Towards socio-techno-economic power systems with demand-side flexibility
A new framework proposes using AI and smart tech to turn buildings and EVs into flexible power assets.
A collaborative research team of 14 authors, led by Hanmin Cai and Yi Guo, has published a comprehensive review on arXiv titled 'Towards socio-techno-economic power systems with demand-side flexibility.' The paper presents a unified framework for transforming power grids by treating end-user assets—like smart buildings and electric vehicles—as flexible resources. This 'sector coupling' aims to smooth the integration of variable renewables like solar and wind, which is critical for reducing global CO2 emissions. The authors stress that this is not just an engineering challenge but a transdisciplinary one, requiring deep integration across social science, economics, and control systems.
The core of the proposed system relies on bidirectional information flows and coordinated, AI-enhanced decision-making between consumers, grid operators, and markets. The review synthesizes recent trends, highlighting that siloed approaches are insufficient. Fully realizing this vision demands commercially viable solutions, new business models, and advanced control technologies to manage the complexity. The authors conclude that future research must focus on holistic methods for identifying, measuring, and utilizing this flexibility to deliver multi-stakeholder benefits, calling for increased collaboration between researchers and practitioners.
- Proposes a unified 'socio-techno-economic' framework to manage demand from buildings and EVs as grid assets
- Identifies the need for advances in AI control systems, market designs, and business models for implementation
- Aims to reduce CO2 emissions by better aligning energy use with renewable generation, requiring transdisciplinary collaboration
Why It Matters
This blueprint is essential for utilities and tech companies building the AI-driven, flexible grid needed to achieve decarbonization goals.