Estimated billing system is the bane of grid electric power supply and development in Nigeria: An empirical analysis

The estimated billing system for electricity was introduced in Nigeria by the Nigerian Electricity Regulatory Commission (NERC) in 2012 for billing customers without meters or with faulty or inaccessible meters. But instead of following the guidelines and formula provided by NERC for the estimation, the electricity Distribution Companies (DisCos) resorted to billing these customers arbitrarily and frustrated efforts by NERC to ensure the proper metering of electricity consumers. This research evaluates the incentive, which makes the DisCos in Nigeria prefer the estimating billing system to a much more efficient smart prepaid metering system. To carry out the research, four Enugu Electricity Distribution Company (EEDC) customers were selected. The estimated bills of these customers, which they received before they got smart prepaid meters, were compared with their prepaid meter bills for an equal period. EEDC was found to be over-billing these customers under the estimated billing system by a yearly average per customer of 64,901.67 Nigerian Naira (170.79 USD).

Development of a horizontal three bladed windmill with vortex tubes

Researchers have been continuously searching for the most readily available means of producing electricity without any negative effect on the environment. Renewable source of energy like solar energy, hydro electric energy, biomass and wind energy has been considered as the alternative. Wind energy among others is rated the best renewable sources of energy because it’s level of environmental friendliness. In this paper, a horizontal windmill was designed, fabricated and its performance evaluated with two types of vortices and without a vortex. The component parts of the mills are towel, blades, shafts, base, tail vain and vortex. During the design of the windmill, consideration was given to the size, area of the blade and the blade material that produce maximum speed. The performance evaluation was carried out to compare the performance of the mill with the solid vortex, gap vortex and without vortex. The result of the evaluation reflects that the solid vortices have the highest wind speed irrespective of time of the day and with an optimum wind speed of 5.04 m/s. Also, the wind mill performed at a higher efficiency with the vortex compare to when it was running without vortex.

Voltage profile improvement and losses minimization for Hayin Rigasa radial network Kaduna using distributed generation

This research work has presented the application of distributed generation (DG) units in a simultaneous placement approach on IEEE 33 radial test systems for validation of the technique with further implementation on 56-Bus Hayin Rigasa feeder. The genetic algorithm (GA) is employed in obtaining the optimal sizes and load loss sensitivity index for locations of the DGs for entire active and reactive power loss reduction. The voltage profile index is computed for each bus of the networks to ascertain the weakest voltage bus of the network before and after DG and circuit breaker allocation. The simultaneous placement approach of the DGs is tested with the IEEE 33-bus test networks and Hayin Rigasa feeder network and the results obtained are confirmed by comparing with the results gotten from separate DGs allocation on the networks. For IEEE 33-bus system, the simultaneous allocation of DGs and of optimal sizes 750 kW, 800 kW and at locations of buses 2 and 6 respectively, lead to a 66.49 % and 68.64 % drop in active and reactive power loss and 3.02 % improvement in voltage profile. For the 56-bus Hayin Rigasa network in Kaduna distribution network, the simultaneous placement of DGs of sizes 1,470 kW and 1490 kW at locations of bus 16 and 23 respectively, lead to a 79.54 % and 73.98 % drop in active and reactive power loss and 15.94 % improvement in voltage profile. From results comparison, it is evident that the allocation of DGs using the combination GA and load loss sensitivity index, gives an improved performance in relations to power loss reduction and voltage profile improvements of networks when compared to without DGs.

Determination of best-fit isotherm model for the sorption of Lead (II) and Manganese (II) ions onto acid-activated shale using selected non-linear error functions

The focus of this research is to apply the selected error function equation to establish the equilibrium isotherm model that best describes the adsorption of Pb2+ and Mn2+ onto acid-activated shale. Data collected from the batch experiment were analyzed using selected isotherm models (Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Sips and Redlich-Peterson). To compute the isotherm parameters used in choosing the best-fit isotherm model, selected non-linear error functions, namely, error sum of the square, normalized standard deviation, hybrid error function, root mean square error and Marquardt’s percent standard deviation were employed. From the scanning electron microscope results, it was observed that the surface characteristics of the shale change considerably with calcination and acid treatment but the acid-treated shale shows better uneven porous surface characteristics. Error function computation shows that the Dubinin-Radushkevich isotherm model had the least sum of normalized error of 0.3623 for Pb2+ adsorption and 0.5465 for Mn2+ adsorption; hence, it was selected as the best isotherm model for explaining the sorption of Pb(II) and Mn(II) ions unto acid-activated shale.

CANFIS based DSTATCOM modelling for solving power quality problems

Devolution of the power grid into smart grid was necessitated by the proliferation of sensitive load profiles into the system, as well as incessant environmental challenges. These two factors culminated into aggravated disturbances that cause serious havoc along the entire system structure. The traditional proportional-plus-integral-plus-derivative (PID) solution offered by the distribution synchronous compensator (DSTATCOM) could no longer hold. As such, this paper proposes some soft-computing framework for redesigning DSTATCOM to automatically deal with power quality (PQ) problems in smart distribution grids. A recipe of artificial neural network (ANN) and coactive neuro-fuzzy inference systems (CANFIS) was fabricated for the objective. The system was modelled, simulated, and validated in MATLAB/Simulink SimPowerSystems environment. The performance of the CANFIS against adaptive neuro-fuzzy inference systems (ANFIS), ANN and fuzzy logic controllers’ algorithms proved superior in handling PQ issues like voltage sag, voltage swell and harmonics.

