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Start date: 2021Subject: search.filters.subject.Sustainable development

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    Development of integrated model and framework for sustainable energy resources and systems planning
    (2024-05) Akpan, Joseph Samuel; Oludolapo, Olanrewaju Akanni
    Sustainable energy development (SED) is a crucial component of the Sustainable Development Goals (SDG), aiming to maintain economic and social progress while protecting the environment and mitigating climate change's effects. SED serves as a transition paradigm for sustainable development, providing a blueprint for energy peace and prosperity for people and all uses. The first objective of this dissertation is to identify 10 interlinked themes of SED and explore 2 of them, which are the least studied in existing SED reviews. These two themes include energy financing and commitment to climate change and the need for 100% renewable energy (RE), a part of the decarbonization strategy towards the 1.5 - 2.0 °C Scenario. The study suggests that the current G20 countries' contributions, if done continuously per annum, in addition to 80% more funding from private investment of the same amount in the 1.5°C scenario financial requirement for clean energy, is sufficient to limit global warming. In addition to the present drive for 100% RE for all purposes, an emphasis is placed on addressing other issues, such as energy storage options, developing countries' development agenda, and regional security stability to prevent energy wars. Emerging SED decarbonization strategies are presented across power, transport, building, and industrial sectors. This part concludes with a summary of SED progress and directions for future research, mainly the need for re-defining Nationally Determined Contribution (NDC) through a centralized global or regional stock-taking strategy for greenhouse gas emissions reduction. Consequently, the next study attempts to address the limitations of the current NDC by formulating a policy hypothesis and applying it to an integrated assessment tool (here, termed the environmental model) for strategic stock-taking in reducing GHG emissions. In developing this indexing model, being the first objective of this thesis, we analysed the potential impact of Nationally Determined Contributions (NDCs) under the Paris Agreement on global temperature rise used as the key model input parameters with countries' historical data and other parameters such as GDP, population growth. With the use of an integrated assessment tool based on the concept of system dynamics, the analysis constructs a framework to project global temperature changes under five policy scenarios, namely baseline, current (announced energy policies 1 and 2), and optimum (2.0 0 C Scenario), and most optimum (1.5 0 C) case scenarios. The hypothesis is formulated based on the analysis of current, announced, and best-case global and or applicable national policy scenarios. The model aims to address critical questions regarding the effectiveness of the on-going NDCs commitments in limiting global temperature rise to well below 2 0 C, in alignment with the Paris Agreement's goals. The simulation results offer a roadmap for optimizing the current NDCs in global and national energy policies and treaties, fostering international collaboration, and reinforcing the global commitment to combating climate change. Leveraging on the preceding simulation result of the environmental model, a novel emissions budgeting (EB) model tool (here, termed the economic model) was introduced as a simplified approach for the determination of the economic attractiveness of the policy scenarios of the environmental model. Hence, the second objective, which was to determine the economic benefit of policy scenarios, was achieved. Some advanced countries’ rapid population, economic growth, and energy consumption from mostly 100% electricity that is majorly fossil-based contributes significantly to global CO 2 emissions. In contrast, the case in most developing countries is different. For instance, electricity access in Africa is less than 60%. Hence, this presents challenges and opportunities for achieving the United Nations’ Sustainable Development Goals (SDGs) 7 and 13 of generating all energy from cleaner or low-carbon sources to reduce CO 2 emissions in all countries and combating climate change consequences. Therefore, considering the peculiar situation of other developmental goals, such as increasing population access to electricity while being obliged with the need to transit to complete renewable energy, as our third objective, we explored the idea and transition paradigm of reaching a 100% renewable energy that is void of unjust energy transitioning, climate injustice, and unbiased drive for increasing renewables energy penetration in the global energy mix. The increasing