Occupancy-based buildings-to-grid integration framework for smart and connected communities

被引:38
|
作者
Dong, Bing [1 ]
Li, Zhaoxuan [1 ]
Taha, Ahmad [2 ]
Gatsis, Nikolaos [2 ]
机构
[1] Univ Texas San Antonio, Dept Mech Engn, One UTSA Circle, San Antonio, TX 78249 USA
[2] Univ Texas San Antonio, Dept Elect & Comp Engn, One UTSA Circle, San Antonio, TX 78249 USA
基金
美国国家科学基金会;
关键词
Buildings-to-grid integration; Model predictive control; Occupancy; Smart grid; MODEL-PREDICTIVE CONTROL; DEMAND RESPONSE; ENERGY BUILDINGS; LOAD PREDICTION; CLIMATE CONTROL; BOX MODEL; SYSTEMS; OPTIMIZATION; PERFORMANCE; MANAGEMENT;
D O I
10.1016/j.apenergy.2018.03.007
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Buildings-to-grid (BtG) integration simulations are becoming prevalent due to the development of smart buildings and smart grid. Buildings are the major energy consumers of the total electricity production worldwide. There is an urgent need to integrate buildings with smart grid operation to accommodate the needs of flexible load controls due to the increasing of renewable energy resources. In the imminent future, smart buildings can contribute to grid stability by changing their overall demand patterns in response to grid operations. Meanwhile, building thermal energy consumption is also maintained by building operators to satisfy occupants' thermal comforts. However, explicit large-scale demonstrations based on a simulation platform that integrates building occupancy, building physics, and grid physics at community level have not been explored. This study develops an occupancy behavior driven BtG optimization platform that can simulate, predict and optimize indoor temperature and energy consumption of buildings, generator setpoint and deviation while maintaining acceptable grid frequency. Authors have tested the framework on two standard power networks. The results show that the integrated framework can provide potential cost savings up to 60% comparing with the decoupled operation.
引用
收藏
页码:123 / 137
页数:15
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