Amidst the global energy crisis, governments are pursuing transitions towards low-carbon
energy systems. In addition to physical infrastructure, political and regulatory enablers, and …

This paper summarises the insights to be gained from a systematic literature review of
empirical research devoted to behavioural considerations associated with the use of smart …

Background Demand response is an important option for accommodating growing shares of
renewable electricity, and therefore, crucial for the success of the energy transition in …

Machine learning (ML) methods can effectively analyse data, recognize patterns in them,
and make high-quality predictions. Good predictions usually come along with" black-box" …

Mitigating the risks of catastrophic climate change requires wide-scale electrification and the
rapid decarbonization of the energy sector. This transformation poses serious challenges to …

Abstract Machine learning (ML) methods can effectively analyse data, recognize patterns in
them, and make high-quality predictions. Good predictions usually come along with “black …