The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems

The artificial neural network (ANN) has recently been applied in many areas, such as medical, biology, financial, economy, engineering and so on. It is known as an excellent classifier of nonlinear input and output numerical data. Improving training efficiency of ANN based algorithm is an active area of research and numerous papers have been reviewed in the literature. The performance of Multi-layer Perceptron (MLP) trained with back-propagation artificial neural network (BP-ANN) method is highly influenced by the size of the data-sets and the data-preprocessing techniques used. This work analyzes the advantages of using pre-processing datasets using different techniques in order to improve the ANN convergence. Specifically Min-Max, Z-Score and Decimal Scaling Normalization preprocessing techniques were evaluated. The simulation results showed that the computational efficiency of ANN training process is highly enhanced when coupled with different preprocessing techniques

Nonlinear finite element analysis of reinforced concrete beams strengthened with textile fine grained mortar

Nowadays, there was an increasing need of repairing and upgrading the reinforced concrete (RC) structure due to the deterioration of the structure. The fibre reinforced polymer (FRP) was commonly used for structural retrofitting purposes. However, owing to the debonding of the FRP from the concrete substrate and high cost of epoxy, it was gradually replaced with textile fine grained mortar (TFGM) nowadays. The TFGM system has been widely used in the construction field nowadays to repair the structure. Our study focus on the strain performances of the concrete surface, steel reinforcement and the textile itself. There were many proven experimental results showing that the TFGM was more effective than the other strengthening method such as FRP plate method. The experimental work done by previous researcher on investigation of strain performances of the concrete surface, steel reinforcement and the textile itself which consists of eleven (11) RC beams with dimension 150 x 200 x 2500 mm. The RC beams were strengthened with FGM and TFGM with 4 layers. The investigation continued with the finite element (FE) strain performance analysis with using Advanced Tool for Engineering Nonlinear Analysis (ATENA) software. The strain of the concrete surface, steel reinforcement and the textile were measured at a mid-point of RC beam. Then, the results of the finite element analysis software ATENA compared against the experimental results. The strain performances of the concrete and steel reinforcement improved noticeably when the number of layers of textile reinforcement used increased

Mechanical and shrinkage properties of hybrid steel and polypropylene fibre reinforced concrete composite

An experimental study had been carried out to investigate the mechanical properties, expansion and shrinkage of fibre reinforced concrete composite (FRC). However, instead of using single type fibre of either steel (SF) or polypropylene (PPF), this study also combined the two types in one mix.The mechanical properties investigated in this study include compressive strength, splitting tensile strength and flexural strength. Three different FRC mix proportions and one normal concrete (control) were casted which includes (a) 75% SF, (b) 75% SF + 25% PPF, (c) 25% PPF, and (d) 0% fibre for control (PC). Meanwhile, the volume fraction, Vf for the FRC was fixed at 1.5% and the concrete strength was designed to achieve grade C60 at 28 days. The results show that the use of fibres in concrete decreased the workability of concrete. In addition, concrete mix with both SF and PPF produced the highest splitting tensile and flexural strengths by an increase of 75.9% and 86.5%, respectively as compared with the control. Furthermore, expansion and shrinkage of FRC was found to be less than the control. It can be concluded that the combined SF and PPF in concrete gives the most appropriate combination as regards to the highest flexural and splitting tensile strengths, and also reduced the shrinkage strain

Improvement of active distribution systems with high penetration capacities of shunt reactive compensators and distributed generators using Bald Eagle Search

This work proposes an intelligent allocation of distributed generation (DG) units and shunt reactive compensators (SRC) with high penetration capacities into distribution systems for power loss mitigation using the Bald Eagle Search (BES) optimization algorithm. The intelligent allocation causes a reduction in voltage variations and enhances the voltage stability of the systems. The SRC units include shunt capacitors (SC), Static Var Compensators (SVC), and Distribution Static Compensators (DSTATCOM), which are determined according to their capacities. The optimization study includes the 33-bus and the 118-bus distribution systems as medium to large systems. Performance parameters, including the reactive power loss, Total Voltage Deviation (TVD), and Stability Index (SI), besides the power loss, are recorded for each optimization case study. When the BES algorithm optimizes 1, 2, and 3 DG units operating at optimal power factor (OPF) into the 33-bus systems, percentage reductions of power loss reach 67.84%, 86.49%, and 94.44%, respectively. Reductions of 28.26%, 34.47%, 35.24%, and 35.44% are achieved in power loss while optimizing 1, 3, 5, and 7 SRC units. With a combination of DG/SRC units, the power loss reductions achieve 72.30%, 93.89%, and 97.49%, optimizing 1, 3, and 5 pairs of them. Similar reductions are achieved for the rest of the performance parameters. With high penetration of compensators into the 118-bus system, the percentage reductions of power loss are 29.14%, 73.27%, 83.72%, 90.14%, and 93.41% for optimal allocations of 1, 3, 5, 7, and 9 DG units operating at OPF. The reduction reaches 11.15%, 39.08% with 1 and 21 devices when optimizing the SRC. When DG SRC units are optimized together, power loss turns out to be 32.83%, 73.31%, 83.32%, 88.52%, and 91.29% with 1, 3, 5, 7, and 9 pairs of them. The approach leads to an enhanced voltage profile near an acceptable range of bus voltages, reduces the voltage fluctuation substantially, and enhances the system stability. The study also ensures the BES algorithm’s capability to solve these nonlinear optimization problems with high decision-variable numbers

