Faculty of Engineering and Built Environment

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Aerobic sequencing batch reactor for the treatment of industrial wastewater from the brewery
(2017) Shabangu, Khaya Pearlman; Chetty, Maggie; Bakare, Babatunde F.
One of the major effects of socio-economic change due to industrialisation is the generation of industrial wastewater, which requires treatment before being released into the environment. Laboratory-scale aerobic sequencing batch reactors under suspended-growth heterotrophic activated sludge were operated in different aeration configurations to study their effect on the treatment of wastewater generated by a local brewery. The main purpose of this study was to evaluate the performance of the two laboratory-scale aerobic sequencing batch reactors treating brewery wastewater under continuous low-oxygen dosing concentration and cyclic aeration schemes on SBR operation. The characterisation of brewery wastewater was undertaken to assess the physicochemical composition of the wastewater produced from one of the breweries in South Africa (SAB). The data showed distinctive characteristics of brewery wastewater, which coincided with studies previously carried out on characterisation of brewery wastewater. The COD average concentration of the brewery influent was 7100 mg/L, with average pH values of 7. The BOD and the total solids content of the brewery wastewater influent from the facility were both high, implying that the influent was very rich in organic content and its discharge into water-receiving bodies or the municipal treatment plant could have adverse effects. From these results, a need for a competitive treatment technology was clearly highlighted so as to carry out a feasible treatment of the influent for the brewery industry. The aerobic sequencing batch reactors were designed, fabricated and set up for laboratory-scale treatment of wastewater from the brewery for 15 weeks. The performance of the two SBR configurations was determined with reference to COD, BOD, TS, VS and TSS. The experimental results demonstrated that wastewater generated from the breweries can be treated successfully using both aeration configurations. The results obtained indicated that treatment efficiencies in terms of COD and BOD were 94 % and 85 % respectively, for the reactor operated under continuous aeration configuration, while 81 % and 65 % was achieved for the reactor operated in the cyclic aeration scheme. The findings from this study demonstrate that the performance of the reactor operated under the continuous aeration scheme was successful, and showed statistically significant differences from the performance of the reactor operated under cyclic aeration schemes. These findings imply that there is a potential for the equipment, including financial benefit as a result of operating aerobic sequencing batch reactors for treating brewery wastewater under continuous low-oxygen concentration dosing schemes. In this study, it was also established that the maximum COD removal could be reached at an optimum hydraulic retention times of 5 days for both reactors. This was based upon viewing the experimental data; it appeared that the most significant difference in percentage COD removal was for HRTs 3 days and 4 days. Although, due to less percentage COD removal observed from HRTs 5 days till 7 days, it was hence established that the optimum removal of high strength organics in the brewery wastewater could be achieved within 5 days of treatment time. The pH adapted at an average of 7 for all batch experimentations of the study. The temperature maintained an average of 23 oC ambient, throughout the experimental period. These physical parameters ensured that the microbial population was kept healthy, without inhibiting its biological degradation activity. Although, sludge build up was observed in both aerobic SBRs on completion of each batch operation due to solids retention and organic pollutants biodegradation from the brewery wastewater. It was perceived that frequently reseeding both aerobic SBRs, as an alternative to 28 days sludge retention time would enhance the recovery of biomass, thus improving the overall removal of TSS consequently minimising sludge bulking in both reactors.
Anaerobic co-digestion of agricultural biomass with industrial wastewater for biogas production
(2021-03-26) Armah, Edward Kwaku; Chetty, Maggie; Deenadayalu, Nirmala
With the increasing demand for clean and affordable energy which is environmentally friendly, the use of renewable energy sources is a way for future energy generation. South Africa, like most countries in the world are over-dependent on the use of fossil fuels, prompting most current researchers to seek an affordable and reliable source of energy which is also,a focal point of the United Nations Sustainable Development Goal 7. In past decades, the process of anaerobic digestion (AD) also referred to as monodigestion, has proven to be efficient with positive environmental benefits for biogas production for the purpose of generating electricity, combined heat and power. However, due to regional shortages, process instability and lower biogas yield, the concept of anaerobic co-digestion (AcoD) emerged to account for these drawbacks. Given the considerable impact that industrial wastewater (WW) could provide nutrients in anaerobic biodigesters, the results of this study could apprise decisionmakers and the government to further implement biogas installations as an alternative energy source. The study aims at optimising the biogas production through AcoD of the agricultural biomasses: sugarcane bagasse (SCB) and corn silage (CS) with industrial WW sourced from Durban, KwaZulu-Natal, South Africa. The study commenced with the characterisation of the biomasses under this study with proximate and ultimate analysis using the Fourier transform infrared spectroscopy (FTIR), the thermo gravimetric analysis (TGA), the scanning electron microscopy (SEM) and the differential scanning calorimetry (DSC). The untreated biomass was subjected to biochemical methane potential (BMP) tests to optimise and predict the biogas potential for the selected biomass. A preliminary run was carried out with the agricultural biomass to determine which of the WW streams would yield the most biogas. Among the four WW streams sourced at this stage, two WW streams; sugar WW (SWW) and dairy WW (DWW) produced the highest volume of biogas in the increasing order; SWW ˃ DWW ˃ brewery WW > municipal WW. Therefore, both SWW and DWW were selected for further process optimisation with each biomass. Using the response surface methodology (RSM), the factors considered were temperature (25-55 °C) and organic loading rate (0.5-1.5 gVS/100mL); and the response was the biogas yield (m3 /kgVS). Maximum biogas yield and methane (CH4) content were found to be 5.0 m3 /kgVS and 79%, respectively, for the AcoD of CS with SWW. This established the association that