Theses and dissertations (Engineering and Built Environment)
Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/10
Browse
3 results
Search Results
Item Power loss minimization and voltage profile improvement in transmission networks using a network modification algorithm(2023-05) Ntombela, Mlungisi; Musasa, Kabeya; Leoaneka, Moketjema ClarenceA number of algorithms that aim to reduce power system losses and improve voltage profiles by optimizing distributed generator (DG) location and size have already been proposed, but they are still subject to several limitations. Hence, new algorithms can be developed or existing ones can be improved so that this important issue can be addressed much more appropriately and effectively. In their formulations, the majority of algorithms focused only on real power loss minimization. Power systems operate with reactive power controller installed at various locations, which are essential to their operation. Therefore, the effect of reactive power control must be taken into consideration when optimizing DG allocation for voltage profile improvement. State-of-the-art optimization algorithms can be used to improve the effectiveness of the existing one in taking into account the effect of reactive power control. This study proposed a modification methodology based on a hybrid optimization algorithm, consisting of a combination of the genetic algorithm (GA) and the improved particle swam optimization (IPSO) algorithm m for minimizing active power loss and maintaining the voltage magnitude at about 1 p.u. The buses at which DGs should be injected were identified based on optimal real power loss and reactive power limit. When applying the proposed optimization algorithm for DGs allocation in power systems, the search space or number of iterations was reduced, increasing its convergence rate. The proposed modification methodology was tested in an IEEE-30 bus electrical network system with DGs allocations and the simulations were conducted using MATLAB software. The hybrid GA and IPSO (HGAIPSO) method has less iterations and is more effective at solving optimization issues than other optimization algorithms like GA, PSO, and IPSO. An IEEE-30 bus network system with DGs allocations was used to evaluate the effectiveness of the proposed HGAIPSO, and the test results were compared to those from alternative techniques (i.e. GA, PSO and IPSO). The outcomes of the simulation demonstrate that the suggested HGAIPSO can be an effective and promising optimization technique for issues with transmission network modification. IEEE-30 bus test system with DGs included at various locations, Type 1, Type 2, and Type 3 DGs allocation, respectively, showed decreases in overall real power loss of 40.7040%, 36.2403%, and 42.9406%. For the IEEE-30 bus, the highest bus voltage profiles are up to 1.01pu.Item Energy-efficient PLIA-RWA algorithms for transparent optical networks(2017) Mutsvangwa, Andrew; Nleya, BakheThe tremendous growth in the volume of telecommunication traffic has undoubtedly triggered an unprecedented information revolution. The emergence of high-speed and bandwidth-hungry applications and services such as high-definition television (HDTV), the internet and online interactive media has forced the telecommunication industry to come up with ingenious and innovative ideas to match the challenges. With the coming of age of purposeful advances in Wavelength Division Multiplexing (WDM) technology, it is inherently practicany possible to deploy ultra-high speed all-optical networks to meet the ever-increasing demand for modern telecommunication services. All-optical networks are capable of transmitting data signals entirely in the optical domain from source to destination, and thus eliminate the incorporation of the often bulky and high-energy consuming optical to-electrical-to-optical (OEO) converters at intermediate nodes. Predictably, all-optical networks consume appreciably low energy as compared to their opaque and translucent counterparts. This low energy consumption results in lower carbon footprint of these networks, and thus a significant reduction in the greenhouse gases (GHGs) emission. In addition, transparent optical networks bring along other additional and favourable rewards such as high bit-rates and overall protocol transparency. Bearing in mind the aforementioned benefits of transparent optical networks, it is vital to point out that there are significant setbacks that accompany these otherwise glamourous rewards. Since OEO conversions are eliminated at intermediate nodes in all-optical networks, the quality of the transmitted signal from source to destination may be severely degraded mainly due to the cumulative effect of physical-layer impairments induced by the passage through the optical fibres and associated network components. It is therefore essential to come up with routing schemes that effectively take into consideration the signal degrading effects of physical -layer impairments so as to safeguard the integrity and health of transmitted signals, and eventually lower blocking probabilities. Furthermore, innovative approaches need to be put in place so as to strike a delicate balance between reduced energy consumption in transparent networks and the quality of transmitted signals. In addition, the incorporation of renewable energy sources in the powering of network devices appears to gain prominence in the design and operation of the next-generation optical networks. The work presented in this dissertation broadly focuses on physical-layer impairment aware routing and wavelength assignment algorithms (PLIA-RWA) that attempt to: (i) achieve a sufficiently high quality of transmission by lowering the blocking probability, and (ii) reduce the energy consumption in the optical networks. Our key contributions of this study may be summarized as follows: Design and development of a Q-factor estimation tool. Formulation, evaluation and validation of a QoT-based analytical model that computes blocking probabilities. Proposal and development of IA-RWA algorithms and comparison with established ones. Design and development of energy-efficient RWA schemes for dynamic optical networks.Item Design and implementation of an intelligent vision and sorting system(2009) Li, Zhi; Govender, PoobalanThis research focuses on the design and implementation of an intelligent machine vision and sorting system that can be used to sort objects in an industrial environment. Machine vision systems used for sorting are either geometry driven or are based on the textural components of an object’s image. The vision system proposed in this research is based on the textural analysis of pixel content and uses an artificial neural network to perform the recognition task. The neural network has been chosen over other methods such as fuzzy logic and support vector machines because of its relative simplicity. A Bluetooth communication link facilitates the communication between the main computer housing the intelligent recognition system and the remote robot control computer located in a plant environment. Digital images of the workpiece are first compressed before the feature vectors are extracted using principal component analysis. The compressed data containing the feature vectors is transmitted via the Bluetooth channel to the remote control computer for recognition by the neural network. The network performs the recognition function and transmits a control signal to the robot control computer which guides the robot arm to place the object in an allocated position. The performance of the proposed intelligent vision and sorting system is tested under different conditions and the most attractive aspect of the design is its simplicity. The ability of the system to remain relatively immune to noise, its capacity to generalize and its fault tolerance when faced with missing data made the neural network an attractive option over fuzzy logic and support vector machines.