Enhanced generalized likelihood ratio test for failure detection in photovoltaic systems

Mansouri, Majdi; Hajji, Mansour; Trabelsi, Mohamed; Al-Khazraji, Ayman; Harkat, Mohamed-Faouzi; Nounou, Hazem; Nounou, Mohamed

doi:10.1002/etep.2640

Cited by 11 publications

(2 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After obtaining P from equation ( 5), the binary hypotheses are identified as the normal mode H 0 and the fault mode H 1 . The statistics of P under binary hypothesis are written as [29]: (7) where µ = V T b.…”

Section: Generalized Likelihood Ratio Test and Problem Formulationmentioning

confidence: 99%

ALPF-GLRT based fault detection method for small faults applied to redundant IMUs

Li¹,

Chen²,

Wu³

et al. 2021

Meas. Sci. Technol.

View full text Add to dashboard Cite

Since small faults exhibit a very close magnitude to sensor noises, the probability of missing detection (PMD) in existing methods will increase sharply in the presence of small faults. To address such a problem, this paper proposes a novel fault detection method for small faults applied to redundant IMUs. First, this method introduces an adaptive low-pass filter (ALPF) into the general likelihood ratio test (GLRT) by filtering the parity residuals of the GLRT model, thereby reducing the disturbance of sensor noises on fault detection. Subsequently, since the introduction of ALPF leads to the changes of the parity residual statistics, the covariance of parity residual should be recalculated at the respective sample instant. Lastly, to theoretically prove the superiority of the proposed method for small faults, the minimum detection bias (MDB) is derived and calculated, thereby validating that the MDB of the proposed method is lower than that of the conventional GLRT method. As indicated from the simulation results, the PMD of the proposed method decreases significantly for small faults compared with the GLRT method and the Monte Carlo PMD of the proposed method is 0.1% under the fault with the magnitude of 1 sigma, which demonstrates the effectiveness of the proposed method.

show abstract

Section: Generalized Likelihood Ratio Test and Problem Formulationmentioning

confidence: 99%

ALPF-GLRT based fault detection method for small faults applied to redundant IMUs

Li¹,

Chen²,

Wu³

et al. 2021

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Potential attack risks: A solar farm is usually connected near to the power distribution loads to reduce system losses. This situation increases the intrusion and attack risks because the solar farm is much easier to be accessed by the public . Moreover, researches has been performed to investigate the cyber‐attack risk of solar PV system.…”

Section: Challenges and Future Research Directionsmentioning

confidence: 99%

Testing guidelines for connection of solar photovoltaic farm to distribution grid: The Malaysian experience

Yong

Ramachandaramurthy

Tan

et al. 2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Solar photovoltaic technology is intermittent in nature and employs power converters for grid‐interconnection, which can bring stability and power quality (PQ) issues to the power grid. Therefore, a set of testing guidelines is required to assure that solar plants comply with the grid and inverter requirements. As such, this article presents comprehensive testing guidelines for the interconnection of solar systems into Malaysian power grid, including inverter and PQ tests. The test points, conditions, parameters and acceptable limits for both tests are discussed in detail. This article also presents the results of a case study in which the testing guidelines were applied to examine the PQ of an actual grid‐connected solar photovoltaic plant in Malaysia and to assess the performance of the smart inverter used in the tested solar system. The testing outcomes, which were recorded by a PQ analyser, showed that the tested solar system was in compliance with all the requirements stipulated in the testing guidelines. The findings presented in this article will help relevant parties to understand these solar testing guidelines and serve to promote the wide deployment of solar technology towards a clean and sustainable future.

show abstract

Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems

Hajji

Harkat

Kouadri

et al. 2021

European Journal of Control

View full text Add to dashboard Cite

Enhanced generalized likelihood ratio test for failure detection in photovoltaic systems

Cited by 11 publications

References 53 publications

ALPF-GLRT based fault detection method for small faults applied to redundant IMUs

ALPF-GLRT based fault detection method for small faults applied to redundant IMUs

Testing guidelines for connection of solar photovoltaic farm to distribution grid: The Malaysian experience

Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems

Contact Info

Product

Resources

About