Algorithm for Determining the Parameters of a Two-Layer Soil Model

—The parameters of a two-layer soil can be determined by processing resistivity data obtained from resistivity measurements carried out on the soil of interest. The processing usually entails applying the resistivity data as inputs to an optimisation function. This paper proposes an algorithm which utilises the square error as an optimisation function. Resistivity data from previous works were applied to test the accuracy of the new algorithm developed and the result obtained conforms significantly to results from previous works

Critical Review of Different Methods for Siting and Sizing Distributed-generators

Due to several benefits attached to distributed generators such as reduction in line losses, improved voltage profile, reliable system etc., the study on how to optimally site and size distributed generators has been on the increase for more than two decades. This has propelled several researchers to explore various scientific and engineering powerful simulation tools, valid and reliable scientific methods like analytical, meta-heuristic and hybrid methods to optimally place and size distributed generator(s) for optimal benefits. This study gives a critical review of different methods used in siting and sizing distributed generators alongside their results, test systems and gaps in literature

Artificial Neural Network Based Load Flow Analysis for Power System Networks

Load flow analysis has become increasingly important as power system expansion now involves unbundling, liberalization, and restructuring networks, putting power system operators in a competitive electricity market. On the other hand, advancements in technology, computing, and software have led to new techniques for carrying out load flow analysis. In this paper, the load flow problem is approached using two techniques: the traditional load flow analysis using the Newton-Raphson method and a non-conventional method using an artificial neural network. This paper presents a load flow solution using the developed artificial neural network on the IEEE 14-bus system and the Nigerian 330kV 28-bus national grid. The results show that load flow analysis can be carried out using the developed artificial neural network with negligible errors between the actual values of voltage magnitudes and voltage phase angles and the neural network output, thus validating the proposed approach. Using the proposed approach, an R-value of 0.9884 and a mean square error of 1.6701x10−3 was obtained for the IEEE 14-bus system. For the Nigerian 330kV 28-bus national grid, an R-value of 0.99972 and a mean square error of 3.8624 × 10−3. MATLAB's neural network toolbox was used to design, develop, and train the artificial neural network used in this paper

Power system voltage collapse prediction using a new line stability index (NLSI-1): A case study of the 330-kV nigerian national grid

The cumulative number of historical and recent power system outages substantiates the fact that further studies are necessary for an improved solution to the issue of voltage instability on the grid and the subsequent system collapse. Voltage collapse is a serious reliability issue which inhibits the objective of running a reliable and secure power system network. In this study, a new line stability index (NLSI_1) for predicting voltage collapse is presented.  The new index considers a switching logic which is derived from the difference of voltage angle between the two load buses. The index is deployed for performance analysis using the 28-bus, 330-kV Nigeria National Grid (NNG).  The simulation implemented in MATLAB shows that the index gives the same results as Line stability index (Lmn) and Fast Voltage Stability Index (FVSI) indices. The base case and the contingency scenarios were considered during the simulation. The base case analysis using the NNG values of all the three indices FVSI, Lmn, and NLSI_1 for simulation generates a value less than one for the entire lines which implies that the NNG is stable in this mode. The values of the three indices are almost the same, which confirms the accuracy of the novel index developed. The analysis for the contingency case reveals that the load bus 16 (Gombe) which has the lowest, maximum permissible reactive load of 139.5MVAR is the weakest; also power line 16-19 is identified as the critical line. The result of the simulation confirms that the accuracy was improved by using NLSI_1

Determining the operational status of a three phase induction motor using a predictive data mining model

The operational performance of a three-phase induction motor is impaired by unbalanced voltage supply due to the generation of negative sequence currents, and negative sequence torque which increase motor losses and also trigger torque pulsations. In this study, data mining approach was applied in developing a predictive model using the historical, simulated operational data of a motor for classifying sample motor data under the appropriate type of voltage supply i.e. balanced (BV) and unbalance voltage supply (UB = 1% to 5%). A dataset containing the values of a three-phase induction motor’s performance parameter values was analysed using KNIME (Konstanz Information Miner) analytics platform. Three predictive models; the Naïve Bayes, Decision Tree and the Probabilistic Neural Network (PNN) Predictors were deployed for comparative analysis. The dataset was divided into two; 70% for model training and learning, and 30% for performance evaluation. The three predictors had accuracies of 98.649%, 100% and 98.649% respectively, and this confirms the suitability of data mining methods for predictive evaluation of a three-phase induction motor’s performance using machine learnin

Critical Review of Different Methods for Siting and Sizing Distributed-generators

Due to several benefits attached to distributed generators such as reduction in line losses, improved voltage profile, reliable system etc., the study on how to optimally site and size distributed generators has been on the increase for more than two decades. This has propelled several researchers to explore various scientific and engineering powerful simulation tools, valid and reliable scientific methods like analytical, meta-heuristic and hybrid methods to optimally place and size distributed generator(s) for optimal benefits. This study gives a critical review of different methods used in siting and sizing distributed generators alongside their results, test systems and gaps in literature

Energy Audit and Optimal Power Supply for a Commercial Building in Nigeria

Energy is indispensable to human existence and its need is on the increase daily due to technological advancement. In recent times, there is sporadic increase in the development of modern buildings, and these buildings require a cost effective and sustainable source of energy. Nigeria and some other African countries have major energy shortage issues due to the insufficient power generation and distribution facilities. This energy poverty creates a challenge for the growing population and as such, it is vital to ensure that the energy supplied to a building is duly optimized and delivered cost effectively. In this study, an energy audit of an eight floor multipurpose business complex was performed to determine the nature and type of loads within the building. Based on the load profile and energy consumption over a ten year period, three alternative energy sources (National grid, Diesel generator and PV system) were considered using various load sharing ratios. The result reveals that though PV solar system is a renewable energy source that reduces the production of greenhouse gases generated by burning diesel, but its continuous application in low middle income country like Nigeria may be challenged by the initial start-up capital which raises the cost of its unit energy

Dataset on the performance of a three phase induction motor under balanced and unbalanced supply voltage conditions

Three phase induction motors (TPIM) are extensively used for various applications in the industry for driving cranes, hoists, lifts, rolling mills, cooling fans, textile operations, and so forth. TPIM are designed to operate on balanced three phase power supply, but sometimes three phase supply line voltages to which the TPIM is connected may be unbalanced. In this data article, the operational data of a TPIM operating under changing voltage scenarios is profiled to determine the variations in the magnitude of the operational parameters of the motor. The magnitude of each of the line voltages was separately varied from the balanced state (0% unbalance) until 5% voltage unbalance condition was achieved, in line with the recommendations and guidelines of the National Electrical Manufactures Association. The motor parameters; both mechanical and electrical, at various slip values were collected in six sets for the 0%, 1%, 2%, 3%, 4%, and 5% unbalance voltage conditions. Frequency distributions and statistical analysis were carried out to identify the data pattern and data variation trends among the parameters in the dataset