existed among the set temperatures of the digestion process and the corresponding organic loading rate (OLR) of the AcoD process operating in batch mode. Both CS and SCB have been classified as lignocellulosic and thus, ionic liquid (IL) pretreatment was adapted in this study to ascertain their potential on the biogas yield. Results showed that the maximum biogas yield and CH4 content were found to be 3.9 m3 /kgVS and 87%, respectively, after IL pretreatment using 1-ethyl-3-methylimidazolium acetate ([Emim][OAc]) for CS with DWW at 55°C and 1.0 gVS/100mL. The IL pretreatment yielded lower biogas but of higher purity of CH4 than the untreated biomass. Data obtained from the BMP tests for the untreated and pretreated biomasses were tested with the existing kinetic models; first order, dual pooled first order, Chen and Hashimoto and the modified Gompertz. The results showed that for both untreated and pretreated biomass, the modified Gompertz had the best fit amongst the four models tested with coefficient of correlation, R 2 values of 0.997 and 0.979, respectively. Comparatively, the modified Gompertz model could be the preferred model for the study of industrial WW when used as co-substrate during AcoD for biogas production. The study showed that higher biogas production and CH4 contents were observed when CS was employed as a reliable feedstock with maximum volume of the untreated and pretreated feedstock reported at 31 L and 20 L respectively.
Anaerobic co-digestion with industrial wastewater for biomethane production
(2020-10-20) Adedeji, Jeremiah; Chetty, Maggie
The increasing demand for energy has led to the utilization of fossil fuels more abundantly as a quick alternative for generation of energy. The use of these sources of energy however as led to the generation of greenhouse gases which tend to cause climate change, thus affecting the ecosystem at large. Thus, there have been the search for alternative sources which cannot be depleted but do generate minimal greenhouse gases. One of such alternate sources is industrial wastewater which have shown to have high concentration of nutrients in the form of organic contents which can be converted by micro-organisms into energy, usually known as biogas, comprising majorly of CH4, CO2 and H2. Another important factor is that industrial wastewaters are a renewable energy source which are continuously generated due to increasing urbanisation and population growth. In this study, the characteristics of three agro-industrial based wastewaters used shows their potential for application in anaerobic co-digestion”. Anaerobic co-digestion method was utilized to harness the synergetic effect of both sewage sludge and agro-industrial wastewater as co-substrate for the generation of biomethane. The result of the effect of varying mix-ratio of the substrates on biomethane production of sugar wastewater and dairy wastewater indicated that mix-ratio of 1:1 for sewage sludge to sugar wastewater operated at 35oC was suitable for optimum generation of biomethane of 1400.99 mL CH4/g COD added and COD reduction of 54%. The model generated using design expert was found to navigate the design space and could perfectly predict the yield of biomethane effectively for the sugar wastewater mix. The biomethane potential tests (BMP) experiment using varying inoculum-substrate ratio (ISR) showed that operating at mesophilic temperature of 25oC with ISR of 1:2 and 2:1 for sugar wastewater and dairy wastewater respectively does increase the methane production within the first three (3) weeks. The kinetic models that best fit the anaerobic co-digestion for sugar wastewater was the first order model while the simplified Gompertz model favoured the dairy wastewater perfectly. The biomethane potential tests indicate significant increase the biomethane production and as well reduction in the volatile solid and chemical oxygen demand (COD) content. In conclusion, both sugar and dairy wastewater can be recommended as co-substrates for anaerobic digestion of sewage sludge for increased and improved biomethane production while simultaneously reducing their COD content at the same time.
The analytical and experimental study on the establishment of a tidal power plant in South Africa
(2021-02) Mtukushe, Namhla Faith; Ojo, Evans Eshiemogie
The majority of South Africa’s electricity is generated from fossil-fuel plants that use mainly coal. In these power plants, the combustion of these fossil fuels liberates greenhouse gasses into the atmosphere that contribute to climate change. This problem coupled with the rapid depletion of fossil fuels has necessitated the need to explore the alternative form of energy such as renewable energy. Tidal energy is a form of ocean energy that can be considered as an alternative energy resource or renewable energy source. This form of energy has not been explored in South Africa, the only country in the world that is bounded by two oceans; the Indian and the Atlantic. Tidal energy can be harnessed from the movements of tides to generate electrical power. This study considered the possibility of harnessing tidal energy as the alternative energy source for power generation which can be used to mitigate the challenges associated with the energy crisis currently being experienced in the country. For this study, an extensive literature review was carried out to understand the tidal phenomenon, the concept of energy conversion from tides, the different techniques or technologies that can be used to generated power from tides. There are two main technologies used for converting tidal energy to electrical energy and these are the tidal barrage and the tidal streams. Based on the inferences drawn from the literature reviews concerning the tides experienced around the South Africa coastal region, it was identified that the tidal stream technique is applicable. Harmonic analysis of the tidal resource for four identified sites was conducted, from these analyses, Esikhawini was selected as an optimum site. Tidal streams extract the kinetic energy of tides and the mode of operation of tidal stream plants is determined by the type of tidal turbine employed. Several turbine designs were reviewed, a helical cross-flow turbine was selected due to its self-starting capability and its ability to operate in reverse stream flows. For this helical turbine, an analytical model using the blade element momentum theory (BEMT) was developed and was implemented on MATLAB environment. For the experimentation, a prototype was developed and tested in a laboratory concrete flume in the department of Civil Engineering at the University of KwaZulu-Natal. Based on the experimental results, an analysis of the unit turbine was done which was used to propose a conceptualized tidal power plant. Hence, the proposed tidal power plant was used to justify the reason for embarking on this study which is to ascertain the possibility of establishing a tidal power plant in South Africa.
