Opportunities and Challenges of Renewable Energy Production in Ethiopia

Machine learning solutions for renewable energy systems: Applications, challenges, limitations, and future directions

The Paris Agreement, a landmark international treaty signed in 2016 to limit global warming to 2°C, has urged researchers to explore various strategies for achieving its ambitious goals. While Renewable Energy (RE) innovation holds promise, it alone may not be sufficient as critical deadlines approach. This field of research presents numerous challenges, foremost among them being the costliness of materials involved. However, emerging advancements in Machine Learning (ML) technologies provide a glimmer of hope; these sophisticated algorithms can accurately predict the output of energy systems without relying on physical resources and instead leverage available data from diverse energy platforms that have emerged over recent decades. The primary objective of this paper is to comprehensively explore various ML techniques and algorithms in the context of Renewable Energy Systems (RES). The investigation will address several vital inquiries, including identifying and evaluating existing RE technologies, assessing their potential for further advancement, and thoroughly analyzing the challenges and limitations associated with their deployment and testing. Furthermore, this research examines how ML can effectively overcome these obstacles by enhancing RES performance. By identifying future research opportunities and outlining potential directions for improvement, this work seeks to contribute to developing environmentally sustainable energy systems.

Electricity demand analysis and forecasting: The case of GADA special economic zone

Ethiopia is a country in East Africa experiencing significant economic growth in recent years, with an increasing electricity demand. Ensuring sustainable and efficient energy for newly developed industries and economic zones is crucial. In this study, a 15-year electric power demand forecast for the new economic zone under construction is conducted. The electrical power demand forecast is done for the year 2025-2040 by using bottom-up forecasting approach for three different scenarios. Long-range Energy Alternatives Planning (LEAP) system software is used to analyze residential, industrial, and general business sector electric power demand. The analysis of the assessed scenario shows that the economic zone's electric power demand increases by 52.2 % from the base year 2025-2040 for the baseline scenario, due to anticipated rapid urbanization, growth in population, economic expansion, and anticipated political stability. Compared to the baseline scenario, the total power demand shows a growth of 68 % from the forecast year (2025) to 2040 for the aggressive scenario, which ensures sustainable and efficient energy options that can draw businesses from both domestic and international baselines. In contrast, the total power demand in the conservative scenario shows a growth of 30.3 % from the base year (2025) to 2040. This reduction in demand compared to the two scenarios indicates a reflection of how much electricity power demand could be if certain development conditions failed to be realized in the economy. In general, both results show a rapid increase in power demand compared to the base year. To address this increasing demand, a supply-side demand analysis can be done for reference and aggressive scenarios. The analysis result indicated that by 2040, supply-side demand from the national grid will increase by 93.5 % and 175.9 % for reference and aggressive scenarios, respectively, compared to the base year 2025 demand. Due to the huge gap between the supply and demand in the country, onsite off-grid generation can be considered to cover 25 % of the demand in the economic zone. Hence, with the support of off-grid generation, the demand from the national grid was reduced to 45 % and 107 % for reference and aggressive scenarios with the support of onsite generation. Hence, this research clearly shows that there is a serious need for large scale electricity generation and distribution planning and preparation to meet the continually increasing electric power demand in a sustainable manner to accommodate the growth and change required to develop the modern economic zones in the country.

Site suitability assessment for the development of wind power plant in Wolaita area, Southern Ethiopia: an AHP-GIS model

