ENetOPT ensures mass and energy balance among individual equipment, regulates the balance at the header connecting the equipment, and achieves overall network balance. It tracks the inflows and outflows of substances and energy for each equipment to maintain a consistent balance, and regulates the exchange of substances and energy between interconnected headers. The optimization algorithms and control mechanisms of ENetOPT work together to achieve a consistent balance.
Major reasons of Imbalance
ENetOPT with Gross error detection
Gross error detection is a data analysis technique used in ENetOPT to identify significant errors or anomalies in a given dataset.
Statistical methods or comparisons with existing models can be employed to detect outliers. Alternatively, data can be examined against predefined thresholds to identify anomalies.
Gross error detection helps ensure data integrity and identifies erroneous values or abnormalities that may impact the optimization process, thereby facilitating the generation of reliable results.
