Engineering

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Browsing Engineering by Author "Abdullateef, A. I."

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    Electricity Theft Prediction on Low Voltage Distribution System Using Autoregressive
    (International Journal of Research in Engineering and Technology, 2012) Abdullateef, A. I.; Salami, Momoh-Jimoh E.; Musse, M. A.; Aibinu, A. M.; Onasanya, Onasanya
    Electricity consumers tend to avoid the payment of electricity dues through various methods such as tampering with energy meter and illegal tapping via direct connection to the distribution feeder. This has led to huge revenue losses by the electricity supplying corporation and the related government or private agencies. A new approach of detecting electricity theft on low voltage distribution systems, either single or three phase, based on the advanced signal processing using linear prediction is presented in this paper. Consumer data were analyzed using Autoregressive (AR) model in order to predict the quantity of power consumed within the specified interval and consequently, compare the result obtained with the actual data recorded against the consumer under study. Thus the model developed was used to predict power consumption at 30minutes interval ahead, thereby facilitating the detection of electricity theft if there is a wide variation between the actual and the predicted data.
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    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm
    (IOP Publishing, 2013) Salami, Momoh-JImoh E.; Tijani, I. B.; Abdullateef, A. I.; Aibinu, M. A.
    A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. The DE at the upper level is formulated as combinatorial optimization to search for the network architecture while the associated network weights that minimize the prediction error is provided by the GA at the lower level. The performance of the algorithm is evaluated on identification of a laboratory rotary motion system. The system identification results show the effectiveness of the proposed algorithm for nonparametric model development.
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    New consumer load prototype for electricity theft monitoring
    (IOP Publishing, 2013) Abdullateef, A. I.; Salami, Momoh-Jimoh E.; Musse, M. A.; Onasanya, M. A.; Alebiosu, M. I.
    Illegal connection which is direct connection to the distribution feeder and tampering of energy meter has been identified as a major process through which nefarious consumers steal electricity on low voltage distribution system. This has contributed enormously to the revenue losses incurred by the power and energy providers. A Consumer Load Prototype (CLP) is constructed and proposed in this study in order to understand the best possible pattern through which the stealing process is effected in real life power consumption. The construction of consumer load prototype will facilitate real time simulation and data collection for the monitoring and detection of electricity theft on low voltage distribution system. The prototype involves electrical design and construction of consumer loads with application of various standard regulations from Institution of Engineering and Technology (IET), formerly known as Institution of Electrical Engineers (IEE). LABVIEW platform was used for data acquisition and the data shows a good representation of the connected loads. The prototype will assist researchers and power utilities, currently facing challenges in getting real time data for the study and monitoring of electricity theft. The simulation of electricity theft in real time is one of the contributions of this prototype. Similarly, the power and energy community including students will appreciate the practical approach which the prototype provides for real time information rather than software simulation which has hitherto been used in the study of electricity theft.