CANS RT
Last Update: 2024/02/01 12:00
CANS RT is a reservoir testbed which emulates the environment of real reservoir operations. The purpose of this reservoir is to intercept the water source from the upstream watershed, regulate the discharge of the spillway while maintaining a stable water supply at the water intake, and keep the water level of the reservoir within the normal range.
The historical records of the a real hydraulic facility were utilized to achieve inflow volume that matches the real environment of a reservoir, and we also designed the gate adjustment rules based on the same hydraulic facility.
Due to equipment limitations, a combination of three physical spillways and twelve virtual spillways was adopted, and the discharge volume at the moment was estimated based on the opening degree and water level of each gate by looking up the table. In addition, the storage capacity and water level of the reservoir are also estimated by looking up the table. Finally, the storage difference of the reservoir will be estimated by all the aforementioned variables.
We are honored to collaborate with the Water Resources Agency of the Ministry of Economic Affairs in Taiwan, obtaining authentic equipment from real hydraulic facilities. As a result, this research has been able to elevate the mathematical simulation of reservoir operations to the level of hardware emulation, enhancing the reference value of the generated dataset for our experiments.
The experimental results of this testbed will be organized into a comprehensive dataset, divided into multiple folders based on operational scenarios and seasonal inputs. For instance, in early 2024, four experiments were conducted, each corresponding to normal and non-normal operations during different seasons. Therefore, the dataset is categorized into eight folders, each containing monitoring records of the HMI and network traffic records (via Wireshark) of the gate control system. Additionally, a README file will be included to provide detailed descriptions of the physical significance of each attribute in the dataset, along with comprehensive explanations of the reservoir's operational states.
