Editorial: Targeting the Optimal Design and Operational Flexibility of Steam Cycles and Steam Networks

Steam cycles and steam networks are essential for a wide range of thermal power plants and industrial processes. Today steam cycles are used not only in fossil-fired power plants and nuclear power plants but also as heat recovery cycles in gas turbine combined cycles (GTCCs) (Gülen 2019), integrated gasification combined cycles (IGCCs) and polygeneration plants (e.g., coproducing electricity and hydrogen or synthesis fuels) (Elsido et al., 2019). Steam networks and combined heat and power cycles are typically used to optimize the heat integration of a wide range of industrial processes (Luo et al., 2016). Steam cycles are used also in renewable technologies such as concentrated solar power plants (Gonzalo et al., 2019) and large biomass-fired plants (Amec-Foster-Wheeler 2016), as well as waste-to-energy plants (Beiron et al., 2019). While steam cycle components are considered mature technologies, it is important to note that each application features a specific optimal thermodynamic design of the steam cycle (i.e., cycle configuration and steam pressures/temperatures) as well as a tailored control strategy for off-design and ramping (Martelli et al.). While these criteria are well known for fired steam cycles and combined cycle power plants, those for novel energy systems (e.g., Integrated Solar Combined Cycles) are still an object of research and development efforts in both academia and industry [see, e.g., (Elsido et al. 2021), and (Temraz et al., 2021)]. Such efforts are spurred by the need of minimizing fuel consumption and the related environmental emissions. Furthermore, the increased penetration of renewable energy sources in the generation of electrical power recently raises technical and economic challenges for the operation of these plants. Existing thermal power plants have to be retrofitted with optimized components [e.g., warming and pre-warming systems for the steam turbine (Pehle et al., 2020)] and control systems (Casella et al., 2011) to improve their operational flexibility, such as ramping rates and shutdown/start-up times. Consequently, accurate dynamic simulation tools are being developed for developing novel equipment designs, control systems, and start-up procedures (Alobaid et al. 2017).