A cost-optimal predictive operation scheme for sector-coupled energy plants with start-up delays and start-up costs

In this work we present a cost-optimal energy management scheme for sector-coupled energy plants, focusing on systems that enable gas-to-electricity, gas-to-heat, and power-to-heat conversions. To capture realistic operational challenges, the considered system model incorporates dynamic constraints, including start-up delays and off-time-dependent start-up costs. By accounting for the impact of these factors, we demonstrate on a case study that they can significantly reduce overall operational costs. The energy management problem is cast as a mixed-integer nonlinear programming (MINLP) problem, which is then solved within a model predictive control (MPC) framework. The proposed approach provides a structured methodology for real-time energy management, enhancing energy efficiency while minimizing costs.