MSc. SET Theses and Dissertations (2024)
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- ItemA Model for assessing digital technology readiness in mini grids(Strathmore University, 2024) Koskei, K. K.In Sub-Saharan Africa, approximately 0.6 billion people lack access to electricity due to challenges with the centralized grid. Mini grids, seen as a solution for rural electrification, face sustainability issues, including technical limitations with renewable energy, outdated monitoring methods, and scalability matters. To address these challenges and strengthen their value proposition, the integration of current and emerging Digital Technologies, such as AI, IoT, Blockchain, and Cybersecurity, is recommended. This study aimed to address a critical gap in the current understanding of Digital Technology Readiness (DTR) in the context of mini grids in Kenya. Recognizing the necessity of a DTR assessment model tailored to end user preferences and the local environment, this research employed a combination of quantitative methods, inferential analysis, and fuzzy synthetic evaluation (FSE). The research methodology embraced the design thinking process and descriptive analysis to develop the DTR assessment model. Data collection involved the use of online questionnaires, employing purposive and snowball sampling techniques. These instruments sought insights from relevant stakeholders in the mini grid industry. Subsequently, surveys were conducted to validate and test the DTR assessment model, ensuring its validity and efficacy. The study findings, based on responses from diverse industry professionals, were instrumental in identifying 15 critical indicators that collectively contribute to digital technology readiness in the mini grids. Through factor analysis, these indicators were categorized into five main dimensions: Digital Literacy (DL), Digital Technology Usefulness (DTU), Digital Technology Preparedness (DTP), Digital Transformation (DT), and Digital Infrastructure Availability (DIA). The critical index values of these dimensions, in descending order, were as follows: DL (4.443), DTU (4.362), DTP (3.839), DT (3.642), and DIA (3.5). These critical index values serve as a valuable guide, emphasizing the key areas of focus in digital technology readiness. The output of this research was a DTR assessment model for mini grids. The model was tested by mini grid stakeholders and it was found to be valid and effective. The model will be used by the stakeholders to measure DT readiness in mini grids. This will aid in strategic decision-making and enhancing the industry's adaptability to the challenges and opportunities presented by Industry 4.0.
- ItemModelling cooking energy demand for E-Cooking transition(Strathmore University, 2024) Ogalo. S. A.As per estimates, 92% of rural households still use a form of traditional biomass as their preferred cooking fuel. Children especially those under 5 years, suffer from respiratory infections due to the solid fuel combustion. Kenyan women as well as young children are especially exposed to indoor air pollution, which is connected with more than 15,000 unnecessary deaths annually. The Kenyan government and other non-governmental agencies have been on the forefront to promote adoption of electric cooking through various policies and set targets. Considering population expansion in the rural areas and greater electrification percentages, the expectation is that electric energy consumption would increase. This study employs the LEAP modelling tool to forecast rural residential cooking energy demand from 2020 to 2040. Results indicate that traditional biomass, continues to dominate cooking practices, contributing to indoor air pollution. However, alternative scenarios demonstrate the potential for accelerated shifts toward cleaner cooking technologies. Analysis of household surveys reveals a prevalent reliance on traditional biomass fuels such as fuelwood and charcoal, with minimal usage of electric cooking technologies. The LEAP modelling exercise simulates three scenarios: Business As Usual (BAU), Moderate Accelerated Shift (MAS), and High Accelerated Shift (HAS). Under the BAU scenario, traditional cooking methods persist, resulting in a steady increase in total energy demand, reaching 1,937.98 million Gigajoules by 2040. In contrast, the MAS scenario projects a moderate shift towards cleaner technologies, with total energy demand reaching 1,681.9 million Gigajoules by 2040. Notably, the HAS scenario envisions a proactive transition, with rapid adoption of electric cooking and other advanced technologies. This scenario leads to a significant reduction in traditional cooking methods, resulting in a 17% decrease in total energy demand by 2040. The findings highlight the importance of targeted interventions to promote the adoption of electric cooking and other clean energy technologies in rural Kenya. Keywords: LEAP model; clean energy; electric cooking fuel; sustainability; scenario analysis; electricity; fuel switching.
