Pub Date : 2026-02-06DOI: 10.23919/SAIEE.2026.11373453
{"title":"Notes for authors","authors":"","doi":"10.23919/SAIEE.2026.11373453","DOIUrl":"https://doi.org/10.23919/SAIEE.2026.11373453","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"117 1","pages":"31-31"},"PeriodicalIF":0.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-06DOI: 10.23919/SAIEE.2026.11373472
Franck C. Mushid;Mohamed F. Khan
Energy storage plays a pivotal role in integrating renewable energy sources into low-voltage (LV) networks, especially in South Africa, where electricity grids are plagued by challenges such as reliability issues, frequent load-shedding, voltage instability, and aging infrastructure. This paper presents a comprehensive mathematical framework for optimizing the sizing of battery energy storage systems (BESS) in South African LV networks. The model focuses on minimizing the total cost of ownership (TCO) by balancing the trade-offs between capital investments, operational expenses, and lifecycle costs of energy storage systems. Additionally, the study aims to enhance grid stability by mitigating voltage fluctuations, reducing peak loads, and improving frequency regulation, all of which are critical for ensuring the resilience of the power network. By enabling smoother integration of intermittent renewable energy sources, particularly solar photovoltaic (PV), the model also seeks to maximize renewable energy utilization by minimizing energy curtailment and storing surplus energy for later use. Furthermore, the optimized BESS configuration helps reduce peak grid imports by discharging stored energy during periods of high demand, thus decreasing reliance on centralized generation and alleviating the impacts of load-shedding. Using mixed-integer linear programming (MILP) and real-world data on energy demand and renewable generation profiles, the study reveals that optimal BESS sizing can reduce the total cost of ownership by up to 25%, curtail renewable energy wastage by 15%, and lower peak grid imports by 30% These findings provide actionable insights for policymakers, energy planners, and stakeholders, emphasizing the critical role of BESS in transforming South Africa's LV networks into more resilient, sustainable, and economically efficient systems while addressing growing energy demands and renewable integration challenges.
{"title":"Analytical model for optimal energy storage sizing in low voltage networks in South Africa","authors":"Franck C. Mushid;Mohamed F. Khan","doi":"10.23919/SAIEE.2026.11373472","DOIUrl":"https://doi.org/10.23919/SAIEE.2026.11373472","url":null,"abstract":"Energy storage plays a pivotal role in integrating renewable energy sources into low-voltage (LV) networks, especially in South Africa, where electricity grids are plagued by challenges such as reliability issues, frequent load-shedding, voltage instability, and aging infrastructure. This paper presents a comprehensive mathematical framework for optimizing the sizing of battery energy storage systems (BESS) in South African LV networks. The model focuses on minimizing the total cost of ownership (TCO) by balancing the trade-offs between capital investments, operational expenses, and lifecycle costs of energy storage systems. Additionally, the study aims to enhance grid stability by mitigating voltage fluctuations, reducing peak loads, and improving frequency regulation, all of which are critical for ensuring the resilience of the power network. By enabling smoother integration of intermittent renewable energy sources, particularly solar photovoltaic (PV), the model also seeks to maximize renewable energy utilization by minimizing energy curtailment and storing surplus energy for later use. Furthermore, the optimized BESS configuration helps reduce peak grid imports by discharging stored energy during periods of high demand, thus decreasing reliance on centralized generation and alleviating the impacts of load-shedding. Using mixed-integer linear programming (MILP) and real-world data on energy demand and renewable generation profiles, the study reveals that optimal BESS sizing can reduce the total cost of ownership by up to 25%, curtail renewable energy wastage by 15%, and lower peak grid imports by 30% These findings provide actionable insights for policymakers, energy planners, and stakeholders, emphasizing the critical role of BESS in transforming South Africa's LV networks into more resilient, sustainable, and economically efficient systems while addressing growing energy demands and renewable integration challenges.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"117 1","pages":"13-22"},"PeriodicalIF":0.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373472","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-06DOI: 10.23919/SAIEE.2026.11373467
Fatma Rouissi;A. J. Han Vinck
This paper introduces a Binary Symmetric Channel (BSC) model, which leads to a simple and practical representation for channels corrupted by the Middleton Class-A impulse noise, such as Powerline communication channels. The proposed BSC channel is based on a variable transition probability according to a Poisson distribution. The average transition probability, which provides insight into the error rate, as well as the capacity bounds for this channel are analyzed in all cases of informed and non-informed transmitter and/or receiver. Particularly, an achievable transmission rate is determined in case of informed transmitter by proposing a suboptimum solution that involves employing a variable transmitted energy, proportional to the known noise variance. Analytical formulation of the achievable rate and simulation results in case of a binary Frequency Shift Keying communication system allow to conclude that the channel state information at the receiver side is helpful when the transmitter is non-informed and uses a fixed transmitted energy. However, it no longer contributes to significant performance enhancement when the transmitter is informed.