Application of optimal control for power systems considering renewable energy technologies
(2021-03) Chetty, Dhanpal; Sharma, Gulshan; Davidson, Innocent Ewaen
Over the last decade, power generation from renewable energy sources such as wind, hydro and solar energies have substantially increased globally and in South Africa. Of all the renewable energy sources, wind energy appears to be the most promising, considering design and costs. However, due to the intermittent nature of wind, the increased integration of wind energy into existing power systems raises several control challenges related to load frequency control (LFC) and tie-line power system stability. The stability of modern power systems, incorporating wind energy generations, will be significantly enhanced with the development of LFC strategies based on modern control theory, which is the focus of this research. This thesis presents the design, modelling and analysis, of two LFC control strategies for interconnected power systems, having wind power integrations. The first design is an optimal control strategy, based on error minimization through full state vector feedback, for a two-area interconnected power system consisting of hydro-thermal generations. The second design is a model predictive control (MPC) strategy, based output vector feedback of system state parameters, for a two-area interconnected power system consisting of thermal generations in each area. Both designs include the active power support from doubly fed induction generator based wind turbines (DFIG) in conjunction with the combined effort of a thyristor control phase shifter (TCPS) and super conducting magnetic energy storage unit (SMES). Both control strategies were simulated in MATLAB Simulink and positive results were obtained. The results show that the optimal control strategy is enhanced with power integrations using DFIG based wind turbines combined with the TCPS-SMES units and the MPC strategy is very robust and provides better dynamic performances even with parameter variations and generation rate restrictions.
Application of organic coagulants in water and wastewater treatment
(IntechOpen, 2019-04-03) Tetteh, Emmanuel Kweinor; Rathilal, Sudesh
Coagulation is an essential mechanism that occurs in most conventional water and wastewater treatment plants. This occurs in a physical purification unit involving transport processes and the addition of coagulants for chemical reactions, charge neutralization, and formation of smaller flocs to agglomerate into larger flocs. This enhances the effective removal of recalcitrant contaminants by downstream processes. However, poor treatment of wastewater might have a high negative impact on biodiversity and the environment in general. This chapter seeks to address the limitation of employing inorganic coagulants by evaluating the efficiency of organic coagulants and exploring the factors and mechanism governing coagulation in a physiochemical treatment process of water and wastewater resources. The effect of pH, coagulant type and dosage to ease the high sludge production and discharge of residual metals into the downstream waters is addressed. The emerging of organic coagulants and technology to mitigate the performance and recovery of mineral coagulants from wastewater treatment residual is been proposed.
Application of synthesized magnetic nanoparticles for biogas production using anaerobic digestion
(2023) Amo-Duodu, Gloria; Rathilal, Sudesh; Chollom, Martha Noro
South Africa is encountering severe challenges in the areas of energy, water, and wastewater management in recent times. This study addresses both water and energy aspects. It aims at using synthesised magnetic nanoparticles (MNPs) on anaerobic digestion (AD) for biogas production from various wastewater sources in South Africa. The study experimented the feasibility of five different synthesized magnetic nanoparticles, magnetite (Fe3O4), copper ferrite (CuFe2O4), nickel ferrite (NiFe2O4), magnesium ferrite (MgFe2O4) and aluminium ferrite (AlFe2O4) on two different wastewater samples (industrial and municipal wastewater) from three sampling sources, Umbilo water works, Umgeni water and a sugar refinery industry. Five research objectives were accessed. The first objective was the synthesis and characterisation of MNPs using scanning electron microscopy/energy dispersive x-ray (SEM/EDX), Brunauer-Emmett-Teller (BET), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analysis. The results showed a surface morphology of facecentred and monoclinic crystal structures with a size less than 20 nm. The nanostructures of ferrimagnetite and magnetite were obtained, and it had an O-H stretching and Fe-O vibration functional groups. The surface area obtained was found to be high for magnetite (Fe3O4) which was 27.597 m2 /g. The second objective was to evaluate the AD performance in terms of water quality and biogas production. This was carried out in two stages. The first was to evaluate the five MNPs with sugar refining wastewater. The second stage was to evaluate the performance of three best performing MNPs on two wastewater samples from Umbilo wastewater. The results for the first stage showed good degradation of organic matter for the bioreactors with MNPs which resulted in a higher yield of biogas and methane as compared to the control as well as good removal of contaminant (chemical oxygen demand (COD), colour and turbidity). Among the five MNPs used, Fe3O4, NiFe2O4 and CuFe2O4 had a contaminant removal efficiency of 60- 70% and a cumulative biogas yield of more than 140 ml/day with more than 85% methane composition, hence these three MNPs were