Load forecasting using statistical time series model in a medium voltage distribution network

被引：0

作者：

Matsila, Hulisani ^{[1
]}

Bokoro, Pitshou ^{[1
]}

机构：

[1] Univ Johannesburg, Dept Elect & Elect Engn Technol, Johannesburg, South Africa

来源：

IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2018年

关键词：

Time series analysis; auto-regressive integral moving average; load forecasting; mean absolute percentage error;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, the suitability of statistical time series technique in the forecasting of load demand of a public hospital facility is tested. The hospital facility is supplied from a medium voltage distribution network. Historical data recorded over a period of three months are used for this purpose. The R-Studio package software is sourced to examine the shape of the time series pattern. The Box-Jenkins seasonal ARIMA model is subsequently applied in an attempt to forecast future series data and thereby predicting load demand pattern likely to be expected by the hospital facility. The suitability of this prediction technique is verified on the basis of the MAPE. Results show MAPE deviation of 3.91% from actual load data measured.

引用

页码：4974 / 4979

页数：6

共 50 条

[31] Load forecasting method considering temperature effect for distribution network
Meng, Xiao Fang
Zhang, Shu Xuan
Wang, Jun
Wu, Shi Hong
2016 INTERNATIONAL CONFERENCE ON MECHATRONICS, MANUFACTURING AND MATERIALS ENGINEERING (MMME 2016), 2016, 63
[32] Multi-step Time Series Forecasting of Electric Load Using Machine Learning Models
Masum, Shamsul
Liu, Ying
Chiverton, John
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2018, PT I, 2018, 10841 : 148 - 159
[33] Smard Grid Software Applications for Distribution Network Load Forecasting
Feinberg, Eugene A.
Fei, Jun
Hajagos, Janos T.
Rossin, Richard J.
PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON SMART GRIDS, GREEN COMMUNICATIONS AND IT ENERGY-AWARE TECHNOLOGIES (ENERGY 2011), 2011, : 76 - 80
[34] Short-term hourly load forecasting using time-series modeling with peak load estimation capability
Amjady, N
IEEE TRANSACTIONS ON POWER SYSTEMS, 2001, 16 (03) : 498 - 505
[35] Short-term hourly load forecasting using time-series modeling with peak load estimation capability
Amjady, N
IEEE TRANSACTIONS ON POWER SYSTEMS, 2001, 16 (04) : 798 - 805
[36] Intraday time series load forecasting using Bayesian deep learning method—a new approach
D. Kiruthiga
V. Manikandan
Electrical Engineering, 2022, 104 : 1697 - 1709
[37] Process Model Forecasting Using Time Series Analysis of Event Sequence Data
De Smedt, Johannes
Yeshchenko, Anton
Polyvyanyy, Artem
De Weerdt, Jochen
Mendling, Jan
CONCEPTUAL MODELING, ER 2021, 2021, 13011 : 47 - 61
[38] Statistical Load Time Series Analysis for the Demand Side Management
Grabner, Miha
Souvent, Andrej
Blazic, Bostjan
Kosir, Andrej
2018 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE), 2018,
[39] Load Forecasting Method for Power Distribution Networks Oriented towards Time Series Simulation with Deep Learning Method
Lu, Xiang
Wang, Hongyu
Zhang, Jinpeng
Han, Zhongxiu
Qi, Shenglong
Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
[40] A New Short-term Power Load Forecasting Model Based on Chaotic Time Series and SVM
Niu, Dongxiao
Wang, Yongli
Duan, Chunming
Xing, Mian
JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2009, 15 (13) : 2726 - 2745

← 1 2 3 4 5 →