Prediction of tungsten insert gas welding process parameter using design of experiment and fuzzy logic

The focus of this study is to predict tungsten inert gas (TIG) welding process parameter such as heat input for stabilizing heat and removing post weld crack formation in mild steel weldment. The main input parameters examined are the welding current, voltage and speed whereas the measured (response) parameter is heat input. Statistical design of experiment was done by means of central composite design method using the range and levels of independent variables. The experiment was carried out 20 times (with 5 specimens per run) using 60 mm x 40 mm x 10 mm mild steel coupons. The plate samples were cut longitudinally with a Single-V joint preparation, with the edges beveled. The welding process utilizes 100% pure argon as a protecting gas to shield the weld specimen from external interaction. The interaction between the input and response variables was analyzed using a fuzzy logic system. The result showed that for a welding current, voltage and speed of 190 A, 21 V, and 2.0 mm/s respectively, the predicted heat input was 0.912 kJ/mm whereas for input parameters of (170 A, 25 V, and 2.0 mm/s) and (180 A, 23 V, 0.98 mm/s), the predicted heat inputs were 1.07 kJ/mm and 1.380 kJ/mm, respectively.

Investigation of the spatial variation of sediments heavy metals along the Nun River using kriging interpolation technique

This study employs geospatial statistical technique to assess the spatial distribution of heavy metals along the Nun River. Core sediment samples were collected from relatively undisturbed areas (twenty-five different stations) using Uwitec Triple sediment cutter. The rectangular coordinates of the sediment sample location were determined with the aid of Germin handheld GPS receiver. The concentrations of cadmium, lead chromium and zinc present in the sediments was determined with the aid of an atomic absorption spectrophotometer. For geospatial analysis, five semi-variogram models (stable, circular, spherical, exponential and K-Bessel) were fitted for each of the four critical parameters (heavy metals). In addition, four goodness-of-fit statistics (mean square error, root mean square error, root mean square standardized error and average standard error) were utilized to decide the most suitable model used to develop the final prediction map for each parameter. From the results obtained, it was observed that; regions with red color codes signify higher concentrations of cadmium, lead, chromium and zinc. Further assessment of the results showed that Otuan, Obeleli, Angiama, Odobio, Kasama, Akedda and Akele experienced high concentration of cadmium while Tombia, Ewoi, Abilabio, Agudama and Yenikpa experienced high concentration of lead.

Statistical prediction of the drying behavior of blanched ginger rhizomes

ARS-680 environmental chamber was employed in this study to determine the drying behavior of sliced ginger rhizomes. Blanched and unblanched treated ginger rhizomes were considered at drying temperature of 40 °C for a period of 2 – 24 h. Linear and non-linear regression analyses were employed to establish the correlation that exits between the drying time and the moisture ratio. Correlation analysis, root mean square error (RMSE) and standard error of estimate (SEE) analysis were chosen in selecting the best thin layer drying models. Higher values of determination coefficient (R2) show goodness of fit and lower values of SEE implies better correlation; and RMSE values were also utilized in determining the goodness of fit. The drying data of the variously treated ginger samples were fitted into the twelve thin layer drying models and the data obtained were fitted by multiple non-linear regression technique. Blanched treated sample exhibited a better drying behavior losing about 82.87 % moisture content compared with unbleached sample that lost about 62.03 % of moisture content. Two-term exponential drying model proved to be the most suitable model for predicting the drying behavior of ginger rhizome. The model exhibited high R2 values of 0.9349-0.9792 (which are close to unity) for both blanched and unbleached samples. Also, it recorded relatively low values of RMSE and SEE (3.6865 - 2.0896 and 3.6564-2.7486 respectively) for both treatments.

Analysis of critical imposed load of plate using variational calculus

This work studied the critical load analysis of rectangular plates, carrying uniformly distributed loads utilizing direct variational energy calculus. The aim of this study is to establish the techniques for calculating the critical lateral imposed loads of the plate before deflection attains the specified maximum threshold, qiw as well as its corresponding critical lateral imposed load before the plate reaches an elastic yield point. The formulated potential energy by the static elastic theory of the plate was minimized to get the shear deformation and coefficient of deflection. The plates under consideration are clamped at the first and second edges, free of support at the third edge and simply supported at the fourth edge (CCFS). From the numerical analysis obtained, it is found that the critical lateral imposed loads (qiw and qip) increase as the thickness (t) of plate increases, and decrease as the length to width ratio increases. This suggests that as the thickness increases, the allowable deflection improves the safety of the plate, whereas an increase in the span (length) of the plate increases the failure tendency of the plate structure.

Enhancement of voltage stability in an interconnected network using unified power flow controller

In this paper, the optimal placement of Unified Power Flow Controllers (UPFC) in a large-scale transmission network in order to improve the loadability margin was considered. In other to achieve this aim, the Line Stability Factor (LQP) as a technique for the optimal location of UPFC in the IEEE 14-bus network and 56-bus Nigerian national grid was adopted. The power injection model for the UPFC was employed to secure improvements in the loading margin of the IEEE 14-bus network and 56-bus Nigerian national grid system. Continuation power flow was used to assess the effect of UPFC on the loadability margin. Steady-state simulations using Power System Analysis Toolbox (PSAT) on MATLAB was applied to determine the effectiveness of placing UPFC between bus 13 and bus 14 in the IEEE 14-bus network and between bus 44 (Ikot-Ekpene) and bus 56 (Odukpani) in the 56-bus Nigerian national grid system. The results showed that the loadability margin increased by 8.52 % after UPFC was optimally placed in the IEEE 14-bus network and increased by 195.5 % after UPFC was optimally placed in the 56-bus Nigerian national grid system. Thus, these enhance the voltage stability of both network and utilizing the network efficiently.