Paper Details

ABSTRACT

Operation of reservoirs, often for conflicting purposes, is a difficult task. The solution to the problem is difficult because of the large number of variables involved, the non-linearity of system dynamics, the stochastic nature of future inflows, and other uncertainties of the system. The uncertainty associated with reservoir operations is further increased due to the on-going hydrological impacts of climate change. Therefore, various artificial intelligence techniques such as genetic algorithms, antcolony optimization, and fuzzy logic are increasingly being employed to solve multi-reservoir operation problems. Here the Genetic Algorithm technique is used for reservoir operation of Ukai Reservoir for hydropower generation. For doing optimization, objective function is formulated which is subjected to various constraints. Constraints include continuity equation, reservoir storage constraints, release constraint and overflow constraint. Monthly data for the study are used of year 2007 to 2011. Three models are developed. In this study, there are three models are developed from 2007. Genetic algorithm is a robust search technique to solve problems which needs optimization. Genetic algorithm is based on Darwin’s theory of Survival of the fittest. GA reduces the difference between releases and demand and returns the value of the fitness function / Objective function. The releases to be made from the reservoir are also obtained. The releases obtained from all these models are compared with the actual releases made from the reservoir. The models are also compared based on their fitness values. In 2007, using Genetic Algorithm the generation of power can be increased 9.22% through optimal releases. There is 7.14% increase in optimal reservoir release. For average data of three year, using Genetic Algorithm the generation of power can be increased to 7.49% through optimal releases. There is 5.30% variation between existing and optimal reservoir release. In 2009, the generation of power can be increased to 5.15% through optimal releases. There is 4.90 % variation between existing and optimal reservoir release.