4. Development of Financial Liability Index for Hydropower Plant with MCDM and Neuro-genetic Models

The population overgrowth along with technological advancement has increased the demand for Electricity all over the World. The cost of Electricity has been increased simultaneously. As the resources of conventional fuels are limited, alternate energy sources to replace fossil fuels are now preferred to supply the excess demand. Among all the sources of alternate energy, hydropower was found to be the most reliable but inexpensive source of alternative Energy. But locational implications and variation in kinetic Energy of water flow during the monsoon and non-monsoon seasons attracts sufficient amount of financial liability. Thus for any hydropower projects the financial liability are evaluated before approving the installation of the project. The conventional practices of liability analysis give equal importance to all the considered factors. But in reality not all the factors have the same importance on liability analysis of Hydropower projects. Thus some factors are overrated and some other under rated which resulted in erroneous decision making. The present investigation proposed a new method of liability analysis where all the major factors were given separate importance as decided from literature, Expert and local surveys. A financial liability index was also proposed to represent the financial liability of the project. The index was applied to hydro-power plants of different capacity and efficiency. The results are found to be coherent with the actual scenario. The index utilized various MCDM techniques followed by ANN architecture to create a flexible but cognitive instrument to analyse the financial liability of new hydro power project.