{"title":"Optimizing transmission rate in BSC model-based Middleton Class-A noise impaired channel with transceiver side information","authors":"Fatma Rouissi;A. J. Han Vinck","doi":"10.23919/SAIEE.2026.11373467","DOIUrl":"https://doi.org/10.23919/SAIEE.2026.11373467","url":null,"abstract":"This paper introduces a Binary Symmetric Channel (BSC) model, which leads to a simple and practical representation for channels corrupted by the Middleton Class-A impulse noise, such as Powerline communication channels. The proposed BSC channel is based on a variable transition probability according to a Poisson distribution. The average transition probability, which provides insight into the error rate, as well as the capacity bounds for this channel are analyzed in all cases of informed and non-informed transmitter and/or receiver. Particularly, an achievable transmission rate is determined in case of informed transmitter by proposing a suboptimum solution that involves employing a variable transmitted energy, proportional to the known noise variance. Analytical formulation of the achievable rate and simulation results in case of a binary Frequency Shift Keying communication system allow to conclude that the channel state information at the receiver side is helpful when the transmitter is non-informed and uses a fixed transmitted energy. However, it no longer contributes to significant performance enhancement when the transmitter is informed.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"117 1","pages":"23-30"},"PeriodicalIF":0.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although several RFID standards for container logistics exist, few address the specific challenges of testing RFID tags in real-world environments where containers are subjected to metallic interference, varying temperatures, and humidity levels. Previous research has primarily focused on RFID tag performance in laboratory settings or general supply chain applications. However, comprehensive test systems tailored to evaluate the performance of RFID tags in diverse and extreme logistical conditions, such as those encountered during container transportation, are lacking. This study addresses this gap by proposing a container electronic tag testing system that combines advanced radio frequency analysis with edge computing and real-time field tests. Our approach provides a novel solution for evaluating RFID tag performance under a wide range of environmental factors, offering significant improvements in the efficiency and accuracy of container tracking in real-world logistics.
