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Faced with an ever-growing resource scarcity and environmental regulations, the last 30 years have witnessed the rapid development of various renewable power sources, such as wind, tidal, and solar power generation. The variable and uncertain nature of these resources is well-known, while the utilization of power electronic converters presents new challenges for the stability of the power grid. Consequently, various control and operational strategies have been proposed and implemented by the industry and research community, with a growing requirement for flexibility and load regulation placed on conventional thermal power generation. Against this background, the modelling and control of conventional thermal engines, such as those based on diesel and gasoline, are experiencing serious obstacles when facing increasing environmental concerns. Efficient control that can fulfill the requirements of high efficiency, low pollution, and long durability is an emerging requirement. The modelling, simulation, and control of thermal energy systems are key to providing innovative and effective solutions. Through applying detailed dynamic modelling, a thorough understanding of the thermal conversion mechanism(s) can be achieved, based on which advanced control strategies can be designed to improve the performance of the thermal energy system, both in economic and environmental terms. Simulation studies and test beds are also of great significance for these research activities prior to proceeding to field tests. This Special Issue will contribute a practical and comprehensive forum for exchanging novel research ideas or empirical practices that bridge the modelling, simulation, and control of thermal energy systems. Papers that analyze particular aspects of thermal energy systems, involving, for example, conventional power plants, innovative thermal power generation, various thermal engines, thermal energy storage, and fundamental heat transfer management, on the basis of one or more of the following topics, are invited in this Special Issue: • Power plant modelling, simulation, and control; • Thermal engines; • Thermal energy control in building energy systems; • Combined heat and power (CHP) generation; • Thermal energy storage systems; • Improving thermal comfort technologies; • Optimization of complex thermal systems; • Modelling and control of thermal networks; • Thermal management of fuel cell systems; • Thermal control of solar utilization; • Heat pump control; • Heat exchanger control.

supercritical circulating fluidized bed --- boiler-turbine unit --- active disturbance rejection control --- burning carbon --- genetic algorithm --- Solar-assisted coal-fired power generation system --- Singular weighted method --- load dispatch --- CSP plant model --- transient analysis --- power tracking control --- two-tank direct energy storage --- electronic device --- flip chip component --- thermal stress --- thermal fatigue --- life prediction --- combustion engine efficiency --- dynamic states --- artificial neural network --- dynamic modeling --- thermal management --- parameter estimation --- energy storage operation and planning --- electric and solar vehicles --- ultra-supercritical unit --- deep neural network --- stacked auto-encoder --- maximum correntropy --- heat exchanger --- forced convection --- film coefficient --- heat transfer --- water properties --- integrated energy system --- operational optimization --- air–fuel ratio --- combustion control --- dynamic matrix control --- power plant control --- high temperature low sag conductor --- coefficient of thermal expansion --- overhead conductor --- low sag performance --- chemical looping --- wavelets --- NARMA model --- generalized predictive control (GPC) --- steam supply scheduling --- exergetic analysis --- multi-objective --- ε-constraint method

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This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems.

manufacturing process --- additive manufacturing --- IoT --- computer systems and networks --- 3D printing --- digital twin --- Industry 4.0 --- pharmaceutical manufacturing --- biopharmaceutical manufacturing --- process modeling --- mixed-integer linear programming --- bin-packing problem --- material requirements planning --- agri-supply chain management --- variable production rate --- optimal resources --- imperfect production --- eco-efficient production --- closed-loop scheduling --- scheduling stability --- optimal control and scheduling --- fouling --- heat exchanger networks --- continuous manufacturing --- bioprocessing --- process systems engineering --- single-use technology --- AGV—Automated Guided Vehicles --- DES—Discrete Event Simulation --- FMS—Flexible Manufacturing Systems --- OEE—Overall Equipment Efficiency --- WCLcWorld Class Logistic --- abrasive water jet --- cutting --- surface quality --- quality prediction --- 3D simulation modeling and analysis --- model implementation --- bottleneck analysis --- production costs --- resource conservation --- smart manufacturing --- edge computing --- machine learning --- blockchain --- Industrial Internet of Things --- inventory management --- supply chain --- multi-echelon --- stochastic programming --- reinforcement learning --- digitalisation --- model-based --- computational engineering --- process simulation --- LNG terminal --- operational optimization --- BOG compressor --- MINLP --- enterprise process architecture --- new technologies integration --- process intelligence --- real-time monitoring --- fault detection --- predictive process adjustment --- vacuum gripper --- sensor data --- Tri-X Intelligence --- cyber-physical systems --- human-cyber systems --- intelligent systems --- intelligent manufacturing --- multi-parametric programming --- explicit MPC --- enterprise-wide optimisation --- set-point tracking --- algebraic geometry --- continuous pharmaceutical manufacturing --- model predictive control --- state estimation --- quality-by-control (QbC) --- glidant effects --- plant-model mismatch --- regional logistics --- low-carbon economy --- cloud model --- comprehensive evaluation --- Beijing-Tianjin-Hebei region --- pharmaceutical manufacture --- uncertainty --- operational flexibility --- operational envelopes --- modeling --- n/a --- AGV-Automated Guided Vehicles --- DES-Discrete Event Simulation --- FMS-Flexible Manufacturing Systems --- OEE-Overall Equipment Efficiency