Please use this identifier to cite or link to this item:
https://hdl.handle.net/10321/4212
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Enitan, Abimbola Motunrayo | - |
dc.contributor.advisor | Han, Khin Aung | - |
dc.contributor.author | Ramrathan, Zesha | en_US |
dc.date.accessioned | 2022-09-01T14:28:39Z | - |
dc.date.available | 2022-09-01T14:28:39Z | - |
dc.date.issued | 2022-05-13 | - |
dc.identifier.uri | https://hdl.handle.net/10321/4212 | - |
dc.description | Submitted in fulfillment of the requirements for the degree of Master of Engineering: Civil Engineering Durban University of Technology, 2022. | en_US |
dc.description.abstract | Development and optimisation of valued added derivatives from wastewater represent the future sustainability paradigm. Among the various challenges in the management of wastewater treatment is the energy consumption for the treatment process that could render this process inefficient in terms of cost and energy consumption. This study focusses on the evaluation of egg-shaped digesters treating municipal wastes, and the optimisation of biogas production using computational intelligence approach (CIA) for sustainable energy production and policy implementation. The study further estimates the amount of electricity that could be generated from the optimised biogas produced from the anaerobic digesters. Historical 5-year (2010-2015) data of the anaerobic digesters were obtained from the Darvill Wastewater Treatment Plant in the KwaZulu-Natal Province of South Africa. The raw data were pre-processed for data cleaning, integration, reduction and data transformations using a rigorous scientific method to test their accuracy, reliability, consistency, and localisation gaps with different multivariate statistical tools. Computation intelligence methods using partial least square (PLS), principal component analysis (PCA) and Fuzzy Logic algorithms were used in this study for simulating the best operational condition and predicting the biogas production. The study further created a contextual framework against the assessment of biogas to energy potential and uses an excel-based tool to determine the bio-economy of energy recovery from an anaerobic egg-shaped digester per cubic meter of treated sludge. In average, the actual methane production was 59.60% while, predicted by Fuzzy-Logic was 65.4%. This shows that the model employed in the improvement of methane production from biogas plants by varying the operational parameters at; Inflow = 590m3 /day, Temp = 32.3°C, pH = 7.12, TS = 3.47%, VS = 43.4% and COD = 510 mg O2/L. The obtained total biogas production was 802.80 m3 /day based on status quo conditions and process configurations. The biogas production translates to electrical energy of 4580.5 KWh/day with an estimated saving (at R1.90 per kWh electricity) of approximately R3.1 million per annum. | en_US |
dc.format.extent | 145 p. | en_US |
dc.language.iso | en | en_US |
dc.subject | Biogas production | en_US |
dc.subject | Municipal wastewater treatment plant | en_US |
dc.subject | Computational intelligence | en_US |
dc.subject | Electricity | en_US |
dc.title | Evaluation and optimisation of biogas production in municipal wastewater treatment plant using computational intelligence approach : potential to generate electricity | en_US |
dc.type | Thesis | en_US |
dc.description.level | M | en_US |
dc.identifier.doi | https://doi.org/10.51415/10321/4212 | - |
local.sdg | SDG07 | - |
local.sdg | SDG11 | - |
local.sdg | SDG06 | - |
local.sdg | SDG12 | - |
local.sdg | SDG15 | - |
item.openairetype | Thesis | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | Theses and dissertations (Engineering and Built Environment) |
Files in This Item:
File | Description | Size | Format | |
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Ramrathan_Z_2022.pdf | Thesis | 2.42 MB | Adobe PDF | View/Open |
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