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

机译:数据分析,用于印度电力市场中价格的统计表征和经验性资源投资计划

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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.
机译:随着技术发展的到来,每个时刻都在创建和提供大量数据。这项工作试图利用这些数据进行有用的解释,并得出资源投资计划策略。数据分析是了解最佳位置的有用工具,可用于网格中的资源投资。该研究有助于减少最优资源投资计划问题中的搜索空间。作为先驱,数据分析研究可以帮助制定可以补充规划问题的政策。印度是一个发展中的经济体,该国的电力需求也在增加。有必要在发电方面吸引更多的投资,以满足未来的需求。重要的是统计统计电价,以找到电网中的潜在投资区域。本文概述了印度的重组电力行业以及现有的各个细分市场,并使用MATLAB的Minitab和Statistics工具箱对日间电力市场价格进行了详细的统计分析。它还讨论了诸如拥塞管理方案之类的运营问题及其对地区价格的影响,这可能有助于经验性资源规划和政策制定。

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