A I Electricity Demand Projection - Copy this React, Tailwind Component to your project

Problem Statement Title To develop an Artificial Intelligence (AI) based model for electricity demand projection including peak demand projection for Delhi Power system Description Background: The load profile of power requirement in NCT of Delhi is highly peculiar. We are witnessing huge load variations during the winter and summer months and also during day and night during the same 24 hour window. This causes imbalance in matching the requisite power purchase with the electricity demand. Description: The peak load in Delhi touched 8300 MW this summer while the minimum load during winters goes as low as 2000 MW. The peak during the summer months also occurs twice i.e. first during the day time at about 15:30 hrs and second time in night hours after 23:00 hrs. Further, the solar generation comes during the day time and wanes by the evening hours thereby lending a Duck curve effect. Solar plants have been allowed +/ 15% variation by CERC. Further, there is uneven load growth in the city, the upcoming areas are witnessing huge load growth while the developed areas are having the lower organic load growth. In addition to that the load curve in Delhi is highly peaky in nature due to the fact that most of the load is domestic and commercial load while industrial load is minimal. Here it may be taken note that while in other States, industrial load which is 24 x 7 in nature lends stability to the overall load curve of the State. Further, in Delhi agricultural load is minimal. In bigger States, having considerable agricultural load, the supply on agricultural feeders is normally given when ample power is available at cheaper rates, especially during early morning hours/ night hours, which in turn provides stability to the State' Transmission and Distribution network and also balances power purchase stipulation. Most of the Long Term power is available RTC (Round the Clock) and Slot wise power is more expensive. Expected Solution: An Artificial Intelligence based model be developed with suitable compensation methodology to factor the weather effects (like temperature humidity, and wind speed, rains/showers), public holidays/ weekly holidays, natural load growth, and real estate development.