Browsing by Author "Getachew Bekele (PhD)"

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    Hydropower Generation and Operation Planning For Ethiopia
    (Addis Ababa University, 2021-12) Firehiwot Girma; Getachew Bekele (PhD); Mikael Ameline (Prof.)
    The Ethiopian power system is highly dominated by hydropower plants. Almost 90% of the generation is covered by hydropower. Although the total generation capacity in the power system is sufficient enough to cover the peak demand, it is common to see load shedding and power rationing in the country, especially in the dry seasons of the year. The absence of a suitable and appropriate generation planning tool makes the current planning dependent on historical generation patterns. Recent literature has shown different models for hydropower planning for long-term and short-term operation in a deterministic, stochastic, stochastic dynamic, etc., with different levels of details and mathematical formulations. However, most of the models are concerned with profit maximization and cost minimization in a competitive electricity market. In addition, no previous studies have been conducted, and no models have been developed for the planning of the unique Ethiopian power system. The Ethiopian power system is a system dominated by hydropower generation, which is dependent on seasonal rainfall. The electricity market is a vertically integrated market where the government determines the electricity price. Therefore, there is no price uncertainty and less concern about cost or profit. The primary concern for the planning of the Ethiopian power system will be the proper scheduling of the power plants to use the stored water in the rainy season through the dry season with minimum load shedding to increase system reliability while keeping the balance between load shedding now and in the future. In principle, load shedding can be avoided by using all the water available right now, but then, if there is a poor rainy season with low inflow the following year, the power system may get into a massive problem supplying the demand for that year. Before the market deregulation, the electricity market in developed European countries was almost similar to what is practiced in Ethiopia now. The difference is they have much more details of measurements and statistics about inflows, run time between reservoirs, etc. This thesis develops different hydropower planning tools, including deterministic and stochastic, risk-neutral, and risk-averse models for the Ethiopian power system based on the limited available data, intending to utilize the water stored in the rainy season throughout the year with minimum load shedding. It further studies and tests the models in a rolling horizon framework for long-term operation.The Methodology used to develop the hydropower planning tool is, first, all the necessary data for the planning is collected from Ethiopian Electric Power (EEP), inflow is scaled from the mean annual energy (MAE) of each reservoir using the publicly available precipitation data from NASA. Then, the deterministic model is developed and compared with the historical generation data. In hydropower generation, inflow is an uncertain stochastic process. To consider the uncertainties in the inflow, the deterministic model is further developed into a two-stage stochastic model. To run the stochastic model, we formulate a method to prepare a synthetic historical inflow series from the available data on hand and derive a method to estimate the stochastic process that mimics the synthetic historical series. We use Monte Carlo simulation to generate random inflow scenarios from the estimated stochastic process. The stochastic planning model is then tested both in a risk-neutral and a risk-averse version. We use Conditional Value-at-Risk (CVaR) risk measure to develop the risk-averse model. Finally, the performance of the models developed is compared using a rolling horizon framework for a one-year planning period. The results show that the Ethiopian power system has a great deal of flexibility to be operated more efficiently to minimize load shedding. The results also show that by using stochastic models, we can better manage the water in the reservoirs in the form of slightly lower load shedding without compromising the energy we reserve for the next planning period. We could also avoid large load shedding events so that the load shedding is evenly distributed throughout the year instead of having massive load shedding in a short period, which could be very valuable when we have higher load demand in Ethiopia. When testing the hydropower planning tools for current load demand, there is a very good generation capacity to supply the demanded load. However, there was significant load shedding in the actual operation, even though the planning model suggested no need for load shedding. It is concluded that it will be an improvement if the planning is supported by stochastic planning tools instead of using the method depending on historical data.
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    Long-Term Modeling and Analysis of Optimal Pathways and Scenario Alternatives for The Ethiopian Power Sector
    (Addis Ababa University, 2023-05) Dawit Habtu; Getachew Bekele (PhD); Erik O. Ahlgren (Prof.)
