Federica Bellizio

Colin Jüni, Mina Montazeri, Yi Guo et al.

Buildings account for approximately 40% of global energy consumption, and with the growing share of intermittent renewable energy sources, enabling demand-side flexibility, particularly in heating, ventilation and air conditioning systems, is essential for grid stability and energy efficiency. This paper presents a safe deep reinforcement learning-based control framework to optimize building space heating while enabling demand-side flexibility provision for power system operators. A deep deterministic policy gradient algorithm is used as the core deep reinforcement learning method, enabling the controller to learn an optimal heating strategy through interaction with the building thermal model while maintaining occupant comfort, minimizing energy cost, and providing flexibility. To address safety concerns with reinforcement learning, particularly regarding compliance with flexibility requests, we propose a real-time adaptive safety-filter to ensure that the system operates within predefined constraints during demand-side flexibility provision. The proposed real-time adaptive safety filter guarantees full compliance with flexibility requests from system operators and improves energy and cost efficiency -- achieving up to 50% savings compared to a rule-based controller -- while outperforming a standalone deep reinforcement learning-based controller in energy and cost metrics, with only a slight increase in comfort temperature violations.

Hanmin Cai, Federica Bellizio, Yi Guo et al.

Harnessing the demand-side flexibility in building and mobility sectors can help to better integrate renewable energy into power systems and reduce global CO2 emissions. Enabling this sector coupling can be achieved with advances in energy management, business models, control technologies, and power grids. The study of demand-side flexibility extends beyond engineering, spanning social science, economics, and power and control systems, which present both challenges and opportunities to researchers and engineers in these fields. This Review outlines recent trends and studies in social, economic, and technological advancements in power systems that leverage demand-side flexibility. We first provide a concept of a socio-techno-economic system with an abstraction of end-users, building and mobility sectors, control systems, electricity markets, and power grids. We discuss the interconnections between these elements, highlighting the importance of bidirectional flows of information and coordinated decision-making. We then emphasize that fully realizing demand-side flexibility necessitates deep integration across stakeholders and systems, moving beyond siloed approaches. Finally, we discuss the future directions in renewable-based power systems and control engineering to address key challenges from both research and practitioners' perspectives. A holistic approach for identifying, measuring, and utilizing demand-side flexibility is key to successfully maximizing its multi-stakeholder benefits but requires further transdisciplinary collaboration and commercially viable solutions for broader implementation.