| Title |
Covid-19 Impact on Uttarakhand State Electricity Load Consumption and Generation |
| ID_Doc |
40619 |
| Authors |
Kumar, R; Ranjan, R; Verma, M |
| Title |
Covid-19 Impact on Uttarakhand State Electricity Load Consumption and Generation |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/ComPE53109.2021.9752439 |
| Abstract |
\Due to the effect of Covid-19 the pattern of energy consumption of Uttarakhand State has affected during lockdown. Since the inception of Covid-19 in Uttarakhand there has drastic change in electricity consumption in thirteen districts of the State including Dehradun which is also a Smart City. It has reported that there is decrease in electricity consumption in the year 2020-21. In this study the long-term load forecasting using Artificial Neural Network is used as per the information released by Uttarakhand Electricity Regulatory Commission (UERC) in their tariff order for Financial Year 2021-22. There is eleven million population in Uttarakhand at present. During economic shutdown in Uttarakhand State the power utilities has faced the challenge of electricity generation, transmission, and distribution. It has been observed that during Covid-19 there is 939.97 million units generated energy loss has faced by power utilities companies in Uttarakhand. Uttarakhand is a emerging State where lots of new Technologies are in pipeline. In this Study the forecasted results is for nine years (2022-2030) which represents that there will be sudden rise in electricity consumption after 2025 to 2030 in Uttarakhand due to the intervention of electric vehicles. In Uttarakhand Dehradun is also a smart city where lots of IoT devices have been deployed across city which are are also consuming electricity. This study has reduced the forecast error upto 7.17 % so that there would be minimum revenue loss in future to the power utilities in Uttarakhand. |
| Author Keywords |
Covid-19; Million Units; Long Term Load Forecasting; Smart City |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000942046000175 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Engineering, Biomedical |
| Research Area |
Computer Science; Engineering |
| PDF |
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