A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis

被引:397
作者
Mariano-Hernandez, D. [1 ,2 ]
Hernandez-Callejo, L. [2 ]
Zorita-Lamadrid, A. [3 ]
Duque-Perez, O. [3 ]
Santos Garcia, F. [4 ,5 ]
机构
[1] Inst Tecnol Santo Domingo, Area Ingn, Santo Domingo 10602, Dominican Rep
[2] Univ Valladolid, Dept Ingn Agr & Forestal, Campus Univ Duques Soria, Soria 42004, Spain
[3] Univ Valladolid, Dept Ingn Elect, Valladolid 47002, Spain
[4] Inst Tecnol Santo Domingo, Area Ciencias Basicas, Santo Domingo 10602, Dominican Rep
[5] Univ Cent Martha Abreu Villas, Ctr Energy Studies & Environm Technol CEETA, Santa Clara 54830, Cuba
关键词
Building energy management system; Building management strategies; Energy efficiency; Energy savings; Energy management system; Smart buildings; MULTIAGENT CONTROL-SYSTEM; PERFORMANCE EVALUATION; COMFORT MANAGEMENT; NEURAL-NETWORK; COMMERCIAL BUILDINGS; SMART BUILDINGS; CONSUMPTION; LOAD; HVAC; EFFICIENCY;
D O I
10.1016/j.jobe.2020.101692
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Building energy use is expected to grow by more than 40% in the next 20 years. Electricity remains the largest energy source consumed by buildings, and that demand is growing. To mitigate the impact of the growing demand, strategies are needed to improve buildings' energy efficiency. In residential buildings home appliances, water, and space heating are answerable for the increase of energy use, while space heating and other miscellaneous equipment are behind the increase of energy utilization in non-residential buildings. Building energy management systems support building managers and proprietors to increase energy efficiency in modern and existing buildings, non-residential and residential buildings can benefit from building energy management system to decrease energy use. Base on the type of building, different management strategies can be used to achieve energy savings. This paper presents a review of management strategies for building energy management systems for improving energy efficiency. Different management strategies are investigated in non-residential and residential buildings. Following this, the reviewed researches are discussed in terms of the type of buildings, building systems, and management strategies. Lastly, the paper discusses future challenges for the increase of energy efficiency in building energy management system.
引用
收藏
页数:12
相关论文
共 128 条
[1]   ISI: Integrate Sensor Networks to Internet With ICN [J].
Adhatarao, Sripriya Srikant ;
Arumaithurai, Mayutan ;
Kutscher, Dirk ;
Fu, Xiaoming .
IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (02) :491-499
[2]   Autonomous Appliance Scheduling for Household Energy Management [J].
Adika, Christopher O. ;
Wang, Lingfeng .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (02) :673-682
[3]   Energy management based on productiveness concept [J].
Agueero, J. ;
Rodriguez, F. ;
Gimenez, A. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 22 :92-100
[4]   Autonomic Management Architecture for Multi-HVAC Systems in Smart Buildings [J].
Aguilar, J. ;
Garces-Jimenez, Alberto ;
Gallego-Salvador, Nuria ;
Gutierrez De Mesa, Jose Antonio ;
Manuel Gomez-Pulido, Jose ;
Jose Garcia-Tejedor, Alvaro .
IEEE ACCESS, 2019, 7 :123402-123415
[5]   An Ensemble Learning Approach for Accurate Energy Prediction in Residential Buildings [J].
Al-Rakhami, Mabrook ;
Gumaei, Abdu ;
Alsanad, Ahmed ;
Alamri, Atif ;
Hassan, Mohammad Mehedi .
IEEE ACCESS, 2019, 7 :48328-48338
[6]   Shifting air-conditioner load in residential buildings: benefits for low-carbon integrated power grids [J].
Ali, Syed Muhammad Hassan ;
Lenzen, Manfred ;
Huang, Jing .
IET RENEWABLE POWER GENERATION, 2018, 12 (11) :1314-1323
[7]   A review of data-driven building energy consumption prediction studies [J].
Amasyali, Kadir ;
El-Gohary, Nora M. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 81 :1192-1205
[8]   Intelligent Residential Energy Management System for Dynamic Demand Response in Smart Buildings [J].
Arun, S. L. ;
Selvan, M. P. .
IEEE SYSTEMS JOURNAL, 2018, 12 (02) :1329-1340
[9]   On the development of multi-linear regression analysis to assess energy consumption in the early stages of building design [J].
Asadi, Somayeh ;
Amiri, Shideh Shams ;
Mottahedi, Mohammad .
ENERGY AND BUILDINGS, 2014, 85 :246-255
[10]   A real industrial building: Modeling, calibration and Pareto optimization of energy retrofit [J].
Ascione, Fabrizio ;
Bianco, Nicola ;
Iovane, Teresa ;
Mauro, Gerardo Maria ;
Napolitano, Davide Ferdinando ;
Ruggiano, Antonio ;
Viscido, Lucio .
JOURNAL OF BUILDING ENGINEERING, 2020, 29