There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Distribution System Modeling and Analysis

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Vector Control And Dynamics Of Ac Drives

Voltage stability assessment and enhancement of power grid with increasing wind energy penetration

Impact of integrating large-scale DFIG-based wind energy conversion system on the voltage stability of weak national grids: A case study of the Nigerian power grid

Distribution system is very essential to load centre or service mains. This is because it is the final section of electric power system (EPS) to supply the consumers. Once this section is compromised, low voltage consumers will be denied of a reliable supply of electricity. One way to make supply to low voltage consumers reliable is by bringing generation close to them through distributed generators. However, location of distributed generator is very important with respect to the entire EPS security. In this study, power network structural topology (PNST) is proposed to optimally locate distributed generator within distribution system which results in minimal loss as well as maintaining voltage profile within constraint limits. 5- bus IEEE test system was used as case study to show the feasibility of the proposed method. Results obtained for both test systems were validated through the results from power world simulation tool.

/pdf/deployment-of-power-network-structural-topology-to-optimally-4bplg9l7zw.pdf

Deployment of Power Network Structural Topology to Optimally Position distributed Generator within Distribution System

This paper presents an Artificial Neural Network (ANN) model to determine the estimated monthly payment for electricity consumed by residential consumers. The network was trained, validated and tested with five consumer input attributes which comprises type of apartment, number of occupants, average daily power supply, scored categories of electrical appliances and scored behavioural energy usage pattern. The corresponding output data comprises of the average monthly payment obtained from metered residential customers. A combined R-value of 0.99923 was obtained for the trained network. This indicates a very accurate ANN training. The developed network was then utilised to compute the estimated monthly amount to be paid by unmetered residential consumers. Comparisons were also made with the rather unclear and controversial estimated amount utilised by the electricity distribution companies in Nigeria. This work therefore provides a better method for estimated billing in the absence of prepaid meter, which has been of inadequate supply to electricity users in developing countries like Nigeria.

Development of an ANN-Based Estimated Electricity Billing System

This paper presents an Artificial Neural Network (ANN) model to predict the excitation capacitance value necessary to sustain the generated voltage of a wind-driven self-excited reluctance generator (WDSERG) within preferred limits. The network was trained, validated and tested with input data which comprises load impedances, power factor and wind speed values and a corresponding output data consisting of the excitation capacitance for each input condition. A mean square error value of less than 0.11 and an R-value of more than 0.999 were obtained for the network. These indicate a very accurate ANN training. The network was then utilized in the complete model of WDSERG under diverse input states of wind speed and load variation. The predicted capacitance value obtained from the network provides the required excitation to keep the generated phase voltage at a preferred constant level of 220±5 V under each input condition. The results depict the effectiveness of the neural network application to provide excitation capacitance control for the WDSERG output voltage when varying wind speed and load profile are considered. The method proposed in this work can provide a basis for the design of a variable capacitor to keep the generated voltage of wind-driven SERG within desired limits despite wind speed and load variation.

Artificial Neural Network-Based Capacitance Prediction Model for Optimal Voltage Control of Stand-alone Wind-Driven Self-Excited Reluctance Generator

The phasor Measurement Unit is a modern tracking tool mounted on a network to track
and manage power systems. PMU is accurate and time-synchronized device that gives
voltage phasor measurements in nodes and current phasor measurements connected to
those nodes where the PMU is installed. This study introduces the Genetic Algorithm for
optimization of allocation of PMUs to enable maximum observation of the power network.
The optimal PMU placement (OPP) problem is developed to minimize the quantity of PMU
to be placed. The set and optimized model can efficiently position PMU in any network,
considering the regular operation and zero injection (ZIN). Thus, the allocation algorithm
implemented on IEEE 14-bus systems, the result was compared to that of existing works
which achieved the same system of redundancy index. As a further study, the proposed
approach is applied to the Nigerian 330kV new 52-bus systems, under operational
arrangements for maximum observability of the network system. The technique formulated
to handle normal operation and zero injection node succeeded in producing comparable
results with other available techniques.

/pdf/optimal-pmu-placement-using-genetic-algorithm-for-330kv-52-invat2t4so.pdf

Optimal PMU Placement Using Genetic Algorithm for 330kV 52-Bus Nigerian Network

Managing people and keeping adequate record of the attendance for most of the tertiary institutions are difficult task. Moreover, the manual taking of attendance adds to the difficulty of this task because it is strenuous, time intensive and can easily be falsified. Meanwhile, With the advent of new technology, a new world of authentication and security has been created via biometrics. This work aims at improving Covenant Universities paper-based attendance by using biometrics, specifically fingerprint technology. It is a web application that works with a fingerprint reader from which the features of the student’s fingerprint are extracted during enrolment. This is also needed during the authentication phase which occurs during the roll call attendance in the halls of residence. It is implemented using PHP and MySQL.

/pdf/web-based-fingerprint-roll-call-attendance-management-system-1bsp05riuy.pdf

Tobilola Emmanuel Somefun

Papers

Deployment of Power Network Structural Topology to Optimally Position distributed Generator within Distribution System

Development of an ANN-Based Estimated Electricity Billing System

Artificial Neural Network-Based Capacitance Prediction Model for Optimal Voltage Control of Stand-alone Wind-Driven Self-Excited Reluctance Generator

Optimal PMU Placement Using Genetic Algorithm for 330kV 52-Bus Nigerian Network

Web based fingerprint roll call attendance management system