Influence of electricity prices on energy flexibility of integrated hybrid heat pump and thermal storage systems in a residential building

被引:68
作者
Fitzpatrick, Peter [1 ]
D'Ettorre, Francesco [1 ]
De Rosa, Mattia [1 ,2 ]
Yadack, Malcolm [3 ]
Eicker, Ursula [4 ]
Finn, Donal P. [1 ,2 ]
机构
[1] Univ Coll Dublin Ireland, Sch Mech & Mat Engn, Dublin 4, Ireland
[2] Univ Coll Dublin Ireland, UCD Energy Inst, Dublin, Ireland
[3] Sch Appl Sci Stuttgart, Stuttgart, Germany
[4] Concordia Univ, Gina Cody Sch Engn & Comp Sci, Montreal, PQ, Canada
基金
爱尔兰科学基金会;
关键词
Buildings; Demand response; Tariffs; Flexibility; Heat pumps; Thermal storage; Optimised control; DEMAND-SIDE-MANAGEMENT; SIMULATION; CHALLENGES; IMPACTS;
D O I
10.1016/j.enbuild.2020.110142
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The aim of the present paper is to investigate the influence of electricity tariffs on energy flexibility in buildings and associated energy costs. A residential building located in Stuttgart, Germany, equipped with a hybrid heat pump which is coupled with a thermal energy storage unit and a gas boiler is used as a case study. A model predictive control algorithm is used to minimise the daily operational cost over a full heating season. Several demand response programs based on controlling the heat pump power consumption were tested and analysed by adopting different metrics capable of describing the flexibility potential and cost of demand response programs. Several tariff structures, including: real-time pricing, two-level day-night tariffs and critical-peak pricing with both fixed and variable feed-in price components, were investigated. The results show that the building can provide up to 1370 kWh(e) of energy flexibility over the heating season with an average specific (marginal) costs of between (sic)0.024-0.035 per kWh(e) of flexibility provided. The demand response programs lead to higher utilisation of thermal energy storage along with increased boiler consumption, by up to 17.1% and 12.1%, respectively in case of maximum demand response intensity. This in turn leads to a higher overall primary energy consumption of between 1.6% and 9.1% depending on demand response intensity. Typically, real-time pricing is the most favourable tariff structure, capable of offering the greatest energy flexibility with lowest associated electricity costs. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页数:15
相关论文
共 33 条
[1]  
[Anonymous], 2012, The Electricity Journal, DOI DOI 10.1016/J.TEJ.2012.08.004
[2]  
[Anonymous], 2014, P 1 ACM C EMB SYST E
[3]   Modeling framework and validation of a smart grid and demand response system for wind power integration [J].
Broeer, Torsten ;
Fuller, Jason ;
Tuffner, Francis ;
Chassin, David ;
Djilali, Ned .
APPLIED ENERGY, 2014, 113 :199-207
[4]   Impacts of large-scale Intermittent Renewable Energy Sources on electricity systems, and how these can be modeled [J].
Brouwer, Anne Sjoerd ;
van den Broek, Machteld ;
Seebregts, Ad ;
Faaij, Andre .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 33 :443-466
[5]   Energy management systems aggregators: A literature survey [J].
Carreiro, Andreia M. ;
Jorge, Humberto M. ;
Antunes, Carlos Henggeler .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 73 :1160-1172
[6]   A new thermostat for real-time price demand response: Cost, comfort and energy impacts of discrete-time control without deadband [J].
Chassin, David P. ;
Stoustrup, Jakob ;
Agathoklis, Panajotis ;
Djilali, Nedjib .
APPLIED ENERGY, 2015, 155 :816-825
[7]   Mapping the energy flexibility potential of single buildings equipped with optimally-controlled heat pump, gas boilers and thermal storage [J].
D'Ettorre, Francesco ;
De Rosa, Mattia ;
Conti, Paolo ;
Testi, Daniele ;
Finn, Donal .
SUSTAINABLE CITIES AND SOCIETY, 2019, 50
[8]   An Iterative Methodology for Model Complexity Reduction in Residential Building Simulation [J].
De Rosa, Mattia ;
Brennenstuhl, Marcus ;
Cabrera, Carlos Andrade ;
Eicker, Ursula ;
Finn, Donal P. .
ENERGIES, 2019, 12 (12)
[9]   Flexibility assessment of a combined heat-power system (CHP) with energy storage under real-time energy price market framework [J].
De Rosa, Mattia ;
Carragher, Mark ;
Finn, Donal P. .
THERMAL SCIENCE AND ENGINEERING PROGRESS, 2018, 8 :426-438
[10]   Impact of wall discretization on the modeling of heating/cooling energy consumption of residential buildings [J].
De Rosa, Mattia ;
Bianco, Vincenzo ;
Scarpa, Federico ;
Tagliafico, Luca A. .
ENERGY EFFICIENCY, 2016, 9 (01) :95-108