found to be the best performed MNPs. The results obtained from the second stage for the three best performed MNPs indicated a high pollutant removal efficiency of more than 70% for Fe3O4, as well as a biogas yield of more than 1100 ml/day and a methane composition of approximately 98%. The third objective was the evaluation and optimisation of the anaerobic magnetised system for biogas production while the fourth objective involved a comparative study between the performances of magnetised biochemical methane potential (BMP) to non-magnetised biochemical methane potential. From the optimisation study, the predicted results obtained from the BBD-RSM showed an average contaminant removal of 70% and a biogas yield of 522 ml/day at an optimum MNP load of 0.5 g, retention time of 45 days, inoculum load of 500 ml, and a temperature of 35℃ with a desirability of 96% as the optimum conditions. With less than 2% deviation, the confirmatory test demonstrated equal performance at the optimum conditions. Findings from the fourth objective indicated that the BMP system with MF exposure exhibited a contaminant removal rate of over 80% and a biogas generation of 1715 ml/day with a 99.94% methane composition. Overall, the system that included both MF and MNP performed better than the other in terms of biogas yield and colour removal. The final objective was the kinetic study of the anaerobic magnetised system using modified Gompertz and first-order kinetic models. The results obtained from the kinetics showed that the modified Gompertz model described the kinetics and dynamics of the anaerobic magnetised system better than the firstorder kinetic model with a correlation co-efficient (R2 ) over 0.9999 and an error less than 0.0002. Therefore, the possibility of using MNPs, particularly magnetite (Fe3O4), in an AD system for biogas production from wastewater was found to be extremely feasible and without negative environmental consequences. Incorporating both MF and MNP in AD was also beneficial for wastewater treatment because it eliminated the need for post-treatment.
Applications of artificial intelligence to photovoltaic systems : a review
(MDPI AG, 2022) Mateo Romero, Héctor Felipe Mateo; González Rebollo, Miguel Ángel González; Cardeñoso-Payo, Valentín; Alonso Gómez, Victor Alonso; Redondo Plaza, Alberto Redondo; Moyo, Ranganai Tawanda; Hernández-Callejo, Luis
This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training . Research is still being conducted in order to solve these problems and find techniques with better performance. This article analyzes the most relevant scientific works that use artificial intelligence to deal with the key PV problems by searching terms related with artificial intelligence and photovoltaic systems in the most important academic research databases. The number of publications shows that this field is of great interest to researchers. The findings also show that these kinds of algorithms really have helped to solve these issues or to improve the previous solutions in terms of efficiency or accuracy.
Artificial intelligence based solar/diesel hybrid water pumping system
(2021-12-01) Moyo, Ranganai Tawanda; Tabakov, Pavel Y.
Solar energy powered systems are increasingly being implemented in different areas due to the advances in solar energy technologies. Some of the major areas for solar energy applications include solar water heating, solar electric power generation, and solar water pumping. Solar water pumping has become the most adopted solar energy technology in the last decade. It has been considered as an attractive way to provide water in remote areas. A major advantage of using solar water pumps is that they are naturally matched with solar irradiation since usually water demand is high in summer when solar irradiation has its maximum values. However, solar energy powered systems are weather dependent. In most cases, a solar energy source has to be combined with another energy source to form a hybrid system to overcome the demerits of using solar alone. This thesis provides the detailed design, modelling and analysis of an Artificial Intelligence (AI) based solar/diesel hybrid water pumping system. This research aims to develop an optimization model that uses AI techniques to maximize the solar energy output and manage the energy flow within the solar/diesel hybrid water pumping. Thus, the proposed system is composed of solar photovoltaic modules, battery bank, Variable Speed Diesel Generator (VSDG), Adaptive Neuro-Fuzzy Inference System (ANFIS) based Maximum Power Point Tracking (MPPT) controllers and an Energy Management Controller (EMC). The EMC, which is based on Fuzzy Logic (FL), is responsible for managing the flow of energy throughout the hybrid system to ensure an undisturbed power supply to the water pump. The PV array, battery bank, VSDG are all sized to power a 5Hp DC water pump and the ANFIS based MPPT controllers are proposed for improving the efficiency of PV modules. The modelling of the system components is performed in the MATLAB/Simulink environment. For evaluation of the proposed system, several case scenarios were considered and simulated in the MATLAB/Simulink environment. The simulation results revealed the effectiveness of the proposed ANFIS based MPPT controllers since the controllers were able to extract maximum available power from PV modules for both steady-state and varying weather conditions. The proposed EMC demonstrated the successful management and control of the energy flow within the hybrid system with less dependency on the VSDG. The EMC was also able to regulate the charging and discharging of the battery bank.
