Community energy projects, actively governed and managed by community members, play an essential role in advancing just energy transitions, for example, by providing energy in remote areas, facilitating the adoption of renewable technologies, and building resilient electricity networks. However, their adoption remains limited. How does community energy work in practice, and how can it become more widespread? This article presents a study of community energy in three countries: Ethiopia, Malawi, and Mozambique. A multi-methods analysis (project inventories, qualitative interviewing, surveys) suggests that the political economy of development and material challenges, such as financing and supply chains, constrain the expansion of community energy. A survey of community energy beneficiaries demonstrates the tangible benefits these projects bring to disadvantaged communities. Concessional grants that recognise the social value of community energy can facilitate its development and support new energy models for a just energy transition.

Expanding electricity access cost-effectively requires strategies that account for spatial heterogeneity in demand, resource availability, and proximity to infrastructure. However, many existing studies oversimplify electrification planning by applying binary rural-urban categorizations and neglecting productive and institutional electricity loads. This study developed a long-term electrification plan at the settlement level, utilizing the Open-Source Spatial Electrification Tool to identify the least-cost solutions among grid extension, mini-grids (MGs), and standalone photovoltaic solar (SA PV) systems. Settlements were delineated by aggregating the high-resolution settlement layer (similar to 30 m resolution) and then enriched it with georeferenced resource data (solar irradiation, wind speeds, hydropower potential) and existing grid networks. Using a myopic optimization approach across three distinct periods (2021-2030, 2030-2040, and 2040-2050), the study analyzed multiple scenarios developed by combining varying electricity demand and grid generation costs. Under a low grid generation cost scenario, grid extension is the least-cost option for more than 82% of the population by 2030, though its share declines slightly in later periods. Under a high grid generation cost scenario, MGs become competitive for about 26% of the population by 2050. SA PV systems emerge as the least-cost option for over 16% of the population in both scenarios by 2030 but become less competitive in later periods. The findings emphasize the need for integrated national planning that combines grid expansion with MG deployment, while gradually phasing out SA PV systems. This approach accelerates the deployment of solutions tailored to local contexts, directly contributing to the achievement of Sustainable Development Goal 7.

Biogas production through anaerobic digestion (AD) presents a sustainable energy alternative with significant potential to reduce global warming. However, AD is a complex, nonlinear, and dynamic process influenced by time-varying parameters and non-stationary disturbances. These challenges, together with the limited availability of reliable online measurements for key concentration variables, hinder effective real-time monitoring. To address these limitations, this study proposes a joint state and parameter estimation approach based on a modified Advanced Monitoring and Control (AMOCO) model with a Particle Swarm Optimization (PSO)-tuned Extended Kalman Filter (EKF), a combination not previously applied to anaerobic digestion processes. The modified AMOCO model, originally developed for control applications, is adapted to better align with both simulated and experimental data. Sensitivity analysis identifies three key parameters whose estimation significantly improves system reconstruction. To further enhance estimation performance, PSO is employed to tune the noise covariance matrices of a discrete EKF. Validation using the Anaerobic Digestion Model No. 1 (ADM1) as a benchmark plant confirms reliable state and parameter estimation and accurate output predictions. Robustness is assessed by applying the EKF tuned for nominal noise to different measurement-noise levels, demonstrating stable performance under moderate noise mismatch and limited degradation under severe mismatch. Results show that the proposed PSO-EKF approach achieves a 70%-80% reduction in augmented state-estimation RMSE compared with a conventionally tuned EKF. The methodology provides a foundation for monitoring and control in AD and has potential for adaptation to other complex, non-linear bioprocesses, thus supporting more sustainable and efficient waste-to-energy systems.