need for renewable energies has been widely acknowledged to greatly advance the climate change agenda as increasing clean energy usage depletes the accumulation of GHG in the atmosphere. Alongside reducing the accumulation of GHG, increasing RE share in the national mix has constantly become the core of many countries' energy policies and the agenda of many of the NDCs reported by countries. Presently, about 30 countries already with over 70% of their national electricity mix from RE. A part of this has birthed a new paradigm and an emerging field of 100% RE for all purposes, recently receiving much attention from academia and in public discourse. Upon establishing the need for analysing the transition towards 100% RE, the thesis demonstrated this conceptual idea through a model (here, termed the energy model) to analyse the possibilities for a 100% renewable energy system at the global level. Because several studies have already done such analysis, however, this has hardly been directly linked to the climate scenarios. Therefore, this thesis bridged this gap in the literature by synthesising the energy transition at different percentage shares in the global primary energy mix over time with the effect on global temperature levels. The rationale behind this was to present a discussion on the pathway possibilities and challenges of achieving 100% RE and whether it is possible to meet the total global energy demand through RE, with what effect on the climate scenarios. To do this analysis, we further define our hypothesis using baseline, optimum, more optimum, and extreme optimum path scenarios to ascertain such possibilities. Finally, we used an integrated assessment model based on the principles of system dynamics to analyse these hypotheses and to find the implications of each action or scenario on other factors such as global temperature, GHG emissions, energy storage breakthrough while keeping the population growth at maximum possible value of 12.4 billion persons by 2100 with GDP growth rate not less than 1.5%. The findings are valuable in helping us discuss if 100% RE can be a reality and what the implications are. Our results show that in the baseline current scenarios, the global average temperature will most likely be kept at 3.3 0 C. Hence, the world would need very urgent and unprecedented efforts beyond the current baseline of business as usual. Interestingly, our findings also indicate that to stay within the 1.5 and 2.0 0 C Scenarios, the world may need just between (58.6 - 77.3) % and (62.7 - 82.8) %, respectively, in the global energy mix. For the most optimistic scenario, (75.5 - 99.8) % RE may be required, and this is able to keep the temperature rise even well below 1.5 0 C but at 1.1 0 C. The 1.1 0 C possibility is quite highly ambitious, in my opinion, because it requires the intensity of global mix energy generation of about 6627 extra joules from renewables only. The major challenge with the idea of 100% RE for all purposes is that achieving such a feat requires a more diverse approach and scarcely are there 100% RE studies that incorporate holistically the interrelation of several pertinent strategies. Therefore, there exists a need to meet both the technical and non-technical requirements. In order to address this shortcoming, our third objective introduces six methodological or evaluation mechanisms (herein, identified as 100% RE evaluation metrics) suitable for existing and future 100% renewable energy analysis. It then reviews energy modelling tools to identify their applicability to 100% RE analysis. The perspectives presented in this thesis are valuable in developing a common integrated methodology and modelling tool for analysing full renewable energy adoption in countries or regions with best trade-offs, using performance indices that have not been previously used. The proposed metrics could also help with proper national and regional energy resources and system planning for new energy projects and installations, contributing to sustainable development. The framework and narrative, presented in the form of a model within this dissertation, make a noteworthy contribution to the ongoing discourse surrounding the energy transition as, to the best of my knowledge, this concept has not been presented this way. The results from this dissertation can be further investigated through a streamlined application of the approach at individual country or regional level to facilitate inclusive and climate-responsive planning and execution strategies for sustainable energy and electricity generation, distribution, and utilization at both national and urban levels. The implications of the findings have the potential to inform the United Nations Framework on Climate Change Convention (UNFCCC) and Conference of Parties (COP) policies in better ways of promoting equitable support for countries, regions, energy consumers, utilities, and prosumers.
