The SimTech Gasifier-twin solution uses rigorous mechanism-based gasification models capable of characterizing current mainstream entrained-flow gasifiers, such as pulverized coal gasifiers represented by the Aerospace gasifier and Shell gasifier, and coal-water slurry gasifiers represented by the Jinhua gasifier and multi-nozzle opposed gasifier. Using data acquisition and management, rigorous gasification mechanism models and optimization algorithms, and system integration technology, it achieves digital twinning and online optimization of the gasification process. Data acquisition is implemented through OPC, Web API, and other methods, with relevant algorithms used for data processing. Based on the rigorous mechanism model, online optimization is performed in real time through optimization algorithms (SOP and linear approximation algorithms), with calculated optimal values sent to the APC system.

The SimTech FCC-twin solution can build rigorous models covering the FCC reactor-regenerator, fractionator, absorption-stabilization system, compressors, heat exchangers, furnaces, and other equipment. It establishes connections between models and unit data, reads data from different sources, and completes functions including data preprocessing, reconciliation, equipment performance monitoring, and real-time optimization. These functions can be automatically completed online by the model according to user-defined calculation cycles, with results presented to clients in charts or reports as operational guidance.

The SimTech Oil & Gas-twin solution automatically collects real-time and laboratory data from the unit site, performs steady-state detection using the collected data. If the steady-state detection fails, it indicates that the unit data is unstable and cannot be used as a basis for subsequent unit calculations. After passing steady-state detection, the collected data undergoes data reconciliation to remove measurements with gross errors and correct random errors in measured values, ultimately producing a set of data that satisfies the unit's material and energy balances. After data reconciliation, the software performs full-process simulation based on the reconciled data, with simulation results serving as the core foundation for subsequent optimization. The reconciled data is fed into the process simulation software for full-process simulation and unit performance calculation, comprehensively monitoring the operating unit's material balance, energy balance, process performance, equipment performance, energy consumption, energy analysis, costs, and economic benefits in real time. Through optimizer calculations, optimal operating parameters are obtained based on different objective function requirements, guiding user optimization or sent to APC as setpoint values, forming a closed-loop RTO to achieve energy conservation, consumption reduction, and maximized economic benefits for the unit.

The customer requirements of the SimTech Compressor-twin solution encompass performance monitoring, fault prediction, energy efficiency optimization, remote monitoring, personnel training, as well as customization and scalability. To meet these needs, the digital twin system comprehensively employs advanced technologies including IoT, big data, and artificial intelligence, providing customers with a comprehensive, efficient, and intelligent compressor management solution. The SimTech Compressor-twin system can obtain actual operating data from the real-time database of the compressor system in the actual plant, generating steady-state and dynamic simulations of the compressor through data reconciliation and online simulation technology, which constitutes the core content of this system. Based on steady-state simulation, functions such as performance prediction and remote HMI can be extended; based on dynamic simulation, functions such as personnel training, review and prediction, and deduction and optimization can be extended. The system also provides flexible integration interfaces for functional interaction with other systems.