Mini-grids (MGs) have emerged as a cost-effective solution for electrifying remote communities characterized by low population density and challenging geographical conditions. However, identifying optimal locations for sustainable MG deployment is complex due to technical, social, and economic factors. This study aims to identify economically feasible sites for renewable MGs in Ethiopia using the Open-Source Spatial Electrification Tool (OnSSET). This GIS-based framework systematically integrates key variables such as resource availability, population density, land cover, terrain slope, and proximity to existing infrastructure, using an equal weighting scheme across two grid proximity scenarios: 2.5 and 25 km from existing medium-voltage (MV) lines. To assess economic feasibility, the study calculated the Levelized Cost of Electricity (LCOE) for the selected sites. The results show that hydro MGs are the most cost-competitive option, with LCOE values between 0.09 and 0.16 /kWh. Under the 2.5 and 25 km grid proximity scenarios, 306 and 84 potential hydro MG sites are identified, capable of electrifying approximately 5 and 1.9 million people, respectively. Solar PV MGs also demonstrate significant potential, with LCOE values ranging from 0.15–0.22/kWh. Solar MGs could electrify 7.2 million people under the 2.5 km scenario and 3.2 million under the 25 km scenario. Wind MG, with LCOE values ranging from 0.12–1.75 /kWh, could provide electricity to 4.8 million people under the 2.5 km scenario and 3.1 million under the 25 km scenario. This study provides a pre-feasibility roadmap for MG deployment, informing policymakers and investors to prioritize sustainable rural electrification in Ethiopia.

The barriers and drivers of industrial decarbonization through energy efficiency (EE) improvements have been extensively explored in energy-intensive industries in developed countries; however, research in developing country contexts remains limited. This paper addresses the gap by investigating a broad range of barriers and drivers of decarbonization efforts in the Ethiopian Cement Industry (ECI). A PESTLE (political, economic, social, technological, legal, and environmental) framework-based measurement theory is developed to analyze the barriers and drivers. The measurement theory suitability is confirmed statistically through exploratory and confirmatory factor analyses, using response data collected from relevant stakeholders via a five-point Likert-scale survey. In this paper, the top-ranked barriers (rating > 3.76/5) identified by respondents are insufficient stakeholder collaboration, weak top-management support, inadequate infrastructure, and absence of economic subsidies. The highly ranked drivers (> 3.77/5) are cost reductions resulting from lowered energy use, threats of rising energy prices, and effective environmental management systems. On the other hand, respondents ranked competing priorities for capital investment (3.41/5) and strengthening the image of a company (3.22/5) at the bottom of barriers and drivers, respectively. The survey also highlighted gaps in EE implementations, proactive energy management (EnM) systems, and industrial EE policies. The key findings and insights drawn from the survey results and analysis are used to formulate several decarbonization strategies for short- and long-term planning, along with policy instruments (e.g., tax rebate/credits, energy/carbon taxes, removing energy subsidies, polluters pay principle, landfill taxes, minimum equipment standards, energy audit regulation) and stakeholder engagement. The main strategies include adopting cost-effective EE technologies and demand response programs, deploying emerging/innovative low carbon technologies, utilizing alternative fuels (waste/biomass), and reducing clinker-to-cement ratio. Strengthening government engagement, stakeholder collaborations, and waste collection and pre-processing infrastructure, reforming EE policies, regulations, and financial schemes, mandating EnM systems, and creating green certifications are essential for advancing decarbonization efforts in ECI. Finally, this paper contributes to the global decarbonization effort by providing a robust methodological framework that leads to formulation of actionable, sector-specific strategies.

Energy availability and reliability are essential for economic growth and sustainable development. The problems with growing energy demand could be addressed by supply-side energy management. However, this task has become increasingly challenging due to high fluctuations in electricity demand and the increasing penetration of intermittent renewable energy into the electricity supply mix. This study aims to investigate the energy demand flexibility potential in the energy-intensive cement production sector. A mixed integer linear programming model (MILP) has been developed to flatten the grid's hourly demand curve by minimizing the industrial customer's hourly peak loads and maximizing the shifting of demand to off-peak periods. The result reveals that the demand flexibility potential of the case study cement plants is about 495 MWh per day, constituting approximately 28 % of the daily total electrical energy used by these cement plants, proving that the cement industry is a potential candidate for demand response strategies. By adapting the proposed model, the loads of the case study plants during the peak period of the day are reduced by an average of 75 %. In addition, case study plants have achieved an overall reduction of 188 t of CO2 emissions per day. Furthermore, the cost of consumed electrical energy for a day decreased on average by 14 % in these plants. Thus, the proposed model can help minimize the impact on grid instability and the cost of energy consumption of an industrial customer. Scenarios such as the variation of the capacity factor and onsite electrical power generation, i.e., waste heat recovery power plants, can promote the demand response strategies in the cement sub-sector. The study could be useful to energy-intensive industries and relevant policymakers to understand the demand response in maintaining power system reliability and explore ways to implement demand-side energy management strategies with appropriate electricity tariffs.

