Application of Neural Networks to Power Systems for Electrical Load Forecasting

Mithilesh Singh, Shubhrata Gupta
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Abstract

The artificial neural network system referred as parallel distributed processors conserve the information previously learnt but same time accessible to learning new information. This paper gives a brief indication of artificial neural network and its application in power system for electrical load forecasting which can further be used for enhancement of power quality. The accuracy of load forecasts has a significant effect on economy and control of power system operations for reliable and secure operation of power system. In this paper the accurate and real time data are collected from Chhattisgarh load dispatch centre of western grid of India of year 2018. This data of power flow is simulated using artificial neural network. The purpose of short-term forecasting is to satisfy as much as possible, to improve prediction accuracy.
神经网络在电力系统负荷预测中的应用
人工神经网络系统被称为并行分布式处理器,它既保留了以前学习过的信息,又可以同时学习新的信息。本文简要介绍了人工神经网络及其在电力系统负荷预测中的应用,并将其应用于改善电能质量。负荷预测的准确性对电力系统运行的经济性和控制性,对电力系统的可靠、安全运行有着重要的影响。本文采集了印度西部电网恰蒂斯加尔邦负荷调度中心2018年的准确实时数据。利用人工神经网络对这些潮流数据进行了仿真。短期预测的目的是为了满足尽可能多的需求,提高预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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