Research Publications (Engineering and Built Environment)

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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.
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.
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.
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 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.
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.
A D2D communication based lightweight customer side data securing scheme in smart grids
(2022-08-20) Nleya, Bakhe; Khumalo, Phlani
With the emergence of modernized power grids into smart equivalents referred to as smart grids (SGs) the bulk generation, transmission, distribution, and end-user infrastructures must be appropriately long-term planned concurrently with the required privacy and security. Notably, the objectives of modern SGs are to minimize power energy losses through theft or physical dissipation. The embedded device-to-device (D2D) communication technology in 5G networks will enable an affordable fail-safe ICT subsystem platform for the SGs. However, Privacy preservation is necessary for D2D services in SGs. In this paper, we propose an anonymity privacy-preserving, and data aggregation scheme. We carry out both security and performance and obtained theoretical analysis and simulation results the privacy algorithm is effective and at the same time, fewer communication overheads are exchanged.
Data re-sequencing in Smart Grids
(IEEE, 2016-11) Khumalo, Zephaniah Philani; Nleya, Bahke
Currently, legacy electrical power grids are being modernized into Smart Grids. These will in turn play a crucial role in real-time balancing between energy productions versus energy consumption. Each Smart Grids will dedicate an advanced metering infrastructure that facilitates collection, storing as well as analyzing data from smart meters to the authorized parties, and also carrying commands, requests, messages and software updates from the authorized parties to the smart meters. As such, data aggregation as well as unimpeded data relaying is a prerequisite for guaranteeing a large acceptance and deployment of Smart Grids. In this paper we provide an overview framework for analyzing packet re-sequencing within the Smart Grid. We utilize the random shortest path calculation algorithm to select the desired routes from source to a given destination. It is from among these that ultimately multipath (dual path) routing of the Advanced Metering Infrastructure data is carried out, hence resulting in re-sequencing necessities.
Design and modeling of the ANFIS-based MPPT controller for a solar photovoltaic system
(ASME International, 2021-08) Moyo, Ranganai T.; Tabakov, Pavel Y.; Moyo, Sibusiso
Abstract Maximum power point tracking (MPPT) controllers play an important role in improving the efficiency of solar photovoltaic (SPV) modules. These controllers achieve maximum power transfer from PV modules through impedance matching between the PV modules and the load connected. Several MPPT techniques have been proposed for searching the optimal matching between the PV module and load resistance. These techniques vary in complexity, tracking speed, cost, accuracy, sensor, and hardware requirements. This paper presents the design and modeling of the adaptive neuro-fuzzy inference system (ANFIS)-based MPPT controller. The design consists of a PV module, ANFIS reference model, DC–DC boost converter, and the fuzzy logic (FL) power controller for generating the control signal for the converter. The performance of the proposed ANFIS-based MPPT controller is evaluated through simulations in the matlab/simulink environment. The simulation results demonstrated the effectiveness of the proposed technique since the controller can extract the maximum available power for both steady-state and varying weather conditions. Moreover, a comparative study between the proposed ANFIS-based MPPT controller and the commonly used, perturbation and observation (P&O) MPPT technique is presented. The simulation results reveal that the proposed ANFIS-based MPPT controller is more efficient than the P&O method since it shows a better dynamic response with few oscillations about the maximum power point (MPP). In addition, the proposed FL power controller for generating the duty cycle of the DC–DC boost converter also gave satisfying results for MPPT.
Dynamic voltage stability studies using a modified IEEE 30-Bus system
(IEEE, 2016) Oni, Oluwafemi E.; Davidson, Innocent Ewaen; Mbangula, Kamati N. I.
Power System stability is an essential study in the planning and operation of an efficient, economic, reliable and secure electric power system because it encompasses all the facet of power systems operations, from planning, to conceptual design stages of the project as well as during the systems operating life span. This paper presents different scenario of power system stability studies on a modified IEEE 30-bus system which is subjected to different faults conditions. A scenario whereby the longest high voltage alternating current (HVAC) line is replaced with a high voltage direct current (HVDC) line was implemented. The results obtained show that the HVDC line enhances system stability more compared to the contemporary HVAC line. Dynamic analysis using RMS simulation tool was used on DigSILENT PowerFactory.
Energy demand and trading optimization in isolated microgrids
(IEEE, 2020-04-30) Chidzonga, Richard; Gomba, Masimba; Nleya, Bakhe
Future generation 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 achieve optimality in 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 overall demand and response by the cooperative microgrids assist greatly in determining the required resources hence leading to cost effectiveness of the entire system.