The primary driver of economic growth is energy, predominantly derived from fossil fuels, the demand for which has experienced a significant increase since the advent of the Industrial Revolution. The emissions of hazardous gases resulting from the utilization of these fuels have been well acknowledged, therefore exerting a notable impact on the environment. In the context of Ethiopia, it is observed that despite the presence of ample renewable resources, the accessibility to power continues to be constrained. In order to effectively tackle this issue, it is imperative to redirect attention towards the utilization of renewable sources, such as wind energy, as a means of enhancing the existing power grid infrastructure. The present study used geospatial tools to evaluate the appropriateness of the Wolayita region for the establishment of a wind power facility. The process of site selection is guided by multiple factors, and a multi-criteria approach is facilitated through the utilization of Geographic Information System (GIS). The evaluation of seven characteristics was conducted utilizing the Analytical Hierarchy Process (AHP) methodology, which involved pairwise comparisons and weighted scoring. The process of suitability mapping involves the classification of locations into four distinct categories, which range from the most suitable to the least suitable. The findings demonstrate that the area of 0.628% (28.00 km2) is deemed the most suitable, while 54.61% (2433.96 km2) is considered somewhat acceptable. Additionally, 0.85% (37.85 km2) is identified as the least suitable, leaving a remaining 43.91% (1060.00 km2) that is deemed unsuitable. The central, northwestern, and southern regions are identified as optimal geographic areas. The results of this study facilitate the process of investing in renewable energy, thereby assisting Ethiopian authorities and organizations in promoting sustainable development. This report serves as a crucial reference point for the wind energy industry.

The potential of industrial sludge and textile solid wastes for biomass briquettes with avocado peels as a binder

Producing biomass briquettes from industrial solid wastes is a more environmentally friendly way to provide alternative energy and is essential for Ethiopia to satisfy its growing energy needs while also ensuring efficient waste management in the expansion of industrial parks. The main objective of this study is to produce biomass briquettes from a mixture of textile sludge and cotton residue using avocado peels as a binder. Textile solid waste, avocado peels, and sludge were dried, carbonized, and turned into powder to make briquettes. Briquettes made from the mixture of industrial sludge and cotton residue were combined in various ratios: 100:0, 90:10, 80:20, 70:30, 60:40, and 50:50 with the same amount of the binder. Briquettes were then made using a hand press mold followed by sun-drying for two weeks. The moisture content, calorific value, briquette density, and burning rate of biomass briquettes ranged from 5.03 to 8.04%, 11.19 to 17.2 MJ/kg, 0.21 to 0.41 g/cm3, and 2.92 to 8.75 g/min, respectively. The results revealed that the briquette produced from a 50:50 ratio of industrial sludge to cotton residue was the most efficient. The inclusion of avocado peels as a binder enhanced the briquette's binding and heating properties. Thus, the findings suggested that mixing various industrial solid wastes with fruit wastes could be an effective means of making sustainable biomass briquettes for domestic purposes. Additionally, it can also promote proper waste management and provide young people with employment prospects.

Maximizing biodiesel production from waste cooking oil with lime-based zinc-doped CaO using response surface methodology

Biodiesel is one of the alternative fuels, commonly produced chemically from oil and methanol using a catalyst. This study aims to maximize biodiesel production from cheap and readily available sources of waste cooking oil (WCO) and lime-based Zinc-doped calcium oxide (Zn-CaO) catalyst prepared with a wet impregnation process. The Zn-CaO nanocatalyst was produced by adding 5% Zn into the calcinated limestone. The morphology, crystal size, and vibrational energies of CaO and Zn-CaO nanocatalysts were determined using SEM, XRD, and FT-IR spectroscopy techniques, respectively. The response surface methodology (RSM), which is based on the box-Behnken design, was used to optimize the key variables of the transesterification reaction. Results showed that when Zn was doped to lime-based CaO, the average crystalline size reduced from 21.14 to 12.51 nm, consequently, structural irregularity and surface area increased. The experimental parameters of methanol to oil molar ratio (14:1), catalyst loading (5% wt.), temperature (57.5 °C), and reaction time (120 min) led to the highest biodiesel conversion of 96.5%. The fuel characteristics of the generated biodiesel fulfilled the American (ASTM D6571) fuel standards. The study suggests the potential use of WCO and lime-based catalyst as efficient and low-cost raw materials for large-scale biodiesel production intended for versatile applications.

Adoption of improved cook stoves by households in informal settlements of Woreda 12, Yeka subcity, Addis Ababa

BACKGROUND

This study analyzed the factors affecting the use of improved cook stoves (ICS) in informal settlements of Addis Ababa based on the data generated from 450 households drawn from Woreda (Woreda is a local term used to describe the lowest administrative unit of Addis Ababa City Administration, Ethiopia.) 12 of Yeka subcity. It examined the interactive effect of households' socio-economic backgrounds and energy sources on the adoption of ICS. The data were analyzed using descriptive methods and the multinomial logit model.

