Faculty of Engineering and Built Environment
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Item The prospect of floating photovoltaic in clean energy provision and net-zero-emissions(Springer Science and Business Media LLC, 2024) Ebhota, Williams S.; Tabakov, Pavel Y.This study emphasizes the critical role of renewable energy in addressing climate change challenges, particularly in reducing greenhouse gas emissions. It highlights the central importance of solar photovoltaic systems. While recognizing South Africa’s progress in renewable energy deployment, the study notes that substantial efforts are still needed to meet the country’s renewable energy targets. The study’s primary aim is to enhance the understanding and deployment of solar photovoltaic systems by critically examining the photovoltaic potential and performance of different sites. To achieve this, two scenarios—land photovoltaic and floating photovoltaic systems—were considered, focusing on hypothetical 10 MWp-installed capacity systems. The results indicate that the 10-MWp land photovoltaic system has a global tilted irradiance of 2184.7 kWh/m2, an annual total output of 18 GWh, and an average yearly performance ratio of 81%. The economic parameters for the land photovoltaic system include a capital expenditure of $9.0 million, an operational expenditure of $157,500 annually, and a levelised cost of energy of $0.04089/kWh. In contrast, the 10-MWp floating photovoltaic system reports a Global Tilted Irradiance of 1797 kWh/m2, an annual total output of 16 GWh, and a performance ratio of 76%. The economic parameters for the floating photovoltaic system include a capital expenditure of $10.6 million, an operational expenditure of $176,250 annually, and a levelised cost of energy of $0.04936/kWh. Both scenarios’ econo-technical parameters fall within acceptable ranges. However, the land photovoltaic system shows better performance, indicating some efficiency loss in the floating photovoltaic system possibly due to harsher offshore conditions. Based on the data from the reports, the study concludes that the econo-technical feasibility of floating photovoltaic in the Western Cape Province of South Africa is high.Item Deploying built-in quality to reduce scrap in an automotive component manufacturer(SAIIE, 2024-05-31) Dewa, Mendon; Makua, EdwardAutomotive component manufacturers face global competitive challenges, and the paradigm has shifted from product price as the determining factor of competitiveness to the quality of the product. An automotive component manufacturer was struggling to manage the outflow of defects, and adding inspectors as quality gates to the rear-step bumper production line had severe cost implications. This study aimed to reduce the number of defects by deploying a strategic path of implementing built-in quality. Quality tools were used, and the study’s results included significant manpower reduction, improved quality capability, and reduced scrap rates and reworks.Item Use of kaizen principle and line balancing technique for process improvement in the assembly of automotive components(SAJIE, 2022-11-11) Govender, Prenisha; Dewa, MendonContinuous process improvement is critical for organisations to stay in business. An automotive component manufacturer faced productivity challenges after the launch of a new hybrid C-SUV automobile in South Africa. This paper aims to improve the seat cover sewing process line through a line balancing technique. The use of process standard times to balance the production process initially led to bottlenecks, and the cycle time was above the takt time of the assembly line. Through the use of work-study analysis and time studies, the bottleneck processes were identified. Elements were then categorized, and kaizen implementation occurred at the processes. The processes were then rebalanced to meet the calculated cycle time. A root cause analysis was also conducted to investigate the sources of muda and the factors affecting the rate of working. The assembly line was then rebalanced, and the balance delay decreased by 33%.Item Fusion in cryptocurrency price prediction: a decade survey on recent advancements, architecture, and potential future directions(Institute of Electrical and Electronics Engineers (IEEE), 2022) Patel, Nisarg P.; Parekh, Raj; Thakkar, Nihar; Gupta, Rajesh; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.; Sharma, RaviCryptographic forms of money are distributed peer-to-peer (P2P) computerized exchange mediums, where the exchanges or records are secured through a protected hash set of secure hash algorithm-256 (SHA-256) and message digest 5 (MD5) calculations. Since their initiation, the prices seem highly volatile and came to their amazing cutoff points during the COVID-19 pandemic. This factor makes them a popular choice for investors with an aim to get higher returns over a short span of time. The colossal high points and low points in digital forms of money costs have drawn in analysts from the scholarly community as well as ventures to foresee their costs. A few machines and deep learning algorithms like gated recurrent unit (GRU), long short-term memory (LSTM), autoregressive integrated moving average with explanatory variable (ARIMAX), and a lot more have been utilized to exactly predict and investigate the elements influencing cryptocurrency prices. The current literature is totally centered around the forecast of digital money costs disregarding its reliance on other cryptographic forms of money. However, Dash coin is an individual cryptocurrency, but it is derived from Bitcoin and Litecoin. The change in Bitcoin and Litecoin prices affects the Dash coin price. Motivated from these, we present a cryptocurrency price prediction framework in this