The Short-Term Load Forecasting Based on Rough Set

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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Research on Improving Short-term Load Forecasting Accuracy in Regional Power System

2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID) ◽

10.1109/icasid.2019.8924993 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xiaoling Shen ◽

Chonghua Li

Keyword(s):

Power System ◽

Load Forecasting ◽

Regional Power ◽

Short Term ◽

Forecasting Accuracy ◽

Short Term Load Forecasting

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

Journal of Physics Conference Series ◽

10.1088/1742-6596/2143/1/012040 ◽

2021 ◽

Vol 2143 (1) ◽

pp. 012040

Author(s):

Yang Donghui

Keyword(s):

Big Data ◽

Power System ◽

Distribution System ◽

Load Forecasting ◽

System Stability ◽

Stable Operation ◽

Short Term ◽

Power Distribution System ◽

Short Term Load Forecasting ◽

Forecasting System

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.

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Short-term load forecasting using Theta method

E3S Web of Conferences ◽

10.1051/e3sconf/20198401004 ◽

2019 ◽

Vol 84 ◽

pp. 01004 ◽

Cited By ~ 1

Author(s):

Grzegorz Dudek

Keyword(s):

Empirical Studies ◽

Load Forecasting ◽

Seasonal Cycles ◽

Short Term ◽

Forecasting Accuracy ◽

Forecasting Methods ◽

Short Term Load Forecasting ◽

Data Definition ◽

System Data ◽

Theta Method

The Theta method attracted the attention of researchers and practitioners in recent years due to its simplicity and superior forecasting accuracy. Its performance has been confirmed by many empirical studies as well as forecasting competitions. In this article the Theta method is tested in short-term load forecasting problem. The load time series expressing multiple seasonal cycles is decomposed in different ways to simplify the forecasting problem. Four variants of input data definition are considered. The standard Theta method is uses as well as the dynamic optimised Theta model proposed recently. The performances of the Theta models are demonstrated through an empirical application using real power system data and compared with other popular forecasting methods.

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