TY - JOUR
T1 - A decision support system for green and economical individual heating resource planning
AU - Esmat, Ayman
AU - Ghiassi-Farrokhfal, Yashar
AU - Gunkel, Philipp Andreas
AU - Bergaentzlé, Claire-Marie
PY - 2023
Y1 - 2023
N2 - The heat sector accounts for almost half of the world’s energy consumption, making it a crucial component in meeting decarbonization targets. One of the biggest challenges of heat energy decarbonization arises at the household level, which collectively has a substantial impact on decarbonization. Individual households commonly rely on decentralized heat sources (DHS). Different technologies can be used as a DHS, each of which leads to different overall (Capex and Opex) costs and carbon emissions. Households choose their DHS technologies freely, though typically influenced by the recommendations from their local city planners who use historical data and analyze the respective economical and environmental consequences. Therefore, developing a decision support system (DSS) that guides individuals in their DHS investment choices is a high priority for city planners as it can help evaluate the role of different policies in aligning economical and environmental concerns. This is becoming more important as both the economical and environmental concerns are increasing, respectively, due to recent energy price spikes and the growing urgency of decarbonization. However, developing such a comprehensive DSS is challenging due to the complexity of accounting for all DHS constraints and the uncertainties in demand, prices, and policies. In this study, we present a reliable and comprehensive DSS that provides a range of optimal strategies including the most cost-efficient and the most environmentally friendly ones. These strategies identify the optimal type, installed capacity, and year of investment of DHS technologies, as well as the expected yearly heat generation of each technology. Our DSS accounts for the uncertainties of heat demand, fuel prices, investment, and operation and maintenance costs. We apply our DSS to a typical household in the municipality of Lyngby-Taarbæk under different policy scenarios. We show that between the most environmentally friendly and most cost-efficient solution only a gap of 9%–15% in cost needs to be bridged. We also demonstrate that current energy taxation policies in Denmark do not provide a level playing field between different heat technologies. Under different policy scenarios, we show that heat pumps integrated with PV have the highest potential for minimizing CO2 emissions for a Danish household.
AB - The heat sector accounts for almost half of the world’s energy consumption, making it a crucial component in meeting decarbonization targets. One of the biggest challenges of heat energy decarbonization arises at the household level, which collectively has a substantial impact on decarbonization. Individual households commonly rely on decentralized heat sources (DHS). Different technologies can be used as a DHS, each of which leads to different overall (Capex and Opex) costs and carbon emissions. Households choose their DHS technologies freely, though typically influenced by the recommendations from their local city planners who use historical data and analyze the respective economical and environmental consequences. Therefore, developing a decision support system (DSS) that guides individuals in their DHS investment choices is a high priority for city planners as it can help evaluate the role of different policies in aligning economical and environmental concerns. This is becoming more important as both the economical and environmental concerns are increasing, respectively, due to recent energy price spikes and the growing urgency of decarbonization. However, developing such a comprehensive DSS is challenging due to the complexity of accounting for all DHS constraints and the uncertainties in demand, prices, and policies. In this study, we present a reliable and comprehensive DSS that provides a range of optimal strategies including the most cost-efficient and the most environmentally friendly ones. These strategies identify the optimal type, installed capacity, and year of investment of DHS technologies, as well as the expected yearly heat generation of each technology. Our DSS accounts for the uncertainties of heat demand, fuel prices, investment, and operation and maintenance costs. We apply our DSS to a typical household in the municipality of Lyngby-Taarbæk under different policy scenarios. We show that between the most environmentally friendly and most cost-efficient solution only a gap of 9%–15% in cost needs to be bridged. We also demonstrate that current energy taxation policies in Denmark do not provide a level playing field between different heat technologies. Under different policy scenarios, we show that heat pumps integrated with PV have the highest potential for minimizing CO2 emissions for a Danish household.
KW - Decentralized heat sources
KW - Decision support system
KW - Long-term strategic planning
U2 - 10.1016/j.apenergy.2023.121442
DO - 10.1016/j.apenergy.2023.121442
M3 - Journal article
SN - 0306-2619
VL - 347
JO - Applied Energy
JF - Applied Energy
M1 - 121442
ER -