Optimal allocation of FACTS devices in power networks using imperialist competitive algorithm (ICA)

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDue to the high energy consumption demand and restrictions in the installation of new transmission lines, using Flexible AC Transmission System (FACTS) devices is inevitable. In power system analysis, transferring high-quality power is essential. In fact, one of the important factors that has a special role in terms of efficiency and operation is maximum power transfer capability. FACTS devices are used for controlling the voltage, stability, power flow and security of transmission lines. However, it is necessary to find the optimal location for these devices in power networks. Many optimization techniques have been deployed to find the optimal location for FACTS devices in power networks. There are several varieties of FACTS devices with different characteristics that are used for different purposes. The imperialist competitive algorithm (ICA) is a recently developed optimization technique that is used widely in power systems. This study presents an approach to find the optimal location and size of FACTS devices in power networks using the imperialist competitive algorithm technique. This technique is based on human social evolution. ICA technique is a new heuristic algorithm for global optimization searches that is based on the concept of imperialistic competition. This algorithm is used for mathematical issues; it can be categorized on the same level as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) techniques. Also, in this study, the enhancement of voltage profile, stability and loss reduction and increasing of load-ability were investigated and carried out. In this case, to apply FACTS devices in power networks, the MATLAB program was used. Indeed, in this program all power network parameters were defined and analysed. IEEE 30-bus and IEEE 68-bus with 16 machine systems are used as a case study. All the simulation results, including voltage profile improvement and convergence characteristics, have been illustrated. The results show the advantages of the imperialist competitive algorithm technique over the conventional approaches

The role of distributed generation on the performance of electrical radial distribution network

Purpose: This article provides available information on the role of distributed generation (DG) in the performance of a power distribution network.Design/methodology/approach: The study reviewed articles about available methods for reducing technical losses in electrical distribution networks. The second step involved studying various researchers' views on renewable energy in some developing countries for introducing DG into a distribution network. The influence of DG on the economic performance of a distribution network. Finally, the study scouted for available information on the implementation of a demand response (DR) program on the performance of a distribution network in the presence of DG.Findings: Available information reveals that the reliability of DG for reducing the technical losses in a distribution network is higher than relying on alternating current controllers. There are indications of renewable energies in developing countries for introducing DG into a distribution network. According to the articles reviewed, the approach for the optimal location of DG did not include the combination of the voltage stability index and power loss reduction index. It is also worth considering using the power system analysis toolbox (PSAT) for DG sitting. The economic influence of DG on a distribution network's performance has not been evaluated based on the technical loss, generation cost, emission cost and reliability. It is also worth considering the benefits of demand response programs in the presence of DG.Research limitation: The review concentrated mainly on DG's influence in reducing technical loss. Articles relating to the effect of DG on other distribution network technical issues such as voltage stability, harmonics etc. also require attentionPractical implications: Distribution network performance is essential for the operation of electrical gadgets. Therefore, improved distribution network performance will result in the economic development of a country.Originality/Value: This paper provides the platform that stimulates interest in using DG to improve the distribution network performance

Voltage Stability Enhancement Based on Optimal Allocation of Shunt Compensation Devices Using Lightning attachment procedure optimization

This paper proposes a combined approach to determine the optimal allocation of different shunt compensation devices (shunt capacitor, static var compensator, and static synchronous compensator) in power systems. The developed approach is a combination between Lightning Attachment Procedure Optimization (LAPO) and loss sensitivity indices (LSIs). Different objective functions such as enhancement of voltage stability index, improvement of voltage profile and minimization of total power losses are considered. Two loss sensitivity indices (LSIs) are developed to reduce the search space in all buses and the total computation time. The developed algorithm is validated using standard IEEE 14-bus and IEEE 30-bus test systems. The developed algorithm successes to achieve the objective functions with the better performance compared with other wellknown optimization techniques such as Teaching learning-based optimization (TLBO), genetic algorithm (GA) and particle swarm optimization (PSO)

Optimal SVC allocation via symbiotic organisms search for voltage security improvement

It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations

A Genetic Algorithm Approach to Optimal Sizing and Placement of Distributed Generation on Nigerian Radial Feeders

Mitigating power loss and voltage profile problems on radial distribution networks has been a major challenge to distribution system operators. While deployment of distributed generation, as compensators, has made a suitable solution option, optimum placement and sizing of the compensators has been a concern and it has thus been receiving great attention. Meta-heuristic algorithms have been found efficacious in this respect, yet the use of the algorithms in addressing problems of radial feeders is still comparatively low in Nigeria where analytical and numerical programming methods are common. Hence; the use of genetic algorithm to site and size distributed generator for real-time power loss reduction and voltage profile improvement on the Nigerian secondary distribution networks is presented. Backward-forward sweep load flow analysis, together with loss sensitivity factor, is deployed to identify the buses suitable for the installation of the distributed generation, while the algorithm is employed in estimating the optimum size. This approach is tested on the standard IEEE 15-bus system and validated using a Nigerian 11 kV feeder. The result obtained on the IEEE test system shows 183 kW loss using the compensator, as compared to 436 kW loss without the compensator; while on the Nigerian network the loss with the compensator was 4.99 kW, in comparison with no-compensation loss of 10.47kW. By the approach of this study, real power loss on the Nigerian feeder decreased by 52.3% together with energy cost reduction from N658,789.12 to N314,227.38. Likewise the minimum bus voltage magnitude and the voltage stability index of the network are improved to acceptable limits. This approach is therefore recommended as capable of strengthening the performance of the Nigerian radial distribution system