New Approach for Long Term Electricity Load Forecasting for Uttarakhand State Power Utilities using Artificial Neural Network

Rakesh Kumar, R. Ranjan, M. Verma
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引用次数: 1

Abstract

The reliable and continuous power supply is must for the today’s era where most of works in every human’s life is based on electricity. In Uttarakhand due to increasing requirement of electricity load and various Transmission and Distribution losses and other obstructions, the Power Generation and DISCOMs are working very closer to the energy demand and generation. The generated electricity cannot be stored efficiently, due to this reason so the electrical load is managed by power utilities for a small approach. The Forecasting of electricity is essential for Power Generation, Transmission and Distribution companies. This study is based on Long Term Load Forecasting using Artificial Neural Network. Due to long duration of forecast it is difficult to foreseen off-peak load demand and this study is based on Long Term Electricity Load Forecasting in Uttarakhand State. The data of Population, GDP, Historical Load from 2011 to 2020 is used as input layer in three-layer feed forward neural network for training, validation, and testing. As a new approach the data of renewal energy source (solar power plants, biogas) and State Gas Generation Station, Electric Vehicle and Charging Infrastructure for Electrical Vehicle is used as input data. The forecasting of electricity load in Uttarakhand for long terms is calculated from 2021 to 2030. The Government of Uttarakhand has launched Vision 2030 for Uttarakhand where the main aim is to accelerate economic growth in Uttarakhand by inviting investors and promotion of free waiver policies on long term infrastructure setup.
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基于人工神经网络的北阿坎德邦电力公司长期负荷预测新方法
当今时代,每个人生活中的大部分工作都是基于电力的,可靠和持续的电力供应是必不可少的。在北阿坎德邦,由于电力负荷需求的增加以及各种输配电损失和其他障碍,发电和DISCOMs的工作非常接近能源需求和发电。由于这个原因,产生的电力不能有效地储存,所以电力负荷是由电力公司管理的一个小方法。电力预测对发电、输配电企业来说是必不可少的。本研究是基于人工神经网络的长期负荷预测。由于预测持续时间较长,因此难以预测非峰负荷需求,本研究基于北阿坎德邦长期电力负荷预测。采用2011 - 2020年人口、GDP、历史负荷数据作为三层前馈神经网络的输入层,进行训练、验证和测试。采用可再生能源(太阳能电站、沼气)和国家燃气电站、电动汽车和电动汽车充电基础设施数据作为输入数据,是一种新的方法。北阿坎德邦的长期电力负荷预测从2021年到2030年进行计算。北阿坎德邦政府启动了北阿坎德邦2030年愿景,其主要目标是通过邀请投资者和促进长期基础设施建设的免费豁免政策来加速北阿坎德邦的经济增长。
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