Mini-grids (MGs) have emerged as an economically viable alternative to communities in remote areas with low population density or with geographical constraints. However, identifying optimal locations where investments can lead to long-term and sustainable MG development remains a significant challenge due to the complex interplay of technical, social, and economic factors. This study addresses this challenge by identifying economically feasible renewable MG sites in Ethiopia. The study employs the Open-Source Spatial Electrification Tool (OnSSET) to integrate critical factors such as resource availability, population density, land cover, terrain slope, and proximity to existing infrastructure. These factors are used based on equal weight criteria, under two grid proximity scenarios (2.5 km and 25 km from existing medium-voltage (MV) grid lines). The Levelized Cost of Electricity (LCOE) for the selected sites is calculated to assess economic feasibility. The results show that hydro MGs, with LCOE values ranging from 0.088–0.16 $/kWh, are the most cost competitive option. Under the 2.5 km and 25 km grid proximity scenarios, 306 and 84 potential mini-hydro sites are identified as capable of electrifying approximately 5 and 1.9 million people, respectively. Solar PV MGs exhibit significant potential and LCOE values ranging 0.15–0.22 $/kWh. Solar MGs could electrify 7.2 million people under the 2.5 km scenario and 3.2 million people under the 25 km scenario. Wind MG, with LCOE values ranging from 0.12–1.75 $/kWh, could provide electricity to 4.8 million people under the 2.5 km scenario and 3.1 million under the 25 km scenario. The study provides a roadmap to compare different suitable locations at the prefeasibility stage for MG deployment, guiding policymakers and investors in prioritizing MG deployment for sustainable rural electrification.

Cement manufacturing is a highly energy-intensive process, with a significant amount of the thermal energy in the production chain being lost. Consequently, exploring ways to capture and utilize this wasted heat to generate electricity and meet industrial energy requirements is crucial. This study investigates the potential for Waste Heat Recovery (WHR) power generation with a case study in the Ethiopian cement industry. The levelized cost of energy (LCOE) and the Net Present Values (NPV) of the WHR power plant based on 3 options (i.e., steam Rankine cycle, Organic Rankine cycle, and Kalina Rankine cycle) are evaluated. The findings reveal that the steam Rankine cycle-based waste heat recovery power plant is the only feasible option in the Ethiopian cement plant, with a NPV of 0.35 million USD and a LCOE of about 0.04 USD per kWh. The power capacity of the feasible plant is about 8.9 MW for the studied cement plant with an annual production capacity of 2.3 Mt of cement, covering about 18% of its electricity demand. The plant's associated reduced CO2 emissions potential is insignificant, as the hydropower sources dominate the national power grid. However, assuming the proposed WHR power plant reduces the activation of diesel power plants during peak hours in the Ethiopian power grid, the Steam Rankine Cycle (SRC)-based waste heat recovery power plant (WHRPP) in the case study cement plant has the potential to reduce CO2 emissions by approximately 7.9 million tonnes per year. Sensitivity analysis has been conducted to ensure that the results derived from the base case assumptions remain reliable despite potential fluctuations in the key parameters. This study could be a useful reference for policymakers and industries to harness alternative and sustainable electricity generation potential from onsite power generation plants in the cement industry.

