Document Type : Original Article
Authors
- Mehdi Yaltaghian Khiabani 1
- S. M. Hashemy-Shahedani 2
- Mohammad Ebrahim Bani Habib 3
- Yousef Hassani 4
1 M.Sc. Student, Water Engineering Department, College of Aburaihan, University of Tehran, Tehran, Iran
2 Assistant Professor, Water Engineering Department, College of Aburaihan, University of Tehran, Tehran, Iran
3 Associate Professor, Water Engineering Department, College of Aburaihan, University of Tehran, Tehran, Iran
4 Ministry of Energy
Abstract
Inefficient operational methods, in distribution of water within irrigation canals, call for applying more efficient ways such as using automation systems. This study assesses capabilities of the automatic operational systems, including centralized Model Predictive Control (MPC) and decentralized Proportional-Integral (PI) controller in enhancing the fairly water delivery throughout the Roodasht main irrigation canal. Existing canal’s operational condition was compared with operational status employing PI and MPC control systems. Comparison was conducted using water level error-based performance indicators of MAE and IAE, and equity indicator. Two operational scenarios including normal and severe inflow fluctuation were assigned. According to results of first scenario, upstream PI system resulting to better indicators of MAE and IAE values rather than other systems. MPC controller leading to better performance in comparison with upstream and downstream PI configurations. Application of MPC system resulted to 12% improvement in equity indicator. In the second scenario with sever inflow fluctuations at the headgate, the maximum IAE and MAE indices for MPC controller were 3.53% and 1.45%, respectively, while these indicators for decentralized systems exceeded 100%, demonstrating the inability of the decentralized systems to control the flow rate in severe water shortage conditions. Finally, calculated equity indicator in second scenario, for current operation, upstream and downstream PI and MPC, were 39.23%, 18.71%, 15.95%, and 4.33%, respectively. Results reveal that the application of centralized MPC controller has significantly improved the equity indicator by 35%.
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