the limitations of these devices is the difficulty of keeping hot water temperature setpoints when changes in water flow occur. As these changes are usually unexpected, the controllers typically used in these devices cannot anticipate them, strongly affecting the users' comfort. Moreover, considerable water and energy waste are associated with the long-time response to cold starts. This work proposes the development of a model predictive control (MPC) to be deployed in low-cost hardware, such that the users' thermal comfort and water savings can be improved. Matlab/Simulink were used to develop, validate and automatically generate C code for implementing the controller in microcontroller-based systems. Hardware-in-the-loop simulations were performed to evaluate the performance of the MPC algorithm in 8-bit and 32-bit microcontrollers. A 6.8% higher comfort index was obtained using the implementation on the 32-bit microcontroller compared to the current deployments; concerning the 8-bit microcontroller, a 4.2% higher comfort index was achieved. These applications in low-cost hardware highlight that users' thermal comfort can be successfully enhanced while ensuring operation safety. Additionally, the environmental impact can be significantly reduced by decreasing water and energy consumption in cold starts of TGWHs.
引用
收藏
页数:20
相关论文
共 50 条
  • [21] Residential Water Heaters as a Grid-Scale Energy Storage Solution Using Model Predictive Control
    Lajoie, Kelcey
    Halamay, Douglas A.
    Brekken, Ted K. A.
    2013 1ST IEEE CONFERENCE ON TECHNOLOGIES FOR SUSTAINABILITY (SUSTECH), 2013, : 62 - 69
  • [22] Designing model predictive control strategies for grid-interactive water heaters for load shifting applications
    Buechler, Elizabeth
    Goldin, Aaron
    Rajagopal, Ram
    APPLIED ENERGY, 2025, 382
  • [23] Optimal Disturbance Control for Energy Feedback of Gas Water Heaters
    Wang, Qian
    Li, Wei
    Meng, Xue-qin
    Li, Chun-lan
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2024, 31 (04): : 1215 - 1222
  • [24] Embedded explicit model predictive vibration control
    Takacs, Gergely
    Batista, Gabriel
    Gulan, Martin
    Rohal'-Ilkiv, Boris
    MECHATRONICS, 2016, 36 : 54 - 62
  • [25] Toward Dependable Embedded Model Predictive Control
    Johansen, Tor A.
    IEEE SYSTEMS JOURNAL, 2017, 11 (02): : 1208 - 1219
  • [26] Learning Optimization Friendly Comfort Model for HVAC Model Predictive Control
    Zhou, Yuxun
    Li, Dan
    Spanos, Costas J.
    2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2015, : 430 - 439
  • [27] Comfort, peak load and energy: Centralised control of water heaters for demand-driven prioritisation
    Roux, M.
    Apperley, M.
    Booysen, M. J.
    ENERGY FOR SUSTAINABLE DEVELOPMENT, 2018, 44 : 78 - 86
  • [28] Model Predictive Control of thermal comfort as a benchmark for controller performance
    Hazyuk, Ion
    Ghiaus, Christian
    Penhouet, David
    AUTOMATION IN CONSTRUCTION, 2014, 43 : 98 - 109
  • [29] Model Predictive Control in buildings with thermal and visual comfort constraints
    Khosravi, Mohammad
    Huber, Benjamin
    Decoussemaeker, Antoon
    Heer, Philipp
    Smith, Roy S.
    ENERGY AND BUILDINGS, 2024, 306
  • [30] Model predictive control for comfort optimization in assisted and driverless vehicles
    Luciani, Sara
    Bonfitto, Angelo
    Amati, Nicola
    Tonoli, Andrea
    ADVANCES IN MECHANICAL ENGINEERING, 2020, 12 (11)