Access to electricity remains a significant developmental challenge in Sub-Saharan Africa. To address this, national electrification planning must account for both the temporal evolution and spatial heterogeneity of electricity demand, reflecting local socioeconomic realities and climatic conditions. This study aims to project longterm, spatially explicit electricity demand for households, productive users, and community institutions in Ethiopia. It also assesses the potential impact of rising temperatures on future electricity demand. Regression models are used to predict temporal changes in electricity demand, while the Open-Source Spatial Electrification Tool (OnSSET) is used to examine the spatial demand dynamics across population settlements. Three scenarios-Business-as-Usual (BAU), High Economic Growth (HEG), and Rapid Urbanization (RU)-are developed to explore different development pathways from 2021 to 2050. The results show that, compared to the base year (2021), national electricity demand could increase by 176 % under the BAU, 219 % under the HEG, and 285 % under the RU by 2050. The most substantial increase in electricity demand is projected to come from households, followed by productive users. Significant spatial variations are evident, with household demand ranging from Tier 1 to Tier 4. Moreover, while projected temperature increases total national demand by only 0.53 % at national level, it can increase local demand by up to 22.6 %. These findings highlight that national averages or household-only models fail to capture the significant spatial and sector-specific variations in electricity demand. Therefore, high-resolution, multi-sector demand projections are essential for designing cost-effective and equitable electrification pathways.

Tedecha Island, Ethiopia, faces unique energy challenges due to its isolation and reliance on traditional energy sources. This research proposes a sustainable hybrid power system for the island’s 2,500 residents, integrating solar, wind, and pumped hydro storage (PHS). Wind data, collected over a year, informed the system design. The PHS utilizes Lake Ziway and a nearby crater pond, with a GIS-LiDAR based 3D model guiding its development. Solar energy potential was assessed using PVGIS 5.2 and local data. Homer Pro optimized hybrid configurations, including a 245 kWh PHS component, resulting in a cost-effective wind-solar-PHS microgrid with a COE of $0.130-$0.162/kWh. Crucially, the system design aligns with the Water-Food-Energy Nexus (W-F-E-N) approach. Analysis of upper reservoir water levels (0-100%) demonstrated robust operation within a 0-75% range, maintaining energy supply. This study showcases the viability of an environmentally friendly hybrid system for Tedecha Island, leveraging existing natural reservoirs to minimize costs and environmental impact, providing a valuable model for similar off-grid communities.

Sensitivity analysis plays a crucial role in understanding the dynamics of anaerobic digesters, converting biodegradable matter into biogas, and it can be used to reduce the need for extensive parameter estimation by determining what the most influential model parameters are. The anaerobic digestion process has complex nonlinear dynamics, that can be described by the modified AMOCO model having seven states and twenty parameters but suffering from a lack of accurate and robust online measurement. Therefore, the development of accurate state and parameter estimation is challenging, one way to improve the robustness and accuracy of the estimator, is to reduce the number of parameters through sensitivity analysis. This study identifies the most influential parameters based on dimensionless sensitivity coefficients. Through a systematic assessment of parameter impacts on model variables, we highlight the strong influence of the model's cascade structure on parameter sensitivity. Furthermore, employing period averaging with a threshold of 0.2, we identify eight significant parameters out of the eighteen model parameters. This research contributes to the understanding of anaerobic digesters, specifically employing the modified AMOCO model, and suggests a framework for parameter selection to enable optimized operation.

AbstractDelivering the energy transition depends on multiple actions in policy and regulation, project delivery, and project operation that require multiple skills. To what extent is current energy education serving the demands of a rapidly changing sector? This chapter adopts the energy literacy framework to examine the energy education landscape in Ethiopia and its suitability to the current demands of the transition to sustainable energy. The energy literacy framework highlights that while energy education has, in general, focused on developing technical and economic skills for the management of energy systems, a changing landscape also requires community and political literacy.Empirical research conducted in Ethiopia examined first policymakers’ perspectives on the skills needed to deliver the energy transition. Second, the research analysed energy-related programmes offered in higher education, looking into the historical development of the Institutes of Technology in Ethiopia. Third, the research conducted a survey with higher education leavers to examine how they have adapted their education to their professional practice. The research reveals a significant gap in social sciences perspectives on energy, compounded by educational programmes that prioritise theory over practice. A concerted reform within the educational sector is needed to ensure professionals acquire the skills to lead the energy transition in Ethiopia.