{"title":"Container electronic tag test system design and experimental method research","authors":"Shibo Xu;Wensheng Cao;Jichun Li;Bencheng Luo;Jing Wang;Yongming Zhang","doi":"10.23919/SAIEE.2026.11373471","DOIUrl":"https://doi.org/10.23919/SAIEE.2026.11373471","url":null,"abstract":"Although several RFID standards for container logistics exist, few address the specific challenges of testing RFID tags in real-world environments where containers are subjected to metallic interference, varying temperatures, and humidity levels. Previous research has primarily focused on RFID tag performance in laboratory settings or general supply chain applications. However, comprehensive test systems tailored to evaluate the performance of RFID tags in diverse and extreme logistical conditions, such as those encountered during container transportation, are lacking. This study addresses this gap by proposing a container electronic tag testing system that combines advanced radio frequency analysis with edge computing and real-time field tests. Our approach provides a novel solution for evaluating RFID tag performance under a wide range of environmental factors, offering significant improvements in the efficiency and accuracy of container tracking in real-world logistics.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"117 1","pages":"4-12"},"PeriodicalIF":0.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373471","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-06DOI: 10.23919/SAIEE.2026.11373476
{"title":"Editors and reviewers","authors":"","doi":"10.23919/SAIEE.2026.11373476","DOIUrl":"https://doi.org/10.23919/SAIEE.2026.11373476","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"117 1","pages":"2-2"},"PeriodicalIF":0.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11373476","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146122800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-18DOI: 10.23919/SAIEE.2025.11129189
{"title":"Editors and reviewers","authors":"","doi":"10.23919/SAIEE.2025.11129189","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129189","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"138-138"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-18DOI: 10.23919/SAIEE.2025.11129187
{"title":"Notes for authors","authors":"","doi":"10.23919/SAIEE.2025.11129187","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129187","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"169-169"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-18DOI: 10.23919/SAIEE.2025.11129188
Simphiwe D. Mtanti;Getnet B. Fanta
Technology transfer is the process of moving technology for use and understanding from one organisation to another for the technology recipient to achieve and implement technology developments and innovations. The technology transfer process is a complex, volatile and iterative one, which requires the flow of information and knowledge between the transferor and the transferee. This qualitative research aims to identify and investigate barriers to the technology transfer of the electronic train control projects undertaken by a South African freight rail operator (FRO) to upgrade its train control systems on several pilot sites. Ten staff members involved in the FRO's project management, maintenance, operations and training functions were interviewed. They have worked or are working on the various installed electronic train control systems. The thematic analysis findings revealed that the FRO is not equipped to exploit and further develop the technology. The barriers that contribute to this include the loss of vital skills internally, the project management of these technology transfer projects and the lack of flexibility of the technology regarding the local conditions and requirements of the FRO. The broadly analysed impact of the loss of skills in freight rail operations resulted in skills retention, adding to the initially proposed research model as a factor that contributes to the technology transfer process alongside learning, the transferor and transferee environment, language and procurement. Including a technology transfer office (internally or externally) could mitigate most of the identified barriers.
{"title":"An investigation into the technology transfer barriers of the electronic train control systems installed on the South African railway network — A study into SA's freight rail operator","authors":"Simphiwe D. Mtanti;Getnet B. Fanta","doi":"10.23919/SAIEE.2025.11129188","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129188","url":null,"abstract":"Technology transfer is the process of moving technology for use and understanding from one organisation to another for the technology recipient to achieve and implement technology developments and innovations. The technology transfer process is a complex, volatile and iterative one, which requires the flow of information and knowledge between the transferor and the transferee. This qualitative research aims to identify and investigate barriers to the technology transfer of the electronic train control projects undertaken by a South African freight rail operator (FRO) to upgrade its train control systems on several pilot sites. Ten staff members involved in the FRO's project management, maintenance, operations and training functions were interviewed. They have worked or are working on the various installed electronic train control systems. The thematic analysis findings revealed that the FRO is not equipped to exploit and further develop the technology. The barriers that contribute to this include the loss of vital skills internally, the project management of these technology transfer projects and the lack of flexibility of the technology regarding the local conditions and requirements of the FRO. The broadly analysed impact of the loss of skills in freight rail operations resulted in skills retention, adding to the initially proposed research model as a factor that contributes to the technology transfer process alongside learning, the transferor and transferee environment, language and procurement. Including a technology transfer office (internally or externally) could mitigate most of the identified barriers.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"140-149"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electricity is vital for social-economic growth and development. However, over 80% of rural dwellers in Uganda do not have access to it due to the absence of the national electricity grid. Most rural inhabitants use biomass to meet their energy needs using primitive conversion devices, e.g., the 3-stone stoves. They are mainly agricultural and generate a lot of waste, whose disposal is usually open dumping and burning. Such practices lead to environmental concerns and limited economic opportunities. This research aimed to address energy poverty and waste management in off-grid Ugandan communities. The study focused on solar photovoltaic (PV)-biogas hybrid microgrids as a potential solution, given the abundance of solar and bio-waste, particularly animal dung. Field surveys were conducted in Mubende District to gather data on energy usage, appliances, and demographics. Technical simulations and financial analyses were performed for different energy supply scenarios. The results indicated that the solar PV-biogas hybrid system was financially viable, with positive internal rate of return, net present value, and return on investment, whereas solar PV only was not. A pilot project was successfully implemented in one community with seven end users and has been operating since April 2024. The feedback from the end users is full of praise and excitement, and many more users wish to be connected. The study concluded that solar PV-biogas hybrid microgrids can be a valuable solution for providing energy access to off-grid communities in Uganda. Scaling up such systems is recommended to address the energy needs of such areas.
