Recent advancements in data science and artificial intelligence, as well as the development
of clean and sustainable energy sources, have created numerous opportunities for energy …

Since the energy sector is the dominant contributor to global greenhouse gas emissions, the
decarbonization of energy systems is crucial for climate change mitigation. Two major …

Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …

Given the steep rises in renewable energy's proportion in the global energy mix expected
over several decades, a systematic way to plan the long-term deployment is needed. The …

For green building design, this paper proposes a multi-objective optimization (MOO)
framework to properly adjust design parameters using a deep reinforcement learning (DRL) …

Abstract Artificial Neural Networks (ANNs) are proposed for sizing and simulating a clean
energy community (CEC) that employs a PV-wind hybrid system, coupled with energy …

Co-optimization of urban morphology and distributed energy systems is key to curb energy
consumption and optimally exploit renewable energy in cities. Currently available …

The energy transition is increasingly being discussed and implemented to cope with the
growing environmental crisis. However, great challenges remain for effectively harvesting …

In the context of carbon neutrality, multi-energy systems are being designed to enhance the
integration of renewable energy, and the deployment of large-scale energy storage …

Co-designing energy systems across multiple energy carriers is increasingly attracting
attention of researchers and policy makers, since it is a prominent means of increasing the …