In recent years, several factors such as environmental pollution, declining fossil fuel supplies, and product price volatility have led to most countries investing in renewable energy sources. In particular, the development of photovoltaic (PV) microgrids, which can be standalone, off-grid connected or grid-connected, is seen as one of the most viable solutions that could help developing countries such as Rwanda to minimize problems related to energy shortage. The country’s current electrification rate is estimated to be 59.7%, and hydropower remains Rwanda’s primary source of energy (with over 43.8% of its total energy supplies) despite advances in solar technology. In order to provide affordable electricity to low-income households, the government of Rwanda has pledged to achieve 48% of its overal electrification goals from off-grid solar systems by 2024. In this paper, we develop a cost-effective power generation model for a solar PV system to power households in rural areas in Rwanda at a reduced cost. A performance comparison between a single household and a microgrid PV system is conducted by developing efficient and low-cost off-grid PV systems. The battery model for these two systems is 1.6 kWh daily load with 0.30 kW peak load for a single household and 193.05 kWh/day with 20.64 kW peak load for an off-grid PV microgrid. The hybrid optimization model for electric renewable (HOMER) software is used to determine the system size and its life cycle cost including the levelized cost of energy (LCOE) and net present cost (NPC) for each of these power generation models. The analysis shows that the optimal system’s NPC, LCOE, electricity production, and operating cost are estimated to 1,166,898.0 USD, 1.28 (USD/kWh), 221, and 715.0 (kWh per year, 37,965.91 (USD per year), respectively, for microgrid and 9284.4(USD), 1.23 (USD/kWh), and 2426.0 (kWh per year, 428.08 (USD per year), respectively, for a single household (standalone). The LCOE of a standalone PV system of an independent household was found to be cost-effective compared with a microgrid PV system that supplies electricity to a rural community in Rwanda.

Rwanda is an East African Community (EAC) nation with rapid and remarkable past development in different sectors and still with the ambitious targets and plans to be achieved in the coming years ahead. The government plans universal electricity access by 2024 with 52% grid connection and 48% off-grid connections. In the transport sector, the concept of electric vehicles has been initiated and started in order to contribute to the UN Paris agreement and decrease the reliance of the transport sector on gaseous fuels which are one source of air pollutants leading to climate change, premature deaths, and morbidity associated with poor air quality. With higher electricity demand than the generation of the Rwandan power grid, different energy strategies are being developed with the overall objective to achieve the targeted universal energy access. In order to overcome the aforementioned issue, this paper proposes an integration of solar PV microgrids for the satisfaction of electric vehicle (EV) technology in Rwanda. Using HOMER Grid software, a managed EV charging station is simulated to a grid connected solar PV microgrid with storage in order to assess the economic impact. The results show that the proposed technology can lower the levelized cost (LCOE) of electricity by 139.7%. This study can contribute to further research developments in either different perspectives related to the integration of distributed energy resources (DERs) with electric vehicles or studies related to affordable and environment-energy systems.

Despite remarkable economic growth and development in recent decades, Rwanda has been still facing energy crises and challenges. Although the country has considerable energy assets, less than 10% is utilized for its local electricity needs. Currently, national installed generation capacity is estimated at 221 MW, for a population around 12 million, and electricity access is estimated at 51% (37% grid and 14% off-grid networks). About half the population is without electricity access while the grid-connected users face high electricity tariffs and frequent power outages (blackouts). The national grid itself is also experiencing high losses. This paper used the HOMER software for modeling the optimal, sustainable, reliable, and affordable photovoltaic solar technologies as energy solutions for all (off-grid and on-grid users) in Rwanda. The selection and recommendation of a suitable photovoltaic (PV) solar technology depend on its annual electricity production capacity, electrical load, renewable energy penetration percentage, economic viability, feasibility, affordability, carbon footprint, and greenhouse gas emission level for climate change considerations towards a clean and greener future. The results show that the least cost of energy (LCOE) for electricity production by each of the solar PV systems with storage, PV-grid-connected household, and PV-grid connection with storage was 67.5%, 56.8%, and 33.9%, respectively, lower than the normal electricity tariff in Rwanda. The PV systems with storage proposed in this paper could be effective in increasing national energy resource exploitation, providing affordable and reliable energy access to all citizens.

