Browsing by Author "Mustafa, M.W."

Now showing 1 - 4 of 4
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    Electricity theft detection framework based on universal prediction algorithm
    (Indonesian Journal of Electrical Engineering and Computer Science, 2019-08) Otuoze, Abdulrahaman; Mustafa, M.W.; Mohammed, OO; Saeed, M.S.; Salisu, S; Surajudeen-Bakinde, N.T.
    Electricity theft has caused huge losses over the globe and the trend of its perpetuation constantly evolve even as smart technologies such as smart meters are being deployed. Although the smart meters have come under some attacks, they provide sufficient data which can be analysed by an intelligent strategy for effective monitoring and detection of compromised situations. So many techniques have been employed but satisfactory result is yet to be obtained for a real-time detection of this electrical fraud. This work suggests a framework based on Universal Anomaly Detection (UAD) utilizing Lempel-Ziv universal compression algorithm, aimed at achieving a real-time detection in a smart grid environment. A number of the network parameters can be monitored to detect anomalies, but this framework monitors the energy consumption data, rate of change of the energy consumption data, its date stamp and time signatures. To classify the data based on normal and abnormal behaviour, Lempel-Ziv algorithm is used to assign probability of occurrence to the compressed data of the monitored parameters. This framework can learn normal behaviours of smart meter data and give alerts during any detected anomaly based on deviation from this probability. A forced aggressivemeasure is also suggested in the framework as means of applying fines to fraudulent customers.
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    Electricity theft detection framework based on universal prediction algorithm
    (Indonesian Journal of Electrical Engineering and Computer Science, 2019-08) Otuoze, Abdulrahaman; Mustafa, M.W.; Sofimieari, I.E.; Dobi, A.M; Sule, A.H; Abioye, A.E.; Saeed, M.S.
    Electricity theft has caused huge losses over the globe and the trend of its perpetuation constantly evolve even as smart technologies such as smart meters are being deployed. Although the smart meters have come under some attacks, they provide sufficient data which can be analysed by an intelligent strategy for effective monitoring and detection of compromised situations. So many techniques have been employed but satisfactory result is yet to be obtained for a real-time detection of this electrical fraud. This work suggests a framework based on Universal Anomaly Detection (UAD) utilizing Lempel-Ziv universal compression algorithm, aimed at achieving a real-time detection in a smart grid environment. A number of the network parameters can be monitored to detect anomalies, but this framework monitors the energy consumption data, rate of change of the energy consumption data, its date stamp and time signatures. To classify the data based on normal and abnormal behaviour, Lempel-Ziv algorithm is used to assign probability of occurrence to the compressed data of the monitored parameters. This framework can learn normal behaviours of smart meter data and give alerts during any detected anomaly based on deviation from this probability. A forced aggressivemeasure is also suggested in the framework as means of applying fines to fraudulent customers.
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    A review of probabilistic approaches for available transfer capability calculation
    (Arid Zone Journal of Engineering, Technology and Environment, 2019-03-04) Otuoze, Abdulrahaman; Mohammed, OO; Mustafa, M.W.; Salisu, S; Abdulrahman, A.Y.
    Several deterministic approaches have been proposed in literature for available transfer capability (ATC) computation. However, the gradual shift in power generation sources from fossil fuels to renewable energy sources has a remarkable influence on the ATC evaluation. The deterministic approaches do not incorporate the uncertainties of the renewable energy sources efficiently, therefore, various probabilistic techniques have been proposed in literature. This article presents a review of the various probabilistic methods for ATC computation. It provides the background, techniques and the features of ATC. Several contributions made by researchers, using probabilistic techniques for ATC computation, have been highlighted in this paper. This review has shown that there is a need for improvement in the existing approaches in order to evaluate ATC accurately. The improvement includes the development of a robust technique incorporating the system uncertainties and the uncertainties due to the renewable energy system as well as complete system dynamics in ATC computation. In addition, evaluation of ATC incorporating the transfer capability margins (TRM and CBM) is necessary to avoid over-/under-estimation of ATC value. This review will serve as a guide for the entrants in this research area.
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    Smart grids security challenges: Classification by sources of threats
    (2018-12-01) Otuoze, Abdulrahaman; Mustafa, M.W.; Larik, Raja
    Smart grids (SGs) deployments have made power systems operation more efficient by the application of distributed computing schemes in grids’ interoperation. However, these schemes have triggered various security issues which are growing to be of major concerns. Physical attacks, cyber-attacks or natural disasters are major notable form of threats to SGs deployment which could lead to infrastructural failure, blackouts, energy theft, customer privacy breach, endangered safety of operating personnel, etc. Hence, the need to critically examine the security issues aimed at preventing possible threats or failures. In this review, various security challenges and threats are discussed with respect to their possible sources of occurrence. These threats are then classified and a framework for achieving more secured SGs is suggested.