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    Sustainable energy transition and optimization of grid electricity generation and supply
    (2024-05) Kabeyi, Moses Jeremiah Barasa; Olanrewaju, Oludolapo Akanni
    Clean and low-carbon energy sources and technologies have emerged as a critical driver in delivering the energy transition and achieving net zero-carbon emissions. All energy sources and power systems produce greenhouse gases (GHGs) and hence they contribute to anthropogenic greenhouse gas emissions and resultant climate change besides contributing to other negative environmental impacts. Energy sustainability remains a major challenge globally due to current heavy reliance on depletable and polluting fossil fuels for most of global energy needs. This study examines the energy transition strategies and proposes a roadmap for sustainable energy transition for sustainable energy planning and grid electricity generation and supply in wake of commitments made by the world community to the Paris Agreement aimed at reducing greenhouse gas emissions and limiting the rise in global average temperature to 2oC and preferably 1.5oC above the preindustrial level and realisation of the sustainable development goal of the United Nations. The sustainable transition strategies typically consist of three major technological changes namely, energy savings on the demand side, generation efficiency at production level and fossil fuel substitution by various renewable energy sources and low carbon non-renewable sources like nuclear power and carbon emission reduction strategies like carbon capture and sequestration and a conversion from high carbon fossil fuels like coal and oil to natural gas which remains the cleanest fossil fuel. The study demonstrated that decentralised generation with application of both demand side management and behind the meter management (BTM) strategies are effective measures to increase the use of renewable energy resources which are often locally available leading to higher uptake of renewable energy sources and conversion of consumers to prosumers making the transition economically sustainable. Waste to energy options have a significant potential to contribute to the energy transition e.g. use of biowaste for biogas production, slaughterhouse waste biodigestion for biogas and electricity generation and waste treatment and disposal, waste heat recovery from used geothermal for extra power generation and reinjection to improve the reservoir sustainability and use of bagasse and sugarcane trash for grid-based power production in sugar factories. Therefore, domestic, and industrial scale waste to energy conversion can enhance the economic sustainability of waste management process by offering useful energy substitutes for fossil fuels and enhanced energy security through decentralisation of generation. Whereas sustainable development has social, economic, and environmental pillars, energy sustainability is best analysed by five-dimensional approach consisting of environmental, economic, social, technical, and institutional/political sustainability to determine energy resource sustainability. The study recommends the adoption of sustainability-based planning for energy development and optimisation of electricity generation and supply where energy sources are analysed and ranked based on the five dimensions of energy sustainability instead of Least Cost Development Planning (LCDP) often applied by many countries. On this basis, the sustainable energy transition and optimisation of power generation will rely on both renewable and non-renewable energy since both have an important role in the realisation of the energy transition plans even though the desire is to shift entirely to renewable energy sources by the year 2050. The sustainability of various energy sources was assessed with hydrogen, wind, solar, sugarcane bagasse and cane trash, biogas and ocean energy technologies proving to be among the most sustainable renewable energy and sustainable sources. The study also examined various power plants and energy conversion systems for electricity generation in terms of their specific role and potential in grid-based power generation with hydro power plants, geothermal, nuclear, fuel cells, raking high on performance indicators like load and capacity factors making them ideal for base load power supply. Diesel engines and gas turbines using cogeneration and dual cycle systems powered by cleaner fuels like natural gas, hydrogen and biomethane will play an important role in supplying intermediate and peak load power. The study highlighted enabling technologies and concepts in the energy transition which include decentralisation of generation, cogeneration and trigeneration, demand side and behind the meter management microgrids and smart grid technologies, energy and generation planning and optimisation models, energy storage, electrification of transport and use of electric cars as decentralised electricity sources through the V2X technologies like the G2V and V2G, and carbon capture and sequestration for emissions reduction in fossil fuel power plants making them more sustainable. The study classifies electric vehicles as distributed power plants and variable loads with extensive use of energy storage while sugar cane bagasse is noted as a sustainable energy resource for power generation by cane sugar factories by application of more efficient grid connected cogeneration power plants. The study identified long project gestation period as