Work

Analysis of Methods of Increasing Data Reliability for Problems of Short Term Forecasting of Nodal Load

Year: 2021

Type: article

Abstract: A comparative analysis of clustering methods was performed to identify gaps and anomalous values in the data. Data from the northwestern region of the United States were used for evaluation. According to the analysis results, it was found that the use of the DBSCAN method leads to a much smaller number of false positives. An algorithm for two-stage data validation using clustering and time series decomposition methods is proposed. Ref.9, fig. 3, tables 3.

Source: Praci Institutu elektrodinamiki Nacionalanoi akademii nauk Ukraini

DOI: 10.15407/publishing2021.60.051

Authors: P.V. Shymaniuk, V.O. Miroshnyk

Institutions: National Academy of Sciences of Ukraine, Institute of Electrodynamics

Language: English

Topic: Energy Load and Power Forecasting

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4200319566

FWCI:

Cites: 6

Cited by:

Related to: 10