Assessing the current live fire training structure environment in Ethekwini using CFD
(2020-03-12) Clarke, Thomas Benjamin Bayliss; Walker, Mark; Mendham, Frank
eThekwini Fire and Emergency Services currently uses a repurposed structure to train their firefighters. This study identifies fire related hazards for trainee firefighters when using the ground and first floor of the existing structure. The purpose is to prevent shortcomings being repeated in the design of future firefighter training structures. The fire related hazards have been identified by using Computational Fluid Dynamics (CFD) to simulate fires in the existing structure. The fundamentals of CFD, as well as the selected CFD based fire model, have been summarized. CFD is selected due to its flexibility, accuracy, and cost effectiveness [1]. The Fire Dynamics Simulator (FDS) is the selected CFD based fire model as it has been extensively validated in the past decade [2], which is an important factor should the CFD code claim any credibility [3]. It was developed by the National Institute of Standards and Technology (NIST) to model fire driven fluid flow. It does this by numerically solving a form of the Navier Stokes equations appropriate for thermally driven low Mach flow [4]. Appropriate inputs required for FDS were investigated specifically for live fire training structures. A unique heat release rate (HRR) was investigated and subsequently proposed for a fire on both the ground floor and first floor. The HRR was assessed to find a rate that will be safe from inducing ventilation-controlled conditions and therefore preventing the occurrence of an explosive backdraught. This was investigated by monitoring the effect of the existing structure on a t-squared fire. A t-squared fire uses a selected growth coefficient to estimate the fire’s HRR when the data on the actual fire is not available. Also, the suitability of selecting the emissivity of soot for surfaces was investigated. This was done because it is expected that there would be residual soot deposits in the existing structure. The investigation used the soot modelling capabilities of FDS. This identified the soot density on exposed surfaces and provided an indication on the number of fires required to cover the majority of the exposed surfaces with soot. The simulations performed in this study were within the required validation range. This included using a selected numerical grid size that was within the validation range for the plume resolution index. There is a range of grid sizes that are valid for the plume resolution index and so to assist in the selection of a suitable grid size from the range of valid grid sizes, the implications of time constraints to complete a simulation were investigated. The investigation compared the accuracy of FDS results when having to restart the simulation multiple times due to limited computer access time, with the accuracy of FDS when using a coarser grid. From the fire induced environment, the heat flux and gas temperature were estimated to assess the safety of training firefighters. After examining past firefighter deaths, it was considered necessary to include normal civilian tenable limits in the study to identify the time to incapacitation should mistakes occur during training. The structure’s surface temperature was also measured to assess possible structural damage due to the concern that the existing structure has been damaged from repeated heating and cooling.
An assessment of the adoption of smart building concept in the Nigerian construction industry
(2022-05-13) Ejidike, Cyril Chinonso; Mewomo, M. C.
Technological penetration across developing countries has impacted the construction industry, with more construction stakeholders deploying various technologies into the building lifecycle's design, construction, management, and maintenance. The building sector has evolved by adopting and implementing smart tools for its operations over the past few years. Building information modelling (BIM), the internet of things (IoT), and smart devices (sensors) are game-changers that have helped to reduce the complexity of construction activity and increase productivity. Meanwhile, introducing the sustainable development concept in the construction industry has enabled the proper management of the earth's natural resources and provided a pathway for ecosystem balance alongside socio-economic development. Amid the skyrocketing population growth, urban sprawl, and globalization, the building industry is confronted with the challenge of providing adequate and holistic built infrastructures such as efficient energy management, good water supply, occupants' indoor comfort, and the management of construction waste. The smart building concept (SBCs), which employs sustainable construction whereby the built product is constructed according to best practices, including efficient energy use, the recycling of raw material, and the realization of a sustainable and carbon-free environment, has demonstrated the digitalization of sustainable development in the construction industry. Therefore, this dissertation seeks to asseeement of the adoption of smart building concepts in the Nigerian construction industry. The research poses the following questions: 1) What is the awareness level of construction professionals in the adoption of the smart building concept (SBCs) in the Nigerian construction industry? 2) What factors can enhance the awareness of the smart building concept among construction professionals in the Nigerian construction industry? 3) What factors enhance the adoption of SBCs among professionals in the Nigerian construction industry? 4) What are barriers to adopting SBCs in construction projects in the Nigerian construction industry? A random sampling technique in selecting the construction professionals. The total population of construction professionals within the study area is 5,108, comprising construction professionals of Architects, Builders (Mechanical, Electrical, and Structural), Engineers, and Quantity Surveyors practicing in Lagos state. The sample size selection was made using the Yamane formula (1967) for calculating sample size. Therefore, the sample for this study is 363. A well-structured questionnaire of 363 was administered to construction professionals to gather relevant data on the topic. The data collected were analyzed using the Kruskal Wallis H test and weighted mean, factor analysis, and binary regression analysis, and mean item score and agreement analysis technique. The key finding of the research indicated that construction professionals are generally aware of the smart building concept. Administration, education, organizational, and environmental factors were discovered to enhance the adoption of smart building concepts among construction professionals. Furthermore, the research indicates that energy and cost-saving, job creation, safety and security, and health care are the critical factors enhancing in adoption of smart building concepts among construction professionals in the Nigerian construction industry. Lastly, the research result discovered that the high cost of smart building materials, inadequate power supply, resistance to change from the use of traditional technology, poor maintenance culture, poor knowledge of smart building technology, inadequate well-trained labour in the practice of smart building construction, and inadequate finance schemes are the significant barriers to the adoption of smart building concept. Based on this research finding, the research recommends that construction professionals engage more in smart building concepts, propagating the country's awareness and development of smart building construction. Furthermore, the government should establish a common platform for the collaboration of all stakeholders, such as professionals in the construction industry and academia, by way of policymaking and funding of research and development towards implementing these smart technologies. It will go a long way for employment creation and improve the country's economy. This study contributes to the body of knowledge by discovering the critical factors that will aid the successful adoption of the smart building concept in the Nigerian construction industry.
