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Theses and dissertations (Engineering and Built Environment)

Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/10

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    Energy assessment and scheduling for energy optimisation of a hot dip galvanising process
    (2021-12-01) Dewa, Mendon; Nleya, Bakhe; Dzwairo, Bloodless
    The dearth of energy sustainability is posing major challenges both locally and glob- ally. Galvanising furnaces are categorised as dominant consumers of electricity in the overall galvanising industry. Relatively little research has been carried out concerning energy optimisation through sequencing or scheduling algorithms by way of enhancing the performance of galvanising lines. In this regard, the research centres on evaluating overall energy performance in this industry. The research sought to introduce an opti- mal energy optimisation-scheduling algorithm for a hot dip galvanising process. A DMAIC based methodology was presented for the provisioning of a structured prob- lem-solving process for improving energy efficiency in a galvanising process. Its framework embraces an energy sustainability assessment of four batch hot-dip galva- nising plants. Four energy minimisation opportunities were identified and quantifiable energy and cost savings, as well as avoided carbon dioxide emissions were derived from the analysis of one of the plants. Production or zinc used was identified as the main driver for electricity consumption for Plant 1, while the number of dips per month, amount of zinc used, and ambient temperature conditions were identified as the rele- vant variables for developing a regression model for Plant 2. The amount of zinc used and ambient temperature conditions were found to be the relevant variables for Plant 3. The derived regression model for Plant 4 was based on the amount of zinc used and ambient temperature conditions. The energy performance indicators for a galvanising plant were established through a comparison of actual and expected consumption, energy intensity index, cumulative sum, and specific energy consumption. A bi-objective GECOS algorithm was further introduced to reduce the total energy consumption as well as makespan. The simula- tion results revealed that the GECOS algorithm outperforms McNaughton’s algorithm, Shortest Processing Time Algorithm, and Integer Linear Programming algorithms on minimising makespan on parallel processing machines. The key contributions to the body of knowledge from the study include a unique eval- uation of electrical energy consumption by a hot-dip galvanising plant, development of an energy consumption baseline and performance indices, and the developed novel bi-objective GECOS algorithm that considers reducing total energy consumption by the process tanks as well as makespan. Future research work may focus on hybrid genetic algorithm-artificial immune system scheduling tools that would derive synergy from the advantages of both algorithms to improve energy performance.
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    Investigating the root cause of solar power unsustainability in KwaZulu-Natal, South Africa
    (2020-05-05) Mdlolo,Bantubenzani Nelson; Olanrewaju, Oludolapo Akanni
    ABSTRACT Like many other countries, South Africa as a developing country relies on electricity as the most important basic amenity needed for development. KwaZulu-Natal (KZN) is a province in South Africa affected by an erratic supply of electricity. In the past few years, some areas in KZN region have continued to experience load shedding, while other areas do not have access to electricity at all. Municipalities are responsible for electricity supply and regulation in the KZN communities. Due to its geographical location KwaZulu-Natal enjoys a warm subtropical climate and receives year-round sunshine even in the winter months. It is thus an ideal region for the implementation of solar power on a large scale. Renewable energy in the form of solar power could easily generate an adequate supply of electricity to meet the electricity demand requirements and energy sustainability of the KZN province. South Africa has a renewable electricity generation of about 2% as per the research of United Nation Statistics Division of 2009 (Manju and Suger, 2017). However, the current access to electricity still faces the challenge of meeting demand and shortage of coal to generate electricity which the most important required to all South Africans; therefore, an effective alternative such as solar power is a necessity. The main challenge to the solar electricity supply is its unsustainability in the region. Intermittent load shedding coupled with the unsustainability of solar power, has negatively affected the economic performance of the region. This challenge (solar power unsustainability) limits the region from meeting the energy demands facing the KZN region. The main aim of this study was to investigate the root cause of solar power unsustainability in the KZN region. A quantitative method as well as a cost-benefit analysis was used to interrogate the solar power crisis in the KZN region. The Cost Benefit Analysis CBA gave an assurance of an early (financial) investment when implementing solar power in the eThekwini region. The adopted multiple regressions also revealed the high possibility of solar power performance of 0.75 r²-value. All challenges facing solar power are investigated through the cause and effect diagram as well. The Economical, Methodological and Environmental (EME) framework was proposed to address the unsustainability of solar power discovered in the region of KwaZulu-Natal. However, more work still needs to be done to investigate the potential growth of solar power in the region.