Mapping the energy flexibility potential of single buildings equipped with optimally-controlled heat pump, gas boilers and thermal storage

被引:58
作者
D'Ettorre, Francesco [1 ]
De Rosa, Mattia [2 ,3 ]
Conti, Paolo [1 ]
Testi, Daniele [1 ]
Finn, Donal [2 ,3 ]
机构
[1] Univ Pisa, Dept Energy Syst Terr & Construct Engn DESTEC, BETTER Bldg Energy Tech & Technol Res Grp, Pisa, Italy
[2] Univ Coll Dublin, Sch Mech & Mat Engn, Dublin 4, Ireland
[3] Univ Coll Dublin, UCD Energy Inst, Dublin 4, Ireland
基金
爱尔兰科学基金会;
关键词
Energy flexibility; Building; Smart grids; Thermal storage; Heat pump; Model predictive control; DEMAND-SIDE-MANAGEMENT; MODEL-PREDICTIVE CONTROL; SYSTEMS; OPTIMIZATION; SIMULATION; IMPACT; OPERATION; FRAMEWORK;
D O I
10.1016/j.scs.2019.101689
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The present paper assesses the capability of a cost-optimal control strategy to activate demand response actions in a building equipped with an air-source heat pump coupled with a water thermal storage system. Commencing with a reference scenario where no demand response actions are considered, the electricity consumption pattern and the operational cost are evaluated. Several demand response scenarios are next considered by adapting consumption patterns by reduction of baseline heat pump power consumption. The difference between the operational cost evaluated under a specific demand response program and the benchmark cost are used to assess the marginal cost that should be considered to provide incentives to promote user participation in demand response programs. The results illustrate the effectiveness of thermal energy storage for reducing the total system operational cost and its seasonal primary energy consumption, both with and without demand response actions. The application of the proposed methodology over the whole heating season, allows performance maps to be created that can be used either by the grid-operator or end-user to identify the best demand response action to be implemented on any particular day. These maps represent useful decision tools to assess and optimise the flexibility potential while meeting end-user needs.
引用
收藏
页数:13
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