In the design of refrigeration process, when taking into account the characteristics of refrigeration working medium, the operation efficiency of refrigeration cycle and uncertain environmental conditions, the calculation will be difficult to solve, which is the flexible problem of operation under uncertain conditions studied in this paper.
Professor Zhu Lingyu's research group in the School of Chemical Engineering proposed an adaptive fine grid feasible region search strategy to search the high energy efficiency refrigerant with maximum operating flexibility for the simultaneous optimization of process and working medium considering operating flexibility under uncertain conditions.
The chemical process is easily affected by various uncertain factors in actual operation and deviates from the optimal calibration condition. These uncertainties mainly come from three aspects :(1) the uncertainty of model parameters used in process design; (2) the uncertainty of internal factors (such as heat and mass transfer coefficient and reaction rate); (3) The uncertainty of external factors of the process, such as feed status, ambient temperature and pressure, and product market demand.
The operational flexibility of a chemical process system can be described by the feasible region in the uncertain parameter space. In THE feasible domain, the requirements of product specification, economy and safety are always satisfied when the process control variables are adjusted at will. Firstly, the feasible region is determined, and then the flexibility of the process system is further quantified by the maximum scaling factor based on the inner hyperrectangle or the flexibility index based on the hypervolume ratio.
This paper proposes a strategy to efficiently maintain grid connectivity information using bidirectional linked list data structure, and uses uniform perturbation sampling method to refine and locate feasible domain boundaries. At the same time, this strategy supports the direct calculation of feasible hypervolume by the sum of feasible hypercubes in the grid, without the use of shape reconstruction techniques. The proposed adaptive grid search strategy can capture the complex shape of the region, reduce the sampling cost and have no randomness.
Schematic of adaptive fine grid search strategy
This method was applied to the single-stage steam compression refrigeration cycle, and the computer-aided refrigerant optimization was carried out to maximize the operational flexibility and energy efficiency, and the refrigerant distribution based on the flexibility and energy efficiency optimization was selected.
Flexible maximum working medium for single stage steam compression refrigeration cycle
The results for "An adaptive refined grid search strategy for assessing the operational flexibility and application on refrigerant Selection "was published in the AIChE Journal. The first author is Jiayuan Wang, Lecturer in the School of Chemical Engineering, the second author is Robin Smith, Professor of the University of Manchester, UK, and the corresponding author is Lingyu Zhu, Professor of the School of Chemical Engineering.
AIChE Journal is one of the most influential journals in the international chemical industry, covering the most important and up-to-date technical research in the core areas of chemical engineering and other related engineering disciplines.
Post time: Oct-21-2022