The energy sector of todays Rwanda has made a remarkable growth to some extent in recent years. Although Rwanda has natural energy resources (e.g., hydro, solar, and methane gas, etc.), the country currently has an installed electricity generation capacity of only 226.7MW from its 45 power plants for a population of about 13 million in 2021. The current national rate of electrification in Rwanda is estimated to 54.5 (i.e.; 39.7 grid-connected and 14.8 off-grid connected systems). This clearly demonstrates that having access to electricity is still a challenge to numerous people not to mention some blackout-related problems. With the ambition of having electricity for all, concentrated solar power (CSP) and photovoltaic (PV) systems are regarded as solutions to the lack of electricity. The production of CSP has still not been seriously considered in Rwanda, even though the technology has attracted significant global attention. Heavy usage of conventional power has led to the depletion of fossil fuels. At the same time, it has highlighted its unfriendly relationship with the environment because of carbon dioxide (CO₂) emission, which is a major cause of global warming. Solar power is another source of electricity that has the potential to generate electricity in Rwanda. Firstly, this paper summarizes the present status of CSP and PV systems in Rwanda. Secondly, we conducted a technoeconomic analysis for CSP and PV systems by considering their strengths, weaknesses, opportunities, and threats (SWOT). The input data of the SWOT analysis were obtained from relevant shareholders from the government, power producers, minigrid, off-grid, and private companies in Rwanda. Lastly, the technical and economical feasibilities of CSP and PV microgrid systems in off-grid areas of Rwanda were conducted using the system advisor model (SAM). The simulation results indicate that the off-grid PV microgrid system for the rural community is the most cost-effective because of its low net present cost (NPC). According to the past literature, the outcomes of this paper through the SWOT analyses and the results obtained from the SAM model, both the CSP and PV systems could undoubtedly play a vital role in Rwandas rural electrification. In fact, PV systems are strongly recommended in Rwanda because they are rapid and cost-effective ways to provide utility-scale electricity for off-grid modern energy services to the millions of people who lack electricity access.

Site investigation is essential for developing and constructing a dependable and effective wind engineering project. Also, the kinetic energy of moving air, used to drive a wind turbine, produces electricity. Having seen the shortage of previous studies on wind energy sites’ suitability across Africa and having read about the abundance of untapped wind energy resources in the East African region, this paper used Geographical Information System (GIS), multi-criteria, and Analytic Hierarchy techniques to provide a geospatial analysis of wind energy technology siting suitability in Eastern African Community Countries. Different data were acquired and processed from numerous open-access databases (Global Wind atlas, Regional Center for Mapping of Resources for Development (RCMRD), African Geoportal, East African community website, and Energy data Info.org). The results reveal Kenya has large parts of its land areas highly appropriate for wind energy siting (15.26%) and 1.55% of its land classified as unsuitable for wind energy generation. The rates of suitability and unsuitability were respectively 26.57% and 4.87% for Burundi, 20.6% and 10.21% for Rwanda, 20.39% and 10.44% for Tanzania, and 4.65% and 27.15% for South Sudan. The findings also show that East Africa exhibits moderate levels of wind energy siting suitability, with an estimated average of around 37.27% of its land area moderately suitable for wind energy technology installation, covering thousands of square kilometers. The study is advantageous to academia and industry-related personnel engaged in renewable energy-related activities in other African countries with similar topographies.

A transition to solar energy systems is considered one of the most important alternatives to conventional fossil fuels. Until recently, solar air heaters (SAHs) were among the other solar energy systems that have been widely used in various households and industrial applications. However, the recent literature reveals that efficiencies of SAHs are still low. Some metaheuristic algorithms have been used to enhance the efficiencies of these SAH systems. In the paper, we do not only discuss the techniques used to enhance the performance of SAHs, but we also reviewed a majority of published papers on the applications of SAH optimization. The metaheuristic algorithms include simulated annealing (SA), particle swarm optimization (PSO), genetic algorithm (GA), artificial bee colony (ABC), teaching-learning-based optimization (TLBO), and elitist teaching-learning-based optimization (ETLBO). For this research, it should be noted that this study is mostly based on the literature published in the last ten years in good energy top journals. Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. Based on the past literature and on the outcomes of this paper, ETLBO is unquestionably more competitive than ABC, GA, PSO, SA, and TLBO for the optimization of SAHs for the same considered problem. Finally, based on the covered six state-of-the-art metaheuristic techniques, some perspectives and recommendations for the future outlook of SAH optimization are proposed. This paper is the first-ever attempt to present the current developments to a large audience on the applications of metaheuristic methods in SAH optimization. Thus, researchers can use this paper for further research and for the advancement of the proposed and other recommended algorithms to generate the best performance for the various SAHs.