    The United Nations launched a new set of Sustainable Development Goals (SDGs) to guide the world during the next fifteen-year period from 2015 to 2030. With the “Goal 7-Ensure access to affordable, reliable, sustainable and modern energy for all”, the agenda 2030 recognizes the importance of sustainability, security, and affordability of energy supply to all countries but in particular for developing countries. And the greatest increase in demand for energy is envisaged to come from developing countries where, with rapid urbanization, largescale electricity generation with a reliable and optimum supply will be required. To achieve the SDG7 and ensure energy security, countries are required to develop sustainable and appropriate approaches to electricity planning. In this regard, policymakers increasingly rely on techno-economic assessments both to inform policy development and to help set the right national targets. Accordingly, the modeling and investigation of different optimal pathways and possible future scenarios has become a critical planning tool in the power sector. This type of assessment is currently lacking in developing countries, specifically in Ethiopia. Consequently, in line with the global and local needs, this dissertation deals with strategies and practices for sustainable energy system development in Ethiopia. It focuses on long-term electric power security to make timely investments on various energy resources and supply energy matched with the economic developments and environmental needs of the country. In this framework, the goal is pursued by setting the following three specific objectives: (1) To review and evaluate energy development, power sector reforms, policies and resource adequacy in Ethiopia. This objective is pursued to assess and evaluate the effectiveness of existing reforms and policies in Ethiopia in terms of meeting the country’s rising demand for energy by breaking the “business-as-usual” trajectory of the past. An analytical method to calculate resource planning indices such as reserve margin and expected unserved energy is used. The results indicate that the near-future generation reserve is not adequate to supply the increasing demand resulting mainly from expansion of electricity access, development of industrial parks, extensive expansion of railway network, extensive agriculture irrigation schemes, new sugar factories and export plan to East African Power Pool (EAPP) countries. The second specific objective is (2) To assess the fundamental dynamics, variables and policies that characterize the energy development and determine the evolution of electricity demand. The scientific literature reveals a weak understanding of the inherent characteristics and specific features of energy systems in developing countries. As a result, this specific objective is pursued by knowing the trend and capturing the relationship between demand and other independent socio-economic and technological variables. Comparative overview of various existing modeling frameworks is done in terms of several criteria, particularly their applicability to developing countries. Appropriate modelling frameworks are identified for assessing and projecting the long-term energy use in a systematic manner within the context of developing countries. A better system representation and applicable alternative policy scenarios are also developed by considering the unique characteristics of energy systems in developing countries (unsustainable use of traditional energy sources, high population growth, modernization and urbanization, low electricity access, supply shortage, high system losses, informal economy, etc.). Extensive and detailed dataset is used to simulate the alternative policy scenarios. The pathways represented by the scenarios can show the maximum expected rise in demand under different drivers and the best-case energy saving opportunities. The current methodologies employed for long-term energy demand projection are then evaluated, particularly focusing on the electricity demand. The result of the policy scenarios shows that while the application of energy efficiency policies and measures would only have a minor impact on the energy demand, their impact on the electricity demand is large, and that the application of such policies is a very important measure to combat supply-demand mismatch causing power shortages and black-outs. The projection results are compared with previous studies and reasons for the deviations and strength of the followed approaches are discussed. The last objective is (3) To identify the best power generation and capacity mixes to meet future electricity demands subject to various technical, economic, and environmental constraints. This is pursued by developing a soft-linked OSeMOSYS and LEAP model to determine the lowest cost electricity generation and capacity mixes to meet long-term electricity demands subject to certain policy scenarios that may impose technical constraints, economic realities and environmental targets. The model has various data requirement that describe the current and historical installed capacities, efficiencies, costs (capital, operating and maintenance, fuel costs), capacity factors, losses, expansion plans, etc. From the literature survey, it is observed that there is a gap in providing independent assessments of alternative technologies and policy choices that can be essential for developing countries in a way that addresses their particular needs and constraints. Thereby, the model explores the feasibility of including new technologies to the existing system. This includes assessments of centralized and decentralized methods of electricity supply. Novelties are introduced in terms of better system representation on reference energy system diagram, development of appropriate model and identification of relevant scenarios considering the context of the country and applicability to developing nations. Moreover, sensitivity analysis is carried out to study the effect of critical assumptions and varying parameters on the results. Five policy scenarios are employed (reference-ref, grid extension-grx, multiple resource mixmix, renewable and intermittent resource target-vRE, improved efficiency-Eff) to explore different possible futures and balance the long-term electricity needs and resources. The improved efficiency scenario is the most desirable compared to the other scenarios because of lower installed capacity requirements and economic benefits. Attributed to lower investment costs and abundant resource availability, the results show that renewable technologies are more competitive and favorable in the context of Ethiopia. Hydropower will continue to play a key role in the future electricity supply with the addition of alternative resources like wind, natural gas, geothermal, solar PV and CSP.
