A Chance-constrained optimization model for design and operation of a reservoir: A case study

The available chance-constrained models for reservoir design and operation were modified, and implications studied using the data of the Ramiala reservoir in the Brahmani basin in Orissa (India). The constraints limited the permissible range of reservoir releases and storage volumes, achieved with certain percentage of exceedance of inflows to the reservoir. To solve the proposed chance-constrained model, the linear decision rule was applied, for it makes the solution easy and reduces considerably the number of possible operating policies that can be considered. Finally, the size (capacity) of the reservoir was minimized; an operating policy meeting water supply (irrigation, hydropower, domestic and industrial), flood control, recreation, and environmental requirements by 2051 AD was developed; and, considering various possible sizes of the reservoir, an economic feasibility analysis based on probability distribution of monthly inflows was studied. The optimum capacity of the reservoir has been estimated as 162.40 MCM (against the existing capacity = 86.00 MCM) that meets all the considered demands by 2051 AD 90% of times.