The field of energy systems and grid management is witnessing significant developments, driven by the increasing integration of renewable energy sources and the need for efficient energy storage and management. Researchers are focusing on improving the accuracy of performance modeling for photovoltaic systems, developing stochastic models for investment planning, and optimizing scheduling for combined power-heat systems. Notably, the introduction of high-resolution hierarchical modeling frameworks and tractable probabilistic models is enhancing the reliability and efficiency of energy systems. Furthermore, the development of intelligent scheduling methods and techno-economic modeling is enabling the optimization of energy storage and grid management. Overall, these advancements are paving the way for a more sustainable and resilient energy future.

Noteworthy papers include: The paper on high-resolution hierarchical PV system performance modeling, which demonstrates a high accuracy in predicting minute-wised dynamic electrical characteristics. The paper on tractable probabilistic models for investment planning, which enables exact and scalable inference of key quantities such as scenario likelihoods and marginal probabilities.