An assessment of the impact of selected construction materials on the life cycle energy performance and thermal comfort in buildings
(2021) Haripersad, Rajesh; Lazarus, Ian Joseph; Singh, Ramkishore; Aiyetan, Olatunji Ayodeji
South Africa is a developing country with various construction projects that are being undertaken both by government and the private sector. The requirements for the construction of energy-efficient buildings as well as the selection methods for providing construction materials have hence become important. Energy efficiency improvements needs to be implemented in the construction of these buildings in order to decrease energy usage and costs and provide more comfortable conditions for its occupants. Previous studies revealed that most of the focus for improving energy efficiency in buildings has been on their operational emissions. It is estimated that about 30% of all energy consumed throughout the lifetime of a building is utilized as embodied energy (this percentage varies based on factors such as age of building, climate and materials). In the past this percentage was much lower, but with increased emphasis placed on reducing operational emissions (such as energy efficiency improvements in heating and cooling systems), the embodied energy contribution has become more significant. Hence, it is important to employ a life-cycle carbon framework in analysing the carbon emissions in buildings. The study aims to augment energy efficiency initiatives by showcasing energy reduction strategies for buildings. The study assessed the thermal performance of selected construction materials by analysing different buildings using energy modelling program, EnergyPlus and TRNSYS. The parametric study was set in the central plateau region of South Africa and was performed to determine appropriate energy efficiency improvements that can be implemented for maximum savings. A life cycle cost analysis was performed on the selected improvements. The models created are representative of the actual buildings when simulated data is compared to recorded data from these buildings. Results showed a significant variation in energy and construction costs with varying construction materials over the buildings’ life cycle. Findings suggest that there is a significant reduction in energy usage when simple efficiency measures are implemented. The study recommends the use of different energy efficient building materials and the implementation of passive interventions in the constructing of buildings; the thermal performance of a building be optimized to ensure thermal comfort and the developed model be adopted for use in the engineering and construction industry for the reduction of energy consumption.
Balancing between demand and trading in microgrids
(IEEE, 2020-01) Gomba, Masimba; Chidzonga, Richard; Nleya, Bakhe; Khumalo, Philani
The envisaged future generation power or smart grid (SG) will incorporate ICT technologies as well as innovative ideas for advanced integrated and automated power systems. The bidirectional information and energy flows within the envisaged advanced SG together with other aiding devices and objects, promote a new vision to energy supply and demand response. Meanwhile, the gradual shift to the next generation fully fledged SGs will be preceded by individual isolated microgrids voluntarily collaborating in the managing of all the available energy resources within their control to optimally serve both demand and distribution. In so doing, innovative applications will emerge that will bring numerous benefits as well as challenges in the SG. This paper introduces a power management approach that is geared towards optimizing power distribution, trading, as well as storage among cooperative microgrids (MGs). The initial task is to formulate the problem as a convex optimization problem and ultimately decompose it into a formulation that jointly considers user utility as well as factors such as MG load variance and associated transmission costs. It is deduced from obtained analytical results that the formulated generic optimization algorithm characterizing both aggregated demand and response from the cooperative microgrids assist greatly in determining the required resources hence enabling operational cost viability of the entire system.
