Modeling and managing residential energy demand for a low-carbon future

Abstract

Achieving a decarbonized society requires balancing two critical and seemingly conflicting objectives: reducing energy consumption and ensuring energy demand flexibility to adapt to the variability of renewable energy production. This study introduces ''energy demand science'' as a multidisciplinary field to address these challenges, focusing on the residential sector, which significantly impacts energy use due to occupant behavior and lifestyle. Using a comprehensive review of literature and advanced modeling techniques, this research explores mechanisms driving energy demand. Key results show that energy demand can be reduced by up to 40 % by 2050 through lifestyle adjustments, urbanization, and innovative technologies, aligning with global warming targets below 1.5 °C. Advanced modeling techniques and high-resolution data analyses were employed to explore mechanisms driving energy demand, supported by historical data from 1970 to present, incorporating advancements in IoT and smart metering technologies. The results highlight the importance of integrating technological, human, natural, and socio-economic factors to achieve a sustainable reduction in energy use while maintaining flexibility. Policy implications emphasize the need for holistic, interdisciplinary strategies to enable efficient demand-side management, enhance renewable energy integration, and align energy consumption with decarbonization goals.

Keywords

• Energy demand modeling
• High spatiotemporal resolution
• Socio-demographic factors
• Energy conservation behaviors
• Theory-driven methods