Abstract
Electricity is one of the essential part of our life. With the increase in consumption of resources the demand of electricity is also increased. Uttarakhand as hilly state is approaching towards implementation of new Technologies and Techniques in the area of growth and suistainable development. Due to the implementation of better road infrastructure, tourism connectivity and IoT devices in various projects and inclusion of electric vehicles and their charging infrastructure in Uttarakhand State the demand of electricity has also increased. The Uttarakhand State has planned the establishment of new infrastructure by providing relaxation on various taxes and option of subsidy to investors. The exemption on xed electricity charges is provided to investors in Uttarakhand. The highest part of Electricity Generation is based on Hydro Power in Uttarakhand. By establishment of new infrastructure in Uttarakhand it would be a thrust to load generation companies to produce demanded of electricity on time. In this study the long-term load forecasting from 2022 to 2030 is analysed using Articial Neural Network. The input data is received from Uttarakhand Electricity Regulatory Commission and Uttarakhand Power Corporation Limited. The prediction is based on last 10 years data of historical load, GDP, Population, and past two years data of electric vehicles, and charging infrastructure. In this study, it has reported that by 2030 there would be huge change in infrastructure and most of diesel and petrol vehicles would come on electric vehicles. This study is focused on the Long-Term Load Forecasting in Uttarakhand State where electric vehicles and charging infrastructure load requirement is also calculated. Using Deep Learning Technique in this paper Articial Neural Network is used for forecasting the results. This tool is used to identify the consumption pattern of electricity in Uttarakhand State for further nine years from 2022 to 2030. The Government of Uttarakhand has planned Vision 2030 for the sustainable development in Uttarakhand.
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