Energy optimization for a smart prosumer
(PONTE International Scientific Researches Journal, 2020-04) Chidzonga, Richard F.; Nleya, Bakhe
This paper outlines the optimization of cost of electrical energy consumption for a small microgrid typical of a residential area where each household has renewable generation capability and the daily load is portioned into essential none-interruptible and schedulable or interruptible loads. Dual tariffs exist, for buying and the other for in-feed into the utility grid. The optimization makes appliances scheduling decisions to suit prevailing power availability as well amount of power to sell or procure from the utility depending on availability and prevailing real time pricing. We assume availability of time-variant energy parameters, then formulate a global optimization problem whose solutions leads to quantification of the optimal amount of energy purchased and sold for each of the individual households. When the unrealistic assumption of availability of information is removed from the implementation of the global optimization, an online algorithm that only requires the current values of the time varying supply and demand processes shows by simulation that the distributed algorithm can realise credible scheduling of prosumer household electricity usage. This is imperative as the very requirement of involving the consumer for appliances scheduling defeats the optimization cause as humans are not suitable for such repetitive and mundane tasks.
Energy-aware lightpath routing algorithm for optical transport networks
(TELKOM, 2019-09-01) Gomba, Ndadzibaya Masimba; Nleya, Bakhe; Dewa, Mendon; Mutsvangwa, Andrew; Khumalo, Zephaniah Philani
Current as well as future applications and services are characterized by bandwidth intensiveness and as such are directly driving the need for the deployment as well as operation of backbone networks that optimize on bandwidth provisioning. Since infrastructural hardware equipment requirements are trebling every two years because of continued surging bandwidth demands, the telecommunication industry is also a growing direct contributor to worldwide greenhouse gases (GHG) emissions as well as energy consumption. This is driving necessities to research on more energy efficient networking approaches. A novel optimized energy-aware lightpath routing (OEA-LR) algorithm is herein proposed. It primarily takes into account the effects of physical layer impairments (PLI) since their effects in high capacity translucent optical networks may not be ignored when formulating routing and wavelength assignment (RWA) algorithms. We assume an all-optical network hence connection requests from source to destination are entirely provisioned in the optical domain, thus optical-electrical-optical (OEO) conversions are not utilised. Both analytical and simulation results indicate that the proposed algorithm improves both energy efficiency operation as well as resource utilization of the network. We further conclude on a general observation of reciprocations between energy savings and blocking performance.
Enhancement of solar PV output error under variable irradiation and temperature using an improved regulation strategy
(IEEE, 2022-08-22) Akinyemi, Ayodeji Stephen; Kabeya, Musasa; Davidson, Innocent Ewaen
A Photo-Voltaic Solar System (PVSS) is being operated in Steve Biko campus, Durban University of Technology. The energy generated by the PVSS is time varying, based on the quantity of sunlight and the temperature at which the photovoltaic (PV) cell functions. Consequently, in all situations, it is critical to obtain the full power from the PV array. The monitoring control strategy of Maximum Power Generated (MPG) from the PVSS connected to a Boost Inverter (BI) is presented in this research paper by employing an Improved Incremental Conductance and Integral Regulator (IIC & IR). The outcomes of the simulation indicate that full power can be obtained from the PV array while ensuring a consistent generated voltage under various operating scenarios.
Enhancing the performance of Eskom’s Cahora Bassa HVDC Scheme and Harmonic Distortion Minimization of LCC-HVDC Scheme using the VSC-HVDC link
(MDPI AG, 2022-04-20) Davidson, Innocent Ewean; Oni, Oluwafemi Emmanuel; Aluko, Anuoluwapo; Buraimoh, Elutunji
Cahora Bassa, a thyristor-based High Voltage Direct (HVDC) link, transmits 1920 MW of power from a hydro-power plant in Zambezi River, north of Mozambique, to Apollo Substation in Johannesburg, South Africa. The high degree of harmonics distortion that is transferred into the AC side of the transmission network and the continuous increase in the rate at which commutation failure occurs during systems disturbance are both flaws in the utilization of this HVDC converter technology. AC and DC filters with rugged controllers are often used to minimize this effect but are limited in scope. Modern converter technology, such as the Voltage Source Converter (VSC), was proposed in this study to reduce harmonics content level, increase power transfer capabilities, enhance network stability, and reduce the rate of commutation failure occurrence. This paper, therefore, evaluates the performance analysis of the Cahora Bassa HVDC link and its level of harmonic distortion in the line commutated converters. A proposed method of utilizing VSC HVDC is provided as a suitable solution using three modular-level voltage source converter technology. Current and voltage waveform characteristics during a three-phase short circuits fault were analyzed, and the latest developments in the area of VSC HVDC were discussed. The results show a lower total harmonics distortion with the usage of VSC HVDC converter technology at the inverter station. The continuous occurrence of commutation failure was minimized by implementing a new converter architecture. The network simulation and analysis were carried out using the DIgSILENT PowerFactory engineering software tool.