AbstractThere is a generalised assumption that the development of energy policy and regulation leads to increased access to energy. This paper investigates the empirical evidence to support this assumption in Ethiopia, Malawi and Mozambique, providing a comparative assessment of the regulatory landscape of energy in the three countries and their current status in terms of advancing towards universal energy access for both electricity and fuels. Using comparatively available data, the analysis examined the impact of extensive and dispersed bodies of regulation on energy access, as well as the extent to which pioneering community energy enhances energy access. The results are examined in the light of the current context of energy provision in the three countries. The results suggest that universal access to electricity requires an extensive body of energy policy in general and regulation of community energy in particular. However, while being a pioneer in community energy is correlated with improvements in energy access, the factors that explain such a correlation are not clear. More research needs to advance the current understanding of how regulation interacts with other drivers of infrastructure development and innovation to understand what works in a sustainable transition to provide universal access to clean energy.

In Ethiopia, renewable energy offers people an affordable, dependable, and eco-friendly power supply while decreasing the carbon footprint. However, delivering a renewable future for the country requires a massive change in social practices and systems of provision. The slow progress of renewable development is hindering the transition to a cleaner energy future. Over 80 % of people live in rural areas where it is expensive to reach them via grid networks in Ethiopia, requiring off-grid alternatives. Community energy systems, which are off-grid energy systems in which communities play a key role, offer alternative strategies to close the country's energy access gap. However, community energy systems remain underdeveloped in Ethiopia. There is a need to understand the opportunities for community energy and the barriers that hinder its development in Ethiopia, and their role in energy transitions. This paper adopts an experimental lens to understand the diverse dimensions of community energy projects through how they are made, maintained, and lived. Using a comparative analysis of three multi-method, qualitative case studies, this paper argues that the political context poses the biggest obstacle to the development of community energy in Ethiopia despite these projects' tangible benefits. The analysis indicates that community energy projects allow communities to be involved in all stages of project development. In every project, communities assume project management responsibilities after commissioning. However, these projects encounter challenges in resourcing capital, managing supply chains, and building necessary skills among community members to understand business models to ensure sustained operation of the systems.

The renewable energy sector has experienced a rapid expansion, driven by rising fossil fuel costs, increasing concerns about energy security, and the imperative to electrify rural areas. This growth creates a demand for skilled professionals, and higher education institutions must respond by providing comprehensive and practical renewable energy education. This study aims to analyze energy education in Ethiopian public universities, considering program offerings, content, geographical distribution, challenges, and opportunities. To achieve this, a multifaceted methodology involving systematic curriculum reviews, targeted surveys, data compilation, and interactive spatial mapping is employed. Findings indicate a diverse landscape, with both standalone programs and integrated courses available. Among the 45 public universities, only 22% of them have Institutes of Technologies (IoTs), indicating a significant technology-focused institute gap. None of these universities provide standalone energy programs at the BSc level, and less than 10% offer such programs at the MSc level. Notably, key energy courses like “Energy Conversion and Rural Electrification” and “Hydropower Engineering” have been identified, taught in 78% of public universities, and integrated within Electrical Power Engineering programs at the BSc level. However, the evident lack of practical training and experiential learning in energy education has implications for the sector's development in Ethiopia.

Cement production is a major consumer of energy and the largest source of industrial CO2 emissions. This study aims to perform an environmental life cycle assessment of clinker and cement production in Ethiopia, using ReCiPe impact assessment method. Inventory data (material, energy, and transportation) is collected from seven major Ethiopian cement industries. The midpoint analysis identified nine hotspot environmental concerns: global warming, ozone formation (human health and terrestrial ecosystem), particulate matter formation, terrestrial (acidification and ecotoxicity), freshwater eutrophication, human carcinogenic toxicity, and fossil resource scarcity. Human health emerged as the most significantly affected endpoint damage category by the midpoint impacts. Among the process stages included in clinker system boundary, clinker production phase (kiln emissions) is a significant contributor to the total score of the hotspot impacts, ranging from 60.7% to 91.8%. The clinker system is responsible for over 81.03% of the overall environmental burden of cement. The sensitivity analysis reveals that a 5% change in kiln energy consumption and transportation burden could lead to a reduction in hotspot impacts ranging from 1.8% to 5%. To foster reliability of this study, uncertainty analysis is also conducted. Overall, the findings indicate the need to enhance environmental sustainability in Ethiopian cement production.