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    Optimization of Security Constrained Economic Dispatch for Integrated Renewable Energy Systems
    (Addis Ababa University, 2021-06) Shewit Tsegaye; Getachew Bekele (PhD)
    One way of noticing the importance of electricity in our daily lives is when sudden interruption or blackout occurs. Considering a power system with Integrated Renewable Energy Systems (IRES) in which power supply interrupts every time it rains, such power system can cause serious damage to different types of loads connected, service centers and production plants. The main cause is the sudden increase or decrease in power output. According to Ethiopian electric power-network blackout report (2013-2016), 15 major blackouts were reported in three years’ time. Production plants and service centers were down for an average of four months a year. Natural incidents, equipment failure, and supply-demand mismatch collectively called contingencies cause most of these blackouts. The first challenging aspect of power system operation is that electrical energy, unlike other commodities; is difficult to store in significant amounts. Implying that electrical power must be consumed at same time it is generated. For a reliable supply of power, it is therefore essential to maintain the balance between generation and demand. This aspect requires an accurate method of balancing generation and demand considering generation limits, transmission security constraints, contingencies, and uncertainties. The other challenging aspect is the intermittency and variability of renewable energy sources. With increasing emphasis on improving efficiency and utilizing more renewable energy to mitigate climate change effects, power industry is confronted with such generation–demand mismatch challenges. These challenges are related to intermittency and non-dispatch ability of IRES. One of the daily power-system operation tasks that coins these challenges is Security-Constrained Economic Dispatch (SCED). SCED is a process of allocating generation levels to generating units to entirely and economically supply the load while satisfying security constraints. Practical power system economic dispatch is multi objective, constrained, and stochastic, as it has to consider the aforementioned challenges. Practically a solution method that can cope up with the varying generation is needed. This Ph.D. dissertation presents hybrid Genetic Algorithm-Hopfield Neural Network (GA-HNN) based optimization of SCED for IRES that address power mismatch problems of the Ethiopian power grid. Hopfield neural network can learn the stochastic behavior of varying generation and genetic algorithm can improve the convergence of global maxima by both reproducing and mutation the top solutions.This dissertation encompasses four main contributions. First, a review on recent trends and state of the art of SCED applied for renewable energy sources and hybrid systems is articulated. Second, development of global search algorithms that provide approximate solutions for SCED problem, and mathematical modelling of the objective functions of IRES is carried out. Third, study and assessments of security parameters with credible contingencies and uncertainty involving determination of the effect of contingencies and security constraints corresponding to renewable energy sources is made. Finally, optimal generation dispatch of modified IEEE 118 bus system and Ethiopian renewable energy system using hybrid GA-HNN is presented. According to the results obtained, hybrid GA-HNN helps to determine SCED global optimum solution of integrated, intermittent renewable energy systems. The obtained results include saving 0.519 million $/MW within 24 hours of operation at power loss of only 35.23 MW. This makes the proposed approach a strong financial solution in renewable energy markets. Utilizing hybrid GA-HNN resulted in the reduction of power mismatch by 23%. This mismatch enables power system operator deal with the unserved customers and unserved energy produce. Moreover, number of recursive blackouts were reduced by 12.36 % and execution time of the solution method by 56.89 %.
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    Radiation Tolerant Power Converter Design for Space Applications
    (Addis Ababa University, 2022-07) Solomon Mamo; Leroux Paul (Prof); Getachew Bekele (PhD); Valentijn De Smedt (Prof.)
    Radiation and extreme temperature are the main inhibitors for the use of electronic devices in space applications. Radiation challenges the normal and stable operation of power converters, used as power supply for onboard systems in satellites and spacecrafts. In this circumstance, special design approaches known as radiation hardening or radiation tolerant designs are employed. FPGAs are beneficial for developing low-cost, high-speed embedded digital controllers for power converters, but their components are highly susceptible to radiation-induced faults. In safety and mission-critical systems, like space systems, radiation-induced faults are a major concern. Majority of commercial off-the-shelf (COTS) FPGAs are not developed to function in high radiation environments, with the exception of a handful of circuits that are radiation–hardened at the manufacturing process level at a very high cost overhead, making them less appealing from a performance and economic standpoint. Design-based techniques are another option for reaching the necessary level of reliability in a system design. This work investigates and designs a novel FPGA-based radiation-tolerant digital controller for DC-DC converters, with applications in space. The controller's radiation-induced failure modes were analyzed in order to develop a mitigation strategy, which included identifying the error modes and determining how existing mitigation approaches could be improved. For FPGA implementation and optimization of the radiation tolerant digital controller, a model-based design approach is presented. To validate the recommended solution strategies, fault injection campaigns are employed.