Long-Term Joint Operation of Cascade Reservoirs Using Enhanced Progressive Optimality Algorithm and Dynamic Programming Hybrid Approach

Dynamic programming (DP) is one of the most classical methods adopted for reservoir operation. It reduces the computational efforts of complex high-dimensional problems by piecewise dimensionality reduction and provides the global optimums of the problems, but it suffers the “curse of dimensionality”. Progressive optimality algorithm (POA) has been used repeatedly in reservoir operation studies during last decades because it alleviates the “curse of dimensionality” of DP and has good convergence and extensive applicability. Nonetheless, POA encounters two difficulties in multi-reservoir operation applications. One is the transfer interrupt problem that makes the search procedure hard to achieve free allocation of water between two nonadjacent stages, and the latter is the dimensionality problem that leads to a low convergence rate. In order to overcome these deficiencies, this paper makes some enhancements to POA and proposes a hybrid approach combining the enhanced POA and DP (EPOA-DP) for long-term operation of cascade reservoir systems. In EPOA-DP, EPOA is employed to improve the quality of the solutions and DP is used to reduce the computational effort of the two-stage problem solution. The proposed approach was tested using a real world four-reservoir cascade system and a ten-reservoir benchmark test example, and the results demonstrate that it outperforms POA both in computational time and quality of the solution.