Access to reliable electricity remains a challenge for millions in remote African villages, including Lake Ziway’s islands in Ethiopia. This study introduces an integrated electricity system for Tulu Gudo Island, combining floating photovoltaics (FPV), pumped-hydro storage (PHS) and diesel generators (DGEs) to overcome energy constraints, land scarcity and sustainability issues. The study assesses electricity demand and solar-PHS potential using LiDAR-based digital elevation model (DEM) data and Geographic Information Systems (GIS). PVsyst and HOMER Pro optimize the system based on net present cost (NPC), cost of energy (COE) and its ability to support a water-energy-food (W-E-F) nexus approach. An optimized configuration with 32.2 KWp FPV and two PHS units (PH: 245 KWh (508 KWh)) meets Tulu Gudo Island’s energy needs through a cycle charging strategy (CCs). This configuration offers economic and environmental sustainability, with an NPC of $154,265 and a COE of $0.140/KWh, while conserving 8760 m3 of water. It integrates successfully with the W-E-F nexus approach, achieving a 7% increase in electricity generation and a 2.4% higher capacity factor compared to conventional setups. The study validates results through comparisons with other simulation tools, ensuring accuracy. This hybrid electricity system has potential applicability in regions with similar conditions worldwide.

The cement industry is one of the most energy and emission-intensive sectors, accounting for approximately 7% of total-industrial energy use and 7% of global CO2 emissions. This study investigates the potential energy savings and CO2 abatement in the cement plants of Ethiopia. A Benchmarking and Energy Saving Tool for Cement is used to compare the energy use performance of the individual cement plants to best practices. The study reveals that all the surveyed plants are less efficient, with an average energy saving potential of 36% indicating a significant potential for energy efficiency improvement. Then, twenty-eight energy efficiency measures are identified and analyzed using a bottom-up energy conservation supply curve model. The results show that the cost-effective electrical energy and fuel-saving potentials of these measures are estimated to be 99 Gigawatt hours per year which is about 11.5% of the plants' annual electrical energy consumption and, 2.7 Petajoules per year which is to be 12.5% of the plants' annual fuel consumption, respectively. The cost-effective fuel measures have an annual average CO2 emission reduction potential of 254 kilo-tonnes per year which covers about 5% of the total CO2 emission. Sensitivity analysis is conducted using the key parameters that show some discrepancy in the base case results. This study could be used as a reference for policymakers to understand the potential for energy savings and CO2 abatement. It could also be used to design policies in improving energy efficiency in the cement sector.

In this study the genetic variability of soybean lines generated from segregating populations introduced from USA was evaluated.A total of 97 soybean genotypes that were introduced from USA along with three checks were grown in 10×10 simple lattice design with two replications at Jimma, Ethiopia.The ANOVA results showed significant (p≤0.05)variations in days to flowering, days to maturity, plant height, number of branches per plant, number of pods per plant, pod length, number of seeds per pod, number of seeds per plant, 100 seed weight, above ground biomass, harvest index, and grain yield indicating a considerable variability among the tested genotypes for the characters.Characters viz., plant height, number of branches per plant, above ground biomass and grain yield had high heritability and high genetic advance.Grain yield had positive and high significant (p≤0.01)genotypic correlations with harvest index (0.746) and 100 seed weight (0.267).Similarly, grain yield showed positive and significant (p≤0.05)genotypic associations with number of seeds per plant (0.225) and above ground biomass (0.205).This implies that higher mean values for these traits tend to improve grain yield in soybean.Cluster analysis grouped the genotypes into three clusters with the maximum squared distance found between cluster II and III.The principal component analysis revealed that the first four principal components (PCs) accounted for more than 71.25% of the total variation.The variability amongst the tested genotypes, heritability and genetic advance, as well as the associations in the tested traits provide information for an increased soybean productivity using this lines.