Data analytics for statistical characterization of prices and empirical resource investment planning in Indian electricity market

With the advent of technological developments, a large amount of data is being created and made available at every time instance. This work tries to leverage this data for useful interpretations and derives resource investment planning strategies. Data analytics can be a useful tool to understand the optimal locations, for resource investments in the grid. The study can be helpful in reducing the search space in an optimal resource investment planning problem. As a precursor data analytics study could help in forming policies that could complement a planning problem. India is a growing economy and the electric demand of the country is also increasing. There is a need to attract more investment in the generation side to meet the future loads. It is important to statistically characterize the electricity prices to find the potential investment regions in the grid. This paper gives an overview of the restructured power industry in India, the various market segments in existence and gives a detailed statistical analysis of the Day Ahead Electricity Market prices using Minitab and Statistics toolbox of MATLAB. It also discusses the operational issues like congestion management scheme followed and their effect on the area prices, that could help in empirical resource planning and policy making.