RESULTS

Demographic and economic factors such as sex of the household head,[Household head is the one who has an income and decision-making power in family affairs (a husband for married people)], family size and family income have no relationships with households' ICS use while education level, number of years lived in the area, type of home owned, and stove-operating costs have a significant influence on the choice of an ICS. Households that live in a good home (made from wood and cement) used more Mirt (Mirt is an improved firewood stove mainly used to bake Injera and bread.) and Lakech [Lakech also called Tikikil is an improved charcoal stove used to cook different kinds of dishes (non-Injera)] stoves than the traditional three-stone stoves. On the other hand, household heads with higher levels of education and who have lived more than 7 years in the area in a better home owned more ICS than the traditional three-stone stoves.

CONCLUSIONS

The availability, affordability, durability and simplicity to operate stoves, and subsidies affect the choice of an ICS. Energy sources that are commonly used by households in informal settlements also have a strong influence on the choice of energy-efficient stoves. Compared to ICS, heavy use of traditional three-stone stoves by households that already have access to electricity, directs government policies to focus on providing reliable electric service and subsidize those using ICS.

Investigating evolutionary trends and characteristics of renewable energy research in Africa: a bibliometric analysis from 1999 to 2021

Several countries across the African continent have been challenged with energy crises for decades. A growing number of studies have identified renewable energy as a sustainable way for Africa to address its persisting energy situation while combating climate change, as the continent has in abundance some of the common renewable energy resources. Little has been reported in the body of literature to quantitatively and qualitatively map the knowledge domain of this growing research field. In the current study, we conduct a bibliometric analysis on research documents extracted from the Web of Science Core Collection to identify trends and characteristics of the knowledge domain related to renewable energy in Africa from 1999 to 2021. Using two different software (VOSviewer and ITgInsight), we report the contribution of journals, countries, institutions, and authors and their collaboration patterns. We also perform co-citation and keyword analysis to identify the intellectual base and central themes of this research field. The results from the study revealed a growing interest in Africa's renewable energy, with about 90% of the total publication from within the last decade. Renewable & Sustainable Energy Reviews was identified as the most productive as well as the most influential journal in this field. The most contributing countries in this field were South Africa, USA, and Algeria. Centre de Developpement Des Energies Renouvelables, a research institute in Algeria, emerged as the most productive and influential institution. The analysis of research hotspots under different categories revealed that "solar energy," "CO2 emissions," and "rural electrification" are the topics that have gained maximum attention over the years. Keyword evolution analysis also identified "economic growth" and "green hydrogen production" as emerging topics that will play a major role in future studies. We conclude our work by providing specific suggestions and strategies to help bridge the gap which exists in the quantity and quality of renewable energy research between Africa and the rest of the world.

An Optimized Enhanced Phase Locked Loop Controller for a Hybrid System

The use of renewable energy sources is the need of the hour, but the highly intermittent nature of the wind and solar energies demands an efficient controller be connected with the system. This paper proposes an adept control algorithm for an isolated system connected with renewable energy sources. The system under consideration is a hybrid power system with a wind power harnessing unit associated with a solar energy module. A controller that works with enhanced phase locked loop (EPLL) algorithm is provided to maintain the quality of power at the load side and ensure that the source current is not affected during the load fluctuations. EPLL is very simple, precise, stable, and highly efficient in maintaining power quality. The double-frequency error which is the drawback of standard phase locked loop is eliminated in EPLL. Optimization techniques are used here to tune the values of the PI controller gains in the controlling algorithm. Tuning of the controller is an important process, as the gains of the controllers decide the quality of the output. The system is designed using MATLAB/SIMULINK. Codes are written in MATLAB for the optimization. Out of the three different optimization techniques applied, the salp swarm algorithm is found to give the most suitable gain values for the proposed system. Solar power generation is made more efficient by implementing maximum power point tracking. Perturb and observe is the method adopted for MPPT.