Area Control Error Forecasting using Deep learning for an Interconnected Power System

Hussein Abdeltawab, Amr Radwan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Area Control Error (ACE) is an essential indicator of the load-generation power imbalance for the transmission system operator. ACE is used to correct the generation dispatch to compensate for frequency deviation. ACE also indicates the required power export or import in an interconnected power system. Unlike wind and solar power prediction, there has been no work to forecast the ACE in the power system. For an interconnected extensive transmission system, the ACE is considered a volatile time-varying signal. For an accurate ACE prediction, this work represents a deep learning-based forecasting model. The model decomposes the ACE signal using the discrete wavelet transform (DWT) and utilizes the bidirectional long short-term memory (BiLSTM) for the prediction. The proposed forecasting technique is trained to capture the deep temporal features of the signal with higher accuracy when compared to other methods. Two ACE datasets with sample times 1-minute and 10 minutes are predicted. The real data is gathered from Pennsylvania, New Jersey, and Maryland interconnection (PJM), USA. To evaluate the proposed technique, it is compared to other benchmark forecasting networks.

Original languageEnglish (US)
Title of host publication2022 IEEE Power and Energy Conference at Illinois, PECI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665402293
DOIs
StatePublished - 2022
Event2022 IEEE Power and Energy Conference at Illinois, PECI 2022 - Champaign, United States
Duration: Mar 10 2022Mar 11 2022

Publication series

Name2022 IEEE Power and Energy Conference at Illinois, PECI 2022

Conference

Conference2022 IEEE Power and Energy Conference at Illinois, PECI 2022
Country/TerritoryUnited States
CityChampaign
Period3/10/223/11/22

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Energy Engineering and Power Technology

Fingerprint

Dive into the research topics of 'Area Control Error Forecasting using Deep learning for an Interconnected Power System'. Together they form a unique fingerprint.

Cite this