MSc. SET Theses and Dissertations

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Toward improving energy security in Kenya via HTLS conductors and load balancing
(Strathmore University, 2024) Mkabane, C. C.
The Industrial and Commercial sectors of the economy are rapidly growing and hence, energy consumption and transmission line loading are also increasing. This explains the major breakdowns related to transmission lines since the initially installed lines are not able to handle the increased energy requirements. Previous studies have been done replacing ACSR with ACCC conductors to reduce thermal line losses. The project aims to replace ACSR with ACCC conductors in short lines, analyze the length of the line in which the ACCC conductor will cease to be beneficial, and analyze the mechanical properties of the line. The Kenyan grid will be analyzed in its present state by performing a load flow analysis and a sag and tension analysis. The short lines will then be replaced by ACCC conductors and the load flow and sag and tension analysis of the new system done. The two systems will then be compared. The length of the line in which the ACCC conductor will no longer be beneficial for application will be determined. The analysis will be performed using Power Factory DigSilent software.
Adoption of Behind-The-Meter Battery Storage Systems for residences in Kenya
(Strathmore University, 2024) Wambugu, A. W.
This research investigates the adoption of Behind-the-Meter Battery Energy Storage Systems (BTM BESS) in Kenyan urban households, focusing on mitigating the challenges posed by unreliable electricity supply, particularly for households engaged in work-from-home (WFH) activities. Electricity reliability challenges in Kenya's densely populated urban areas presents a significant challenge to the growing WFH workforce. While BTM BESS offer a potential solution for reliability, their affordability with grid-charging remains uncertain. The study develops a modified Levelized Cost of Storage (LCOS) model that integrates the WFH Reliability Metric and the WFH Income Value of Lost Load, offering a nuanced understanding of BTM BESS affordability tailored to the needs and economic realities of WFH individuals. Analysis reveals that BTM BESS becomes increasingly affordable as a reliability solution for WFH individuals, particularly those facing frequent outages or whose income is highly dependent on constant electricity access. This research contributes to the discourse on sustainable energy transitions by highlighting the economic and reliability advantages of BTM BESS for urban households in Kenya, proposing policy recommendations to enhance BTM BESS adoption and support the provision of reliable electricity as per Sustainable Development Goal 7 (SDG7).
A 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
Modeling and optimization of renewable energy accessibility in underserved regions: a case of Mashuru area
(Strathmore University, 2024) Mutekhele, D. N.
Underserved regions have problems of inadequate access to energy. These regions are characterized by inadequate or no grid infrastructure, making it difficult to establish centralized energy systems. To address these challenges, various solutions have been undertaken such as the development of decentralized energy systems. Modeling tools are used to simulate energy systems. They, however, do not prioritize decentralized solutions. So far, less focus has been put on the evaluation of decentralized renewable energy modeling tools for promotion of access to energy in underserved regions. There is a demand for modeling tools to aid in the design of these solutions. The objective of this study is to develop, test and validate a renewable energy model that will optimize accessibility in underserved regions. To achieve the objectives of research, this work focused on Mashuru area in Kajiado County. This area has inadequate grid infrastructure and is characterized by a population with low income and poor purchasing power. This research project targeted small-scale farmers, who use diesel pumps to provide energy for irrigation. The study proposes an optimization model for renewable energy systems consisting of photovoltaics, batteries, supercapacitors, and a diesel generator which act as back up, to provide energy for powering pumping systems. Four technologies were considered; solar PV with battery backup, solar PV with super capacitor backup, standalone solar PV system and solar PV system with a generator set backup. It is based on the selection of an optimal PV system, battery, supercapacitor, and generator capacity while minimizing the LCOE. It employed a debt-versus-equity financial model to compute the WACC used for LCOE calculations. The study established that the total load was 1000 MWh. The optimal capacity requirements for various scenarios were; solar PV with battery backup (693.52kW), solar PV with super capacitor backup (679.71kW), standalone solar (668.45kW) and solar PV with genset backup (467.52kW). From the model results, the optimal LCOE was 8.95KES/kWh, 11.67KES/kWh, 14.47KES/kWh and 33.23KES/kWh for PV only, PV plus battery backup, PV plus supercapacitor back up and PV plus genset back up respectively. The model was validated using HOMER simulation tool to compare its performance and ascertain the correctness of the results.
A 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.
A 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.
Energy 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.
Modelling a sustainable electromobility infrastructure
(Strathmore University, 2024) Amiani, D. M.