paper. It acknowledges different cryptographic forms of money (which are subject to one another) as information and yields higher accuracy. To illustrate this concept, we have considered a price prediction of Dash coin through the past days’ prices of Dash, Litecoin, and Bitcoin as they have hierarchical dependency among them at the protocol level. We can portray the outcomes that the proposed scheme predicts the prices with low misfortune and high precision. The model can be applied to different digital money cost expectations.Item Modeling of double stage photovoltaic inverter system with fast delayed signal cancellation for fault ride-through control application in microgrids(MDPI AG, 2022-02) Buraimoh, Elutunji; Davidson, Innocent E.This research presents a secondary control for a grid-supporting microgrid with photovoltaics sources to guarantee grid code compliance and ancillary services. The secondary control accomplishes the fault ride-through, which implements a delayed signal cancellation (DSC) algorithm for negative sequence detection. Without mode switching, the proposed control strategy meets grid code requirements and ensures voltage regulation at the secondary level, which is active and more salient throughout the transient period of host grid disturbances. This control also ensures a constant supply of the microgrid’s sensitive local load while adhering to grid code requirements. Similarly, active power injection into the main grid is limited by progressively altering the MPPT operating point dependent on the depth of voltage sag to optimize reactive power injection to sustain grid voltage sag. The recommended secondary control is triggered by utilizing the DSC process’s detection algorithm to identify the occurrence of a fault in a tiny fraction of a half-cycle in a grid fault. Consequently, while satisfying microgrid load needs, the devised technique guaranteed that increases in DC-link voltage and AC grid current were controlled. MATLAB Simscape ElectricalTM and OPAL-RT Lab are used to do time-domain simulations of the model using the recommended secondary control systems.Item Modelling of solar PV under varying condition with an improved incremental conductance and integral regulator(MDPI AG, 2022-04-01) Stephen, Akinyemi Ayodeji; Musasa, Kabeya; Davidson, Innocent EwaenThe introduction of solar photovoltaic (PV) systems would provide electricity accessibility to rural areas that are far from or have no access to the grid system. Various countries are planning to reduce their emissions from fossil fuel, due to its negative effects, by substituting with renewable energy resources. The use of solar PV systems is expanding globally because of growing energy demands and depleting fossil fuel reserves. Grid integration of the solar system is expected to increase further in the near future. However, the power output of solar PV systems is inherently intermittent, and depends on the irradiance and the temperature operation of the solar cell, resulting in a wide range of defects. Hence, it is vital to extract peak power from the solar panel in all conditions to provide constant power to the load. This paper presents a tracking control method of the peak output power of a solar PV system connected to a DC-DC boost converter using an improved incremental conductance and integral regulator (IC + IR). The research was carried out because the solar PV output is dependent on environmental parameters, such as solar insolation and temperature. Therefore, it is pertinent to forecast the peak power point in outdoor conditions and to operate at that point, so that solar PV can produce the highest output each time it is used. A peak power point strategy that maximizes the output of a solar PV array is proposed. This method establishes the maximum output operation point under the effects of the solar insolation and the module temperature. An automatic converter restoration scheme with block/de-block signal control is proposed to protect the converters from the higher phase current, total capacitor voltage deviation, grid disturbance, and fault current. The proposed scheme also tracks the peak power point (PPP) of the solar array with stable output voltage under varying operating conditions. It reduces the error signal and ripples at the PPP during instantaneous and incremental conductance to zero. In addition, it controls the solar PV system under constantly changing climatic conditions, and thus improves the system efficiency.Item Coalition games for performance evaluation in 5G and beyond networks : a survey(Institute of Electrical and Electronics Engineers (IEEE), 2022) Singh, Upendra; Ramaswamy, Aditya; Dua, Amit; Kumar, Neeraj; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.; Sharma, RaviThe 5G network is an emerging field of the research community. 5G is a multi-disciplinary network that aims to support a wide range of services. 5G network has an objective to support a massive number of connected devices. Game theory has an extensive role in wireless network management. Game theory is an approach to analyzing and modeling the system where multiple actors have a role in decisionmaking with independent objectives and actions. The game theory is an exciting methodology to control the strategic behavior of players and generate an efficient outcome. Coalition game theory can play a crucial role in ensuring cooperation among a massive number of devices. This article provides insight into the current research trends in 5G using coalition games. The work presented in the survey is divided into three categories, namely resource management, interference management, and miscellaneous. This article also provides the foundation about 5G and coalition games highlight the scope of future research.