TY - JOUR
KW - Demand response
KW - Energy flexibility
KW - Economic model predictive control
KW - Residential space heating
KW - Structural thermal storage
AU - Theis Heidmann Pedersen
AU - Rasmus Elbæk Hedegaard
AU - Steffen Petersen
AB - In future and smarter energy systems, time varying energy prices enable indirect demand response (DR) to assist the electricity supply system to meet demand. This simulation-based study investigates how economic model predictive control (E-MPC) schemes for space heating operation can utilize the thermal mass in an existing multi-story apartment block and eight retrofit scenarios to provide DR. The performance of the E-MPC scheme was evaluated in terms of its ability to enable end-user cost savings, reduce CO2 emissions and to perform load shift of the heating demand compared to a conventional PI controller. Two E-MPC approaches were considered: centralized E-MPC where inter-zonal effects were considered and decentralized E-MPC that neglected heat transfer between adjacent apartments. The E-MPC schemes led to increasing cost savings (up to approx. 6%) and reduced CO2 emissions (up to approx. 3%) as a function of increasing energy efficiency of the retrofit scenarios. The absolute amount of shifted power from peak load periods was rather consistent (approx. 2 kWh/m2 heated net area) across all retrofit scenarios compared to the existing building. The centralized E-MPC scheme led to marginally better results than the decentralized E-MPC. The added complexity involved in establishing a centralized E-MPC compared to a decentralized E-MPC may therefore not be worth the effort.
BT - Energy and Buildings
DO - 10.1016/j.enbuild.2017.02.035
LA - English
N2 - In future and smarter energy systems, time varying energy prices enable indirect demand response (DR) to assist the electricity supply system to meet demand. This simulation-based study investigates how economic model predictive control (E-MPC) schemes for space heating operation can utilize the thermal mass in an existing multi-story apartment block and eight retrofit scenarios to provide DR. The performance of the E-MPC scheme was evaluated in terms of its ability to enable end-user cost savings, reduce CO2 emissions and to perform load shift of the heating demand compared to a conventional PI controller. Two E-MPC approaches were considered: centralized E-MPC where inter-zonal effects were considered and decentralized E-MPC that neglected heat transfer between adjacent apartments. The E-MPC schemes led to increasing cost savings (up to approx. 6%) and reduced CO2 emissions (up to approx. 3%) as a function of increasing energy efficiency of the retrofit scenarios. The absolute amount of shifted power from peak load periods was rather consistent (approx. 2 kWh/m2 heated net area) across all retrofit scenarios compared to the existing building. The centralized E-MPC scheme led to marginally better results than the decentralized E-MPC. The added complexity involved in establishing a centralized E-MPC compared to a decentralized E-MPC may therefore not be worth the effort.
PB - Elsevier
PY - 2017
EP - 158–166
T2 - Energy and Buildings
TI - Space heating demand response potential of retrofitted residential apartment blocks
VL - 141
ER -