Bioremediation of acid mine drainage and crude contaminated soils
(2020-09) Anekwe, Ifeanyi Michael; Isa, Yusuf Makarﬁ
Pollution is one of the greatest ills plaguing the existence of the ecosystem which could lead to the annihilation of terrestrial and aquatic habitat if not remedied. Acid mine drainage (AMD) and crude oil are among the major land and water pollutants cause by industrial and human activities. The constant exploration, mining, and processing of mineral resources and prevalent use of petroleum products for economic purposes have contributed to contamination of soil and proximate water bodies which results in environmental degradation; thus, remediation becomes necessary. The treatment of AMD contaminated soils using the conventional methods has some room for improvement to meet the remediation purpose. Bioremediation technology provides a sustainable and eco-friendly approach to the treatment of contaminants. This study aims to evaluate the performance of different potential bioremediation techniques and conduct a comparative analysis of these methods for the treatment of AMD and crude oil-contaminated soils. The treatment approach for both pollutants comprises of soils separately contaminated with AMD and crude oil before the application of bioremediation techniques. For the biostimulation study, contaminated soils were amended with varying ratios of the brewery or municipal wastewaters (BWW and MWW), while the bioventing (BVT) treatment involved wastewater amendment and supply of atmospheric air from the vadose zone at 3L/min at 30 minutes intervals every 48 hours. The bacteria strain Pseudomonas aeruginosa ATCC 15442 used for the study which was inoculated at 5%(w/w) was cultured in two different media for respective treatments and wastewater was amended as an extra energy source for bioaugmentation (BAU) study while Bioattenuation (BAT) which received no amendment was used as a control treatment for the study. The treatments were conducted in plastic bioreactors under mesophilic conditions for 28 days and samples were collected from each treatment system on weekly basis to analyse for sulfate, heavy metals, and total petroleum hydrocarbon (TPH) reduction. The result of the study showed that the amendment of contaminated soils with wastewater increased alkalinity in the system which enhanced microbial activities for effective remediation which recorded 52.43 and 51.23% average TPH and metal removal efficiency for the BSTc treatment. Also, the combined application of bioremediation techniques was more effective than single application as the introduction of oxygen into the treatment system with wastewater amendment increased the TPH and metal removal efficiency by an average of 12.98 and 13.17% respectively but efforts to enhance sulfate removal by air-injection (BVTa) proved abortive with 17.20 and 14.67% removal efficiencies less than BSTa and BAUa respectively as sulfate-reducing bacteria thrive in an anaerobic environment. However, P. aeruginosa ATCC 15442 adopts the sorption process in the reduction of hydrocarbon and metal toxicity with 42.02 and 41.81% average removal efficiencies respectively and the amendment extra nutrient (wastewater) increased the removal efficiency of these pollutants by 25.24 and 16.23% respectively. The results of the study inferred that wastewater (BWW and MWW), air-injection and P. aeruginosa ATCC 15442 showed great potentials in the degradation and removal of TPH, metals and sulfate contaminants, hence, can serve as a viable strategy for the remediation of AMD and crude oil polluted soils while improving waste management and amelioration of pollution aftermath faced by communities involved in mining and oil production and/or processing. There is a need for optimization to ensure effective remediation while further study is required to validate large scale application.
Comparative analysis of different computational intelligence techniques for maximum power point tracking of PV systems
(University of Oradea, 2022-10-01) Moyo, Ranganai Tawanda; Tabakov, Pavel Y.; Moyo, Sibusiso
The performance of a photovoltaic (PV) module can be improved by employing maximum power point tracking (MPPT) controllers. MPPT controllers are algorithms that are included in PV battery charge controllers or inverters to extract the maximum available power from PV modules for any given temperature and irradiance. Several studies report that the use of PV modules without MPPT controllers results in power losses, which ultimately results in the need to install more solar panels for the same power requirement. Numerous techniques of varying complexities have been proposed in the literature to solve the MPPT objective function. This paper presents a comparative analysis of three computational intelligence (CI) based MPPT techniques namely, the fuzzy logic (FL) based controller, artificial neural networks (ANN) based controller, adaptive neuro-fuzzy inference system (ANFIS) based controller and one conventional technique, the perturbation and observation (P&O) controller. These MPPT controllers are designed, simulated and analysed in the MATLAB/Simulink environment. The performance of the studied MPPT techniques is evaluated under steady-state weather conditions, rapidly changing weather conditions and varying load conditions. CI-based MPPT controllers are found to be more efficient than the P&O controller. Moreover, the ANFIS-based MPPT controller shows an outstanding MPPT performance for all the scenarios studied.
Comparative analysis of high voltage alternating current & high voltage direct current offshore collection grid systems
(2021-12-01) Pillay, Caleb Jordache; Musasa, Kabeya; Davidson, Innocent Ewaen
An increase in industries as well as the world’s population, is causing a strain on the electricity supply. This coupled with the fact that fossil fuel supplies are decreasing, is leading the world to new, greener methods of electrical energy generation. Offshore wind farms are being developed far offshore and solar farms are being developed in remote locations with intense sunlight. This allows for the optimal operation of these systems. HVAC collection systems for offshore wind farms have traditionally been used but imposes limitations on the transmission distance. Exuberant amounts of capital are required for greater distances. HVDC systems have started to be recognised as a viable method of transmitting this electrical energy at a much lower cost on longer distances. This study shows a comparative performance and cost evaluation of both HVAC and HVDC collection systems for offshore wind farms. It evaluates the efficiency of the wind farm based on system losses, determines the advantages, disadvantages, and cost implications of each system, and determines the best type of technology to be used in offshore applications. The study looks at a case of a 40 MW wind farm at a distance of 120 km offshore. A simulation is developed for each system using MATLAB simulation software to determine the performance of each system during normal operation and fault conditions. From these simulations, it was found that HVDC collection systems have much higher efficiency when compared to HVAC systems and perform better under both normal operation and fault conditions. HVDC systems also have a lower cost once the break-even distance point is passed. From the study, it is found that HVDC collection systems are much better suited to allow offshore wind farms to have a high efficiency as well as be located further offshore to allow for maximum wind usage. The technology can be used for other long-distance transmission systems and incorporated for other renewable energy generation systems.
