Carbon capture and storage can both reduce greenhouse gas emissions and provide
negative emissions to contribute to the transition to a net-zero society. The contribution of …

It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

The concepts of risk aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. The statistical learning community has …

Efficiently embedding and/or integrating mechanistic information with data-driven models is
essential if it is desired to simultaneously take advantage of both engineering principles and …

Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and
optimising modern electrical power systems over multiple periods. PyPSA includes models …

This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in
dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic …

In this paper, we present a review of deterministic software for solving convex MINLP
problems as well as a comprehensive comparison of a large selection of commonly …

Advanced building control strategies like model predictive control and reinforcement
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …

The evolving nature of electricity production, transmission, and consumption necessitates an
update to the IEEE's Reliability Test System (RTS), which was last modernized in 1996. The …

In recent years, the power system research community has seen an explosion of novel
methods for formulating and solving power network optimization problems. These emerging …