Cascade hydropower systems optimal operation: implications for Iran’s Great Karun hydropower systems

• Published in: Applied water science Vol. 9; no. 3; pp. 1 - 9
• Main Authors: Jamali, Saeed, Jamali, Behzad
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.04.2019; Springer Nature B.V; SpringerOpen
• Subjects: Agricultural management; Algorithms; Aquatic Pollution; Comparative Law; Computer simulation; Dams; Decision making; Earth and Environmental Science; Earth Sciences; Energy conservation; Energy demand; Evaluation; Frameworks; GANetXL; Hydroelectric power; Hydroelectric power generation; Hydroelectricity; Hydrogeology; Hydropower; Industrial and Production Engineering; International & Foreign Law; Karun River basin; Mathematical models; Mental task performance; Multi-reservoir system operation; Nanotechnology; Optimization; Original Article; Private International Law; Reliability; Reservoir releases; Reservoirs; River basins; Rivers; Simulation; Simulation–optimization; Waste Water Technology; Water Industry/Water Technologies; Water Management; Water Pollution Control; Water resources; WEAP; Multi-reservoir system operation; Hydropower; Karun River basin; Simulation–optimization; WEAP; GANetXL
• ISSN: 2190-5487; 2190-5495
• DOI: 10.1007/s13201-019-0939-3

Water resources optimal allocation in large complex water systems such as multi-reservoir dams is a challenging task for decision makers. Wide range of decision variables as well as difficult nonlinear optimization problems (highly nonlinear problems) make it difficult to use optimization approaches. Alternatively, simulation–optimization approaches are then providing more realistic and applicable solution. This study presents a simulation–optimization framework for extracting monthly long-term operation rules. This method is applied to Karun River Basin including six multi-objective (hydropower generation, agricultural and environmental water supplement) cascade dams. In this regard, Water Evaluation and Planning System is used as the simulation model coupled with an optimization model. Decision variables include (1) monthly variation of top of buffer parameter in reservoirs where the reservoir releases water to meet the required demand and (2) monthly priority for filling of the reservoirs. Two-objective NSGA-II algorithms are used to minimize sum of squares unmet energy and agricultural water demands within two scenarios. The results show that the reliability of the generation of hydroelectricity in Karun River Basin has been increased sufficiently. Results showed that the scenario 2 (an aggregate energy demand at the system level) has better performance in terms of reliability (91.4% compared to 89.6%) and efficiency of centralized approach in which all reservoirs are operated in an integrated management scheme.