Comparative analysis of specific energy consumption and energy consumption benchmarking in galvanising plants
(IEOM Society International, 2022-08-04) Dewa, Mendon
The inadequacy of sustainable energy is endlessly posing major challenges globally. The issue of energy optimisation is indispensable for manufacturing sector, particularly for a hot-dip galvanising process where galvanising furnaces are the significant energy users. This study is aimed at comparative analysis of specific energy consumption and energy consumption benchmarking in four galvanising plants with the view to necessitate the identification of best practices. Energy baselines were used as quantitative reference points to compare energy performance indicators and quantify fluctuations in energy performance during the baseline and reporting periods. A quantitative analysis was also conducted to benchmark four galvanising facilities on factors that included the electricity/zinc ratio, electricity /dips ratio and product tonnage/zinc used ratio. The results revealed improved performance for plant 4 over time relative to the baseline consumption when compared to plants 1, 2 and 3. Plant 4 also outperformed other facilities after the energy efficiency interventions in terms of electricity/zinc ratio and electricity/ product tonnage ratio. Given the disparity between the results of specific energy consumption (SEC) for the four plants, it was concluded that SEC alone should not be used as an energy performance indicator.
Control of multi-level voltage source converters integrating a wind turbine system into the grid
(IEEE, 2016) Hamatwi, E.; Davidson, Innocent E.; Gitau, M.N.
In recent years, wind energy has proven to be the most competitive and environmental friendliest renewable energy (RE) source for generating electricity. Wind farms are more likely to be located far from the load centres, and hence the generated power has to be transmitted over long distances. A high voltage direct current (HVDC) transmission system increases the transmission capacity, improves the system stability, and possesses lower transmission losses. Therefore, it is the preferred means for power delivery over long distances compared to the high voltage alternating current transmission system. In this paper, a 690V, 2MW wind turbine is modelled to be integrated into a 33kV AC grid via a 3-level Neutral-Point-Clamped Voltage Source Converter-based HVDC transmission system. Three control schemes were implemented: a pitch-angle controller, a controller applied to the generator-side converter, and a controller applied to the grid-side converter. The proposed wind energy conversion system and control schemes were implemented in MATLAB/SIMULINK and simulations were carried out to analyse the performance of the system.
Coordinated control of conventional power sources and plug-in hybrid electric vehicles for a hybrid power system
(2022-05) Adbul-Kader, Mohammed Ozayr; Akindeji, Timothy Kayode; Sharma, Gulshan
Globally, the requirement for renewable and clean energy technologies is becoming vastly popular. With the high implementation of solar and wind energy systems, together with plugin hybrid electric vehicle (PHEV) aggregators, energy costs can be minimised, greenhouse gas emissions decrease, and overall maintenance becomes reduced. The constant increase of load demand is becoming a challenge for the current power systems, with difficulties including stability concerns and excessive regulations by the government. Due to irradiance and wind speed fluctuations, the solar and wind energy system’s non-linearity affects the existing power system stability. The growth of the electric vehicle industry has also shed new light on potential auxiliary services that can be provided, as and when required, to the power system. Hence, this research examines the potential control strategies that are required to maintain the system in steady-state conditions after disturbances that occur with higher penetration of renewable energy systems (RESs) and PHEVs. The case study models a isolated two-area thermal type power system that is interconnected through an AC tie-line. Three scenarios are modelled, simulated and analysed. The first scenario models a isolated thermal power system with PHEVs with two areas which utilises a fractional order proportional integral derivative (FOPID) controller in each area. The resulting model is analysed to see the effects of PHEVs coupled with FOPID on the power system. The second scenario models a isolated two-area thermal power system with RES and utilises a fuzzy type-2 (FT2) FOPID controller in each area. The RES penetration istested for its non-linearity effect on the isolated power system, and the error is reduced by an advanced controller that uses artificial intelligence techniques. The third scenario is modelled as an isolated two-area thermal power system with PHEVs and RES coupled with neural network predictive controller (NNPC) in each area. The three scenarios are simulated in MATLAB/Simulink with results displayed graphically and numerically. The results show that the integration of PHEVs for load and/or storage in the multi-area power system, and the proposed control methods for each scenario, have the best dynamic response with the least error, no oscillations and the fastest response to steady state condition.
Curbing electricity theft using wireless technique with communication constraints
(IEEE, 2020-08) Tshikomba, Salome C.; Estrice, Milton; Ojo, Evans E.; Davidson, Innocent E.
Utility services are experiencing a common problem of power losses, which impose a significant impact on their annual budget. Practically, power losses consist of technical losses and non-technical losses. Technical losses are due to operations and aging of infrastructure, while nontechnical losses (NTL) are due to non-metered energy. The focus is on managing non-technical losses using an automation wireless method. The wireless ZigBee technique is proposed and further investigated for communication failure over long distances while solving the problem of stealing electricity. Advance-metering infrastructure (AMI) technique and smart meters are feasible for system integration; that is why they are chosen to be part of this study. The success of the study depends on quality data of the Utility, meaning the more accurate the data, the easier the analysis of outliers. The operation and planning of revenue protection contain a large amount of data that needs to be worked on, so data mining assists in that regard. Then the load profiling method assists in illustrating the variation in demandJelectricalload over a specific time. This is a preliminary investigation using a wireless communication technique as a viable solution in curbing electricity theft. The uniqueness of the proposed ZigBee system is that it recognizes the everyday act of stealing electricity through tempering with the meter box and tapping of the supply.