scholarly journals Short-term Load Forecasting System for Power System Based on Big Data

2021 ◽  
Vol 2143 (1) ◽  
pp. 012040
Author(s):  
Yang Donghui

Abstract Short-term load forecasting of power system is an important task of power distribution system. Accurate short-term load forecasting provides the best configuration for grid power generation and distribution, maximizing energy saving and ensuring stable operation. This paper aims to study the design of short-term load forecasting system of power system based on big data. On the basis of analyzing power system load forecasting algorithms, classification of load forecasting, characteristics of load forecasting and system design principles, each module of the system is designed in detail, and finally tested the performance of the system. The test results show that the system has no adverse reactions in the use of a large number of users and repeated operation for a long time. In the case of large throughput, the system has a satisfactory response time and relatively reliable system stability.

2011 ◽  
Vol 383-390 ◽  
pp. 5023-5027
Author(s):  
Zhi Xian Pi ◽  
Ru Zhi Xu ◽  
Jian Guo

Short-term load forecasting in power system is an important daily work in Dispatch Operation Department of Power System. The level of forecasting accuracy directly affects the operating economy and supply quality of power system.This paper adopts the rough sets to forecast short-term load. It designs an overall structure of forecasting the short-term load based on the rough sets, applies the rough sets to analyze the importance of attribute of each condition on decision-making attribute and then gets a reduced forecasting system, lists examples to forecast short-term load on the basis of the real historical data, and compare the results with the traditional decision-making tree algorithm. The results of this study prove that the rough sets is much practical in short-term load forecasting.


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