The global transportation sector is undergoing a significant transformation as societies increasingly seek sustainable alternatives to conventional fossil fuelled. Electricity as an alternative for fossil fuels to power mobility in the wake of green transition has gained prominence. Energy inaccessibility due to inadequate availability of a robust infrastructure with reliable and efficient energy provision has become a drawback towards the transition from petroleum powered to electrified mobility. This study aimed to create a model that will foster the uptake of electromobility by formulating a model equation to determine the infrastructural requirements of establishing a sustainable e-mobility charging infrastructure. The study adopts desktop, descriptive and experimental research designs in sourcing for data and simulation of the model. To this end, Westlands region of Nairobi County was selected as an area with a blend of residential and most sought-after office space with capability for modern e-mobility infrastructure. Results depicted that the current EV infrastructural capacity (charging stations, charging station capacity and area coverage) is not sustainable (SI=2.316 (>0.29)) for the given population, energy demand, and coverage area. This is also the case in the short term (5 years) (SI=4.030 (>0.29)), medium term (10 years) (4.828 (>0.29)) as well as long term (15 years) (5.339 (>0.29)). The findings highlight the inadequacy and inflexibility of the current infrastructure to meet the evolving demands of a growing population, increasing energy demand, casting doubt on the viability of Kenya's e-mobility ecosystem in fostering sustainable transportation solutions. To ensure the continued sustainability of the e-mobility infrastructure, policymakers, government agencies, private sector stakeholders and urban planners should prioritize integrated planning and investment strategies in developing a cohesive framework to address current and future demands of e-mobility ecosystem. Key Words: Energy Access, Electromobility, Energy Transition, Sustainability
Modelling 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.
Modeling carbon emission from cooking fuels in rural communities: a pathway to low-carbon emission
(Strathmore University, 2025) Rono, B. C.
The availability of clean, sustainable cooking fuel remains a fundamental obstacle throughout Kenyan rural areas since traditional biomass fuels like firewood and charcoal control household energy usage patterns. Using these fuels causes significant carbon pollution, deforestation damage, and health risks from indoor air contamination. The transition must establish low-carbon energy alternatives for effective change between environmental responsibility and reasonable cost-effectiveness. This research evaluates carbon emissions across cooking fuel types within Kenyan rural areas while identifying methods to decrease emissions. The analysis uses Microsoft Excel Software to evaluate four energy transition strategies, from Business-As-Usual (BAU) through Liquefied Petroleum Gas (LPG) use and bioethanol and electricity combination to an extensive clean energy implementation. The study presents data-driven emission projections that combine literature research with energy consumption surveys and policy guidelines for different intervention approaches. The KNBS data shows that cooking fuel emissions will increase because of population expansion and the continued use of biomass in the Business-As-Usual context. The complete electrification of cooking equipment offers the most lasting solution against emissions reduction since it effectively surpasses LPG and bioethanol systems. The transition to sustainable cooking needs improvements in infrastructure systems, a solution for affordability, and better policy enforcement. The investigation demonstrates the pressing requirement for government-backed programs, financial resources from the private sector, and active community participation to enhance clean cooking technology adoption rates. Governments should provide financial support for green energy fuels, develop expanded power grid systems, and launch information programs to change public cooking behavior. Implementing such measures will lead rural communities towards sustainable, low-carbon cooking solutions that support countrywide and global climate objectives.
Modelling of municipal solid waste use for steam generation for industrial and hospitality sector
(Strathmore University, 2025) Omare, J. W.
The cumulative demand for steam in the hospitality and industrial sectors has led to rising financial and environmental costs due to the prevalent use of biomass for steam generation. This challenge has intensified by issues such as resource depletion, competition for land with food crops, and the bulky nature of biomass, which complicates energy management. Previous attempts to use Municipal Solid Waste (MSW) as an alternative fuel for steam generation have yielded inconclusive results, underscoring the need for further research to establish its feasibility as a replacement for biomass. This study modeled the use of MSW for steam generation in industrial and hospitality sectors. The main objective of this study was to model transport and treatment processes in MSW steam generation. Secondary data was collected from three zones in Nairobi, an industry setup and a hotel, each characterized by different energy & waste profiles stemming from varied commercial and social activities. The data collected was analyzed using a developed model incorporating governing equations for calorific value calculations, transport, treatment, and the Levelized Cost of Steam (LCOS). Under three scenarios, the calorific values of MSW and biomass (Eucalyptus globulus) were analyzed, revealing that MSW possessed a superior energy density at 23.80 MJ/kg compared to biomass at 17.34–17.43 MJ/kg. Proximate analysis of Nairobi’s MSW highlighted organic waste dominates at 65.4% of the total waste and moisture content was reduced from 19.03% to 15% via drying to enhance combustion efficiency. Also, transportation costs were modeled for two collection points, emphasizing distance-driven variations. The techno-economic framework computed the LCOS by integrating capital and operational expenditures, as well as transport and treatment costs. Results demonstrated the cost-effectiveness of MSW, with LCOS values of 1.48–1.49 Ksh/kg and 2.24–2.32 Ksh/kg for the two companies analyzed respectively. This shows 25–26% reduction over biomass. Scenario analyses confirmed MSW’s resilience to cost escalations, as it maintained lower costs than biomass. Although costs varied non-linearly with transportation and drying, the processes added more operational annually, but the overall LCOS remained economically viable, compared to biomass. MSW reduced feedstock demand by 27% and storage requirements, thereby aligning with Kenya’s waste management and renewable energy goals. The proposed model offered a replicable framework for optimizing MSW utilization in steam generation, emphasizing localized waste characterization and policy cost incentives. Recommendations include advancing waste-to-energy conversion studies, spatial transport optimization, and the integration of social economic factors in future models. These findings supported the adoption of MSW to mitigate production costs, reduce deforestation, and foster sustainable urban energy transitions.
