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Optimal Reservoir Operation Using Genetic Algorithm: A Case Study of Ukai Reservoir Project

Sumitra Sonaliya , Dr. T.M.V. Suryanarayana

Application of optimization techniques for determining the optimal operating policy of reservoirs is a major issue in water resources planning and management. Genetic Algorithm is an optimization technique, based on the principle of natural selection, derived from the theory of evolution, are popular for solving optimization problems. The main aim of the present study is to develop a policy for optimizing the release of water for the purpose of irrigation. The fitness function used is minimizing the squared deviation of monthly irrigation demand along with the squared deviation in mass balance equation. The months considered are from July to October for three years from year 2007 to 2009. The decision variables are monthly releases for irrigation from the reservoir and initial storages in reservoir at beginning of the month. The constraints considered for this optimization are the bounds for the releases and reservoir capacity. Results show that in the year 2007, for months of July and August, 625 and 1573.86 MCM of water is saved respectively. In the year 2008, for July 65.67 MCM, August 27.15 MCM, September 35.32 MCM and October 62.91 MCM of water is saved. In the year 2009, for July 49.18 MCM, August 35.48 MCM, and in October 43.51 MCM of water is saved. Hence, GA model, if applied to the Ukai reservoir project in Gujarat State, India, can completely satisfy downstream irrigation demands and releases are minimized which leads to considerable amount of saving in water.