Exploring the mechanics of city-to-city learning in urban strategic planning: insights from southern Africa
(Elsevier BV, 2020) Moodley, Sogen
The importance of city-to-city learning processes in urban development has been gaining traction over the last two decades, particularly in the global North. Little empirical work has been done however, to critically analyse exactly how knowledge is transferred and the conditions under which these happen in order to facilitate better policy transfer between southern cities and regions. This paper focuses on the experiences of urban planning practitioners and key stakeholders from cities in South Africa, Malawi and Namibia that participated in a mentorship program coordinated by the international United Cities and Local Governments (UCLG). Using this case study, it develops a staged learning model that unpacks in detail, the mechanics of how the learning occurs during the program. In order to inform good practice, key ingredients that contribute to knowledge transfer – in this instance around urban strategic planning – is distilled. The study employed a qualitative approach combining observation, focus group and in-depth interviews with 18 practitioners directly involved in the program. The study shows that effective knowledge transfer requires inter-alia an expertly-facilitated and highly structured program of mutual learning. Most importantly however, the paper argues that the building of trust between the practitioners involved in city-to-city learning is critical for transformative action in cities of the global South.
Green roofs and stormwater runoff quality in the urban landscape in South Africa
(National Research Council Canada, 2021-06-20) Sucheran, Arisha; Sucheran, Reshma
A number of sustainable urban drainage systems (SuDS), such as green roofs, are being developed and implemented in cities around the world to help reduce stormwater runoff and improve stormwater runoff quality. This study compares the water quality of green roofs with that of conventional roofs in the eThekwini region, South Africa. Samples of stormwater runoff from the different green roof systems on the eThekwini Green Roof Pilot Project were collected to test their level of contaminants and pollutants. The tests focused on all physical, aesthetic, chemical, and microbiological determinants pertaining to stormwater runoff. For all tests, the level of contaminants and pollutants were measured against the South African Water Quality Guidelines Volume 7 for Aquatic Ecosystems. The data revealed significant variations in pollutant concentrations between the green roofs and the conventional roof. Moreover, runoff water quality varied across the various roof types, which may indicate that the substrate composition has the greatest impact on green roof performance regarding rainwater quality. Overall, the results suggest that these green roof systems do not have the ability to filter pollutants out of stormwater runoff, but rather increase their levels of concentration.
Guiding principles for grid code compliance of large utility scale renewable power plant intergration onto South Africa's transmission/distribution networks
(IEEE, 2016-11) Sewchurran, Sanjeeth; Davidson, Innocent E.
Renewable energy generation technologies with its short lead times have become an attractive alternative to assist South Africa to solve its energy crisis and hence led to the Government calling upon Independent Power Producer to enter the market. Subsequently, the Integrated Resource Plan 2010 set a target of 17 800 MW (equivalent to 42%) of new electricity generation capacity in the country to be derived from renewable energy sources. The South African Renewable Energy Grid Code was then published in 2010 to assist with safe and technical integration of these plants into the South African grid. Electricity utilities are now faced with the task to understand the code and carry out testing of these renewable power plants in order to certify them grid code compliant. This paper assists by discussing the requirements of the South African Renewable Energy Grid Code Version 2.8 with testing methods to check grid code compliance.
Harmonic distortion of LCC-HVDC and VSC-HVDC link in Eskom's Cahora Bassa HVDC Scheme
(IEEE, 2016-11) Oni, Oluwafemi E.; Davidson, Innocent Ewaen
Cahora Bassa, a thyristors based HVDC link transmits 1,920 MW of power from hydropower plant located in Zambezi river, north of Mozambique to Johannesburg, South Africa. This HVDC converter suffer few deficiency in its high level of harmonics distortion that transferred into its AC side of the transmission network couple with persistence rate of commutation failure. AC and DC filters with rugged controller are often used to minimize this effect but are limited in some aspect. Modern converter technology used for different HVDC links reduces harmonics content level, increases power transfer capabilities, enhances network stability and finally reduced the rate of commutation failure. This paper therefore investigate the level of harmonic distortion in line commutated converter used in Cahora Bassa link and thus proffer a suitable solution with the use of VSC-HVDC link. Current waveform characteristics and latest developments was also addressed. Simulation analysis was carried out using DigSILENT PowerFactory.