Optimized renewable energy powered irrigation system using mathematical programming: a case study for Kiserian, Kenya
(Strathmore University, 2025) Juma, S.
Energy supply for irrigation in remote areas has been a challenge. Energy is needed to support agricultural activities like pumping water required to enhance crop development and growth in areas that receive less rainfall. There have been efforts to expand the grid for universal access. However, it has been proven to be costly to extend the grid network to remote areas. A suggested solution is to use decentralized systems such as wind and solar. They are affordable, clean sources of energy and readily available. They are affordable, clean sources of energy and readily available. This approach could work well, however, there is insufficiency of data that could help decision makers to settle on the most appropriate solutions. This creates a need for researchers to innovatively develop more data on how solar and wind resources could be optimized for energy applications in agriculture. This study looked at the optimization of solar photovoltaic and wind turbines to pump water for irrigation as a hybrid system that could be utilized at Kiserian, Kajiado county. Tomato crops were used to determine the energy needed to supply water on a hectare piece of land. A hybrid energy system of solar PV and wind turbine was designed using an Equilibrium Optimizer (EO) algorithm and simulated using MATLAB R2024b software. The model was used to perform the net present cost of the integrated system to generate the optimal result. Then the levelized cost of energy was determined to assess the economic performance of hybrid system. The results were compared with standalone solar PV and wind turbines. The study revealed that it was economical for small-scale farmers to power an irrigation system using solar PV as a standalone, and the hybrid of solar PV and wind turbine would work well for large scale farmers. Keywords: Renewable energy system, solar photovoltaic, wind turbine, Equilibrium Optimizer Algorithm, Net Present Cost, Levelized Cost of Energy and Optimization.
Decarbonization of urban road infrastructure using solar street lighting in Kenya: assessing implementation and impact
(Strathmore University, 2025) Mabonga, P. S.
Decarbonizing urban road infrastructure using solar street lighting is a very promising perspective for the sustainable development of Kenya. This dissertation deals with a comprehensive study investigating the implementation and impacts of solar-powered lighting system adoption in urban areas, taking Mombasa City’s southern bypass highway as a case study. The fact that warrants the transition is that the benefits are manifold, such as reduced greenhouse gas emissions, increased energy efficiency, better public safety, and economic savings in running and maintaining lighting systems. However, the potential of solar street lighting has several limitations and assumptions that require empirical research to evaluate its feasibility and effectiveness. The dissertation design is based on a comprehensive literature review to consolidate the current knowledge on solar street lighting, followed by a detailed methodology based on data collection, model development, and data analysis. The Mombasa Southern Bypass case study has helped us understand the local context, considering regulatory frameworks, technological requirements, and socioeconomic factors. The research, by running a qualitative and quantitative investigation about the main technical, economic, and regulatory issues arising from the implementation of solar street lighting, aimed to estimate the impacts that the sustainable infrastructure solution has on urban planning, energy consumption, and environmental quality to orient the definition of the potential advantages and disadvantages for policymakers, urban planners, and other stakeholders in implementing such solutions. The way forward is to gather findings from the outcomes of this research, which aided in developing evidence-based mechanisms to achieve decarbonization and sustainable urban development in Kenya and beyond. The study found that while street lighting infrastructure in Mombasa City is functional, significant improvements are needed, with a predominant reliance on conventional lighting technologies like incandescent and fluorescent lamps. In addition, the study found that solar street lighting is viable in Mombasa, and the irradiation level is sufficient to maintain reliable operation. The study identified several barriers to adopting solar street lighting in Kenya, including high initial costs, insufficient technical expertise, inadequate infrastructure, limited local solar technology availability, and logistical challenges. It also highlights the lack of government incentives, public resistance, and financing issues as significant obstacles to widespread adoption. Further, the study revealed that adopting solar street lighting in urban areas, including Mombasa City, is expected to reduce energy consumption and carbon emissions. The study recommends transitioning to solar-powered lighting technologies in Mombasa City and the rest of the country to reduce energy consumption and emissions. It suggests integrating sustainable lighting into urban planning, investing in local solar technology adoption, and developing financing mechanisms to overcome financial barriers. Additionally, it emphasizes strengthening local capacity through training, streamlining approval processes, and increasing awareness campaigns to address public resistance and ensure the successful implementation of solar street lighting projects.
