EWMA control charts to monitor energy output in combined cycle power plant: a new approach based on RBS profiling

Electric energy production frequently uses combined cycle power plants (CCPPs) to handle peak loads. CCPPs must be continuously monitored for power performance to enhance the electrical output power. The electrical output datasets often show asymmetric behaviour; therefore, the Birnbaum-Saunders (BS) distribution is one of the potential models for fitting such datasets. In this study, novel exponentially weighted moving average (EWMA) control charts based on the Reparametrised Birnbaum-Saunders (RBS) regression model are developed. We perform a simulation study to evaluate the effectiveness of derived approaches in terms of run length characteristics. Moreover, a case study on the combined cycle power plant's (CCPP) electrical energy output is provided to demonstrate further the suitability of the recommended approach for early fault detection in electric power systems.

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Publication Details

Journal
Communications in Statistics - Simulation and Computation
Published
2024-12-13
DOI
https://doi.org/10.1080/03610918.2024.2439461
Citations
2
Primary Topic
Advanced Statistical Process Monitoring
Type
article
Field-Weighted Citation Impact
0.92
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article

EWMA control charts to monitor energy output in combined cycle power plant: a new approach based on RBS profiling

Tahir Mahmood, Anam Iqbal
2 citations
Communications in Statistics - Simulation and Computation
Advanced Statistical Process Monitoring
0.92
article

EWMA control charts to monitor energy output in combined cycle power plant: a new approach based on RBS profiling

Tahir Mahmood, Anam Iqbal
article en
2 citations

Abstract

Electric energy production frequently uses combined cycle power plants (CCPPs) to handle peak loads. CCPPs must be continuously monitored for power performance to enhance the electrical output power. The electrical output datasets often show asymmetric behaviour; therefore, the Birnbaum-Saunders (BS) distribution is one of the potential models for fitting such datasets. In this study, novel exponentially weighted moving average (EWMA) control charts based on the Reparametrised Birnbaum-Saunders (RBS) regression model are developed. We perform a simulation study to evaluate the effectiveness of derived approaches in terms of run length characteristics. Moreover, a case study on the combined cycle power plant's (CCPP) electrical energy output is provided to demonstrate further the suitability of the recommended approach for early fault detection in electric power systems.

Communications in Statistics - Simulation and ComputationVol. 55(4)
UNSW Sydney (AU), Australian Defence Force Academy (AU), University of the West of Scotland (GB)
Affordable and clean energy
Openalex Percentile: Top 20%
Advanced Statistical Process Monitoring
0.92
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