{"title":"Development of a solar photovoltaic-biogas hybrid microgrid for off-grid rural communities in Uganda","authors":"Emmanuel Wokulira Miyingo;David Sunday Tusubira;Roseline Nyongarwizi Akol;Sheila N. Mugala;Davis Kayiza Kawooya","doi":"10.23919/SAIEE.2025.11129186","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129186","url":null,"abstract":"Electricity is vital for social-economic growth and development. However, over 80% of rural dwellers in Uganda do not have access to it due to the absence of the national electricity grid. Most rural inhabitants use biomass to meet their energy needs using primitive conversion devices, e.g., the 3-stone stoves. They are mainly agricultural and generate a lot of waste, whose disposal is usually open dumping and burning. Such practices lead to environmental concerns and limited economic opportunities. This research aimed to address energy poverty and waste management in off-grid Ugandan communities. The study focused on solar photovoltaic (PV)-biogas hybrid microgrids as a potential solution, given the abundance of solar and bio-waste, particularly animal dung. Field surveys were conducted in Mubende District to gather data on energy usage, appliances, and demographics. Technical simulations and financial analyses were performed for different energy supply scenarios. The results indicated that the solar PV-biogas hybrid system was financially viable, with positive internal rate of return, net present value, and return on investment, whereas solar PV only was not. A pilot project was successfully implemented in one community with seven end users and has been operating since April 2024. The feedback from the end users is full of praise and excitement, and many more users wish to be connected. The study concluded that solar PV-biogas hybrid microgrids can be a valuable solution for providing energy access to off-grid communities in Uganda. Scaling up such systems is recommended to address the energy needs of such areas.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"150-159"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-18DOI: 10.23919/SAIEE.2025.11129185
Malcolm Sande;Giscard Binini
Cell-free massive multiple-input-multiple-output (MIMO) is a technique that couples the cell-free network architecture and massive antenna arrays. In cell-free massive MIMO, multiple access points (APs) are collocated to serve fewer user equipment (UEs), which results in a system with more APs than UEs. To achieve optimum transmission performance, massive MIMO requires knowledge of accurate channel state information (CSI). However, the conventional method of CSI estimation, based on minimum mean square error, suffers from high computational complexity, pilot contamination, and noise interference, which degrade the performance of the system. In this paper, we propose a deep learning-based channel estimation approach that makes use of a deep neural network to provide a scalable and efficient channel estimation scheme. Simulation results showed that the proposed scheme consistently outperformed conventional cell-free massive MIMO, small cell network, and cellular massive MIMO architectures.
{"title":"A deep learning-based channel estimation scheme for cell-free massive MIMO systems","authors":"Malcolm Sande;Giscard Binini","doi":"10.23919/SAIEE.2025.11129185","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129185","url":null,"abstract":"Cell-free massive multiple-input-multiple-output (MIMO) is a technique that couples the cell-free network architecture and massive antenna arrays. In cell-free massive MIMO, multiple access points (APs) are collocated to serve fewer user equipment (UEs), which results in a system with more APs than UEs. To achieve optimum transmission performance, massive MIMO requires knowledge of accurate channel state information (CSI). However, the conventional method of CSI estimation, based on minimum mean square error, suffers from high computational complexity, pilot contamination, and noise interference, which degrade the performance of the system. In this paper, we propose a deep learning-based channel estimation approach that makes use of a deep neural network to provide a scalable and efficient channel estimation scheme. Simulation results showed that the proposed scheme consistently outperformed conventional cell-free massive MIMO, small cell network, and cellular massive MIMO architectures.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"160-168"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129185","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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