Renewable Energy-Based Hybrid Power Systems for off-grid Base Transceiver Stations - a case study of BTS site in Kajiado County
(Strathmore University, 2025) Kiarie, A. B
This study explores the technical and economic feasibility of deploying a renewable hybrid power system comprising solar photovoltaic (PV), battery storage, and hydrogen fuel cells for powering off-grid Base Transceiver Stations (BTS) in Kenya. Motivated by the environmental impact and high operational costs of diesel generators currently used as backup power sources in telecommunications infrastructure, the research proposes an alternative energy solution aligned with Kenya’s carbon reduction targets under the Nationally Determined Contributions (NDC). A case study of a BTS site in Kajiado County was used to evaluate the proposed hybrid configuration. The system was modelled and simulated using MATLAB/Simulink to assess power flow, fuel cell activation, battery state of charge, and solar irradiance behaviour. HOMER software was used for system optimization and economic analysis, incorporating real load data, solar resource inputs, and cost parameters. Results indicate that the hybrid system meets energy demands reliably, with solar PV supplying most of the energy, batteries stabilizing supply, and the proton exchange membrane fuel cell (PEMFC) acting as a backup. The proposed system achieves an annual electricity output of approximately 67.43 MWh, with a Levelized Cost of Electricity (LCOE) of $0.351/kWh and a Net Present Cost (NPC) of $87,404 lower than the $102,253 NPC of a diesel-based system. Additionally, the system significantly reduces carbon emissions and fuel dependency. The findings demonstrate that integrating hydrogen fuel cells with solar and battery systems can provide a sustainable, cost-effective power solution for off-grid telecom sites. The study supports broader adoption of clean energy in Kenya’s telecommunications sector and contributes to climate action and energy access goals.
Assessment of sustainable electricity generation scenarios in Burundi using multi-criteria approaches
(Strathmore University, 2025) Igiraneza, N. L.
With an 11% electrification rate, Burundi is one of the countries in the sub-Saharan region still facing significant energy access challenges in the region. This has considerably impacted the economic development, energy security and technical advancement of the country. The country primarily relies on hydroelectric power, with 49MW installed out of a potential 1700MW, as well as diesel thermal plants, solar, biomass, peat, firewood, coal, bagasse, although on a smaller scale. Due to a poor energy mix and inadequate maintenance of existing hydro infrastructure, technical issues, like insufficient capacity, supply disruptions lead to low-quality electrical supply. Moreover, the increasing reliance on traditional biomass has led to deforestation, and environmental degradation. There have been nevertheless attempted initiatives to close the energy supply and demand imbalance, while promoting renewable energy integration. Burundi is boosting energy generation through public and private initiatives, including rehabilitating existing hydropower infrastructure, developing rural electrification with mini-hydro, solar, and wind power, extending electric networks and building regional plants with neighbors. Feasibility studies for solar and wind power investments are also in progress. Despite this, there is no data and structured modeling tool available to support evidence-based decisions about these investments. This study aimed to assess the pathways to electricity generation by developing and testing an energy planning tool, that integrated available resources and the future energy demand in Burundi, to close the existing gap between supply and demand. It will serve as a resource for the relevant stakeholders as they tackle the issues of energy access, affordability, security, decarbonization and decentralization, and support potential investors in their decision making.
A Model for estimating the state of health of retired lithium-ion EV batteries based on machine learning
(Strathmore University, 2025) Rugami, V.
The electric vehicle market is growing rapidly and with it comes subsequent growth in the number of lithium-ion batteries that reach end of life in electric vehicle applications. Instead of being discarded in landfills, these batteries can be used in other applications such as energy storage since they still retain about 70% to 80% of their original capacity. This is known as battery repurposing, and it helps to manage battery waste. To repurpose batteries, their state of health must be tested to determine if they are adequately safe and reliable to use in second life applications. Current testing methods are time-consuming. Long testing times inhibit the scalability of repurposing operations to match the rapidly increasing number of electric vehicles, hence retired electric vehicle batteries. In this study, a machine learning model was developed to determine the SOH of used batteries. The model was based on quantum particle swarm optimization-support vector regression (QPSO-SVR) and used partial discharge data from differential capacity curves to estimate SOH. It was trained on data obtained from cycling used battery cells. The model achieved best MAE of 0.6139, RMSE of 0.7875, and R2 of 0.8481.

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