- ItemA Model for predicting greenhouse gas emissions from motorcycles in Kenya(Strathmore University, 2024) Cheruiyot, L. C.In Kenya, inefficient public transport systems coupled with rough terrains have made motorcycles the most preferred means of transport. The transport sector is a leading emitter of greenhouse gases, the main driver of global climate change. This is due to the reliance on fossil fuels which require Internal Combustion Engines to operate. The threat posed by climate change and variability has fueled the ongoing energy transition from fossil fuels to green technologies through Emobility. Motorcycles have been described as low-hanging fruit in the E-mobility transition from fuel-based engines to electric-powered motors. However, this transition has shown little progress due to fewer and inadequate models to inform E-mobility policy and investment decisions. This study sought to develop a model for calculating GHG emissions from conventional and electric motorcycles under different scenarios. The scenarios were based on traffic conditions and engine efficiency. The study also aimed to analyze existing ICE and electric two-wheeler technologies in Kenya. A descriptive and experimental research design was adopted for the study. Primary data was collected using a structured questionnaire embedded in the Kobo Toolbox and was administered to motorcycle operators in Nairobi and Machakos counties. Secondary data was also collected from the NTSA database. The R-programming tool was used for data analysis and simulation of GHG emissions under different scenarios. The model was validated using experimental results to increase confidence in the findings. The study results provided comprehensive insights into the determinants of greenhouse gas emissions from both conventional Internal Combustion Engine (ICE) and electric motorcycles. Through an analysis of rider demographics, and electric and conventional motorcycle characteristics, the study revealed the multifaceted factors that contributed to the environmental impact of motorcycles. The specifics of electric motorcycle technologies, including battery characteristics, charging habits, and daily travel distances, were explored, offering valuable insights into the state of electric mobility in the country. Additionally, the study developed and applied a General Additive Model (GAM) for predicting motorcycle emissions, yielding high predictive accuracy and significant predictors. The model underscored the influence of fuel type and temporal trends on emissions, emphasizing the importance of considering both technological and temporal factors in policy formulation. Projection of emissions to 2045 revealed an alarming exponential increase, necessitating urgent intervention. Keywords: Predictive model, GHG emissions, electric two-wheelers
- ItemA Framework for sizing solar PV systems adaptable to off grid areas(Strathmore University, 2024) Nyangoka, I. K.Solar PV sizing is the process of determining the quantity and capacity of solar PV system components to meet a given energy demand. This process is needed to ensure that the components are not undersized resulting in insufficient energy or oversized increasing the system cost. There are several solar PV sizing frameworks currently in use in the market such as intuitive, numerical, and analytical frameworks. However, these frameworks have neglected some key adaptability factors unique to off-grid areas such as the ability of the household to pay and the type of roofing structure. This neglect has seen development of solar PV systems that are beyond the budget of most households in off-grid areas and with specifications that technically inhibit their effective use in the setup. Therefore, for enhanced adaptability, there is need to develop a new solar PV sizing framework that considers the unique adaptability factors of off grid areas. This study identified these unique adaptability factors and investigated how they influence the size of a solar PV system. Through the modification of the exiting numerical sizing framework, these adaptability factors were integrated in the sizing process within the context of this study. It was established that by integrating these factors, the resultant PV systems were more adaptable to off-grid areas in terms of cost, mobility, durability and reliability.
- ItemEnergy supply optimization of the microgrids. A case of Wasini Island(Strathmore University, 2024) Chiro, J. K.The energy transition topic from fossil fuel to non-fossil fuel and non-energy efficient appliances to energy efficient appliances has been gaining momentum since the realization that human socio-economic activities form the major catalyst to climate change. It is therefore clear that conventional power generation sources can hold rapid growth of technological innovations that are putting more pressure on the existing regimes. The pressures put on existing regimes have resulted to innovations of microgrids that uses variable power generation sources from solar and wind to cushion rural communities who are likely to defer their electricity connection due to the rush of providing charging stations for plug in electric hybrid vehicle and EV, also use of cleaning cooking relying on the National grid which has a reserve of only 1100MW. This study looked at the essence of reliable and sustainable microgrids for rural areas such as the case study area. The island of Mkwiro - Wasini is not connected to the national electricity grid and its future access to electricity cannot be immediate. The study identifies multisource hybrid power supply systems that represent the use of renewable technology. In this study wind turbine generators, solar photovoltaic panels, tidal wave energy converters and storage batteries were used to build a block chain microgrid that is optimal based on the performance criteria in terms of cost and reliability. In this study, an energy supply model was designed and simulated using MATLAB 2016a as platform for particle swarm optimization (PSO) algorithm. The algorithm was simulated to generate an annualized system cost and energy index reliability of non-dominated solutions. Three energy supply models were designed to find the best configurations using particle swarm optimization technique. The intermittent nature of wind speed and solar insolation together with random load variation, a time series models were adopted to reflect the stochastic nature. A robustness and reliability test was conducted to determine the impacts of intermittent sources in the microgrid universal performance. Keywords: Energy Reliability, Microgrids, Particle swarm Optimization, wind generators, solar photovoltaic, tidal wave energy converters, annualized system cost and energy index reliability.