the main factor limiting nuclear and geothermal energy deployment and recommends the adoption of modularised wellhead generators and small modular nuclear reactors (SMRs) as a solution to enhance exploitation of these sustainable energy and technologies through faster deployment with high degree of flexibility. Biogas and biomethane demonstrated significant potential as renewable energy sources for power generation and substitute fuels in all applications of fossil natural gas. The study recommends sustainability-based planning for the energy sector and power generation and use of both renewable and non-renewable but sustainable sources of energy, adoption of smart energy concept by all sectors and investment in energy technology and infrastructure development for hydrogen and other promising energy sources like ocean thermal, wave and tidal energy and the conversion of the transition from the traditional to smart grid systems and a shift from centralised to decentralised power generation. Since the transport sector accounts for a significant portion of the global greenhouse gas emissions, electrification of the transport sector and coupling with the power sector is a key strategy recommended for the transition with the smart grid and microgrids playing an enabling role. Since energy sources and generation technologies have associated emissions occurring at different sections of the lifecycle, the use of lifecycle costs and emissions are helpful in long term energy and generation planning which demonstrate that renewable sources and nuclear are the most sustainable when analysed within the five dimensions of energy sustainability, but with the non-renewable sources playing a critical role as dispatchable sources for sustainable grid power generation, while the smart grids and use of energy storage can increase the uptake of variable renewables to as high as 95% to 100% up from a low of 20-25% uptake of variable renewables with the traditional grid. This will significantly help the world in achieving the global emissions and climate targets as. stipulated in the Paris Agreement as well as the sustainable development goals (SDGs). Graphical Abstract The overall objective of the study was to provide solutions to build global energy systems based on renewable and sustainable energy resources and optimise power generation and consumption by use of sustainable energy resources and generation technologies based on the five dimensions of energy sustainability. A sustainable energy system should intergrade electricity and other sectors through smart electricity grids, smart gas grids and smart heat grids as demonstrated below.
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    Energy assessment and scheduling for energy optimisation of a hot dip galvanising process
    (2021-12-01) Dewa, Mendon; Nleya, Bakhe; Dzwairo, Bloodless
    The dearth of energy sustainability is posing major challenges both locally and glob- ally. Galvanising furnaces are categorised as dominant consumers of electricity in the overall galvanising industry. Relatively little research has been carried out concerning energy optimisation through sequencing or scheduling algorithms by way of enhancing the performance of galvanising lines. In this regard, the research centres on evaluating overall energy performance in this industry. The research sought to introduce an opti- mal energy optimisation-scheduling algorithm for a hot dip galvanising process. A DMAIC based methodology was presented for the provisioning of a structured prob- lem-solving process for improving energy efficiency in a galvanising process. Its framework embraces an energy sustainability assessment of four batch hot-dip galva- nising plants. Four energy minimisation opportunities were identified and quantifiable energy and cost savings, as well as avoided carbon dioxide emissions were derived from the analysis of one of the plants. Production or zinc used was identified as the main driver for electricity consumption for Plant 1, while the number of dips per month, amount of zinc used, and ambient temperature conditions were identified as the rele- vant variables for developing a regression model for Plant 2. The amount of zinc used and ambient temperature conditions were found to be the relevant variables for Plant 3. The derived regression model for Plant 4 was based on the amount of zinc used and ambient temperature conditions. The energy performance indicators for a galvanising plant were established through a comparison of actual and expected consumption, energy intensity index, cumulative sum, and specific energy consumption. A bi-objective GECOS algorithm was further introduced to reduce the total energy consumption as well as makespan. The simula- tion results revealed that the GECOS algorithm outperforms McNaughton’s algorithm, Shortest Processing Time Algorithm, and Integer Linear Programming algorithms on minimising makespan on parallel processing machines. The key contributions to the body of knowledge from the study include a unique eval- uation of electrical energy consumption by a hot-dip galvanising plant, development of an energy consumption baseline and performance indices, and the developed novel bi-objective GECOS algorithm that considers reducing total energy consumption by the process tanks as well as makespan. Future research work may focus on hybrid genetic algorithm-artificial immune system scheduling tools that would derive synergy from the advantages of both algorithms to improve energy performance.