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Optimum Predictive Modelling, Holistic Integration and Analysis of Energy Sources Mix for Power Generation and Sustainability in Developing Economies : = A Case of the Nigerian Power System.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Optimum Predictive Modelling, Holistic Integration and Analysis of Energy Sources Mix for Power Generation and Sustainability in Developing Economies :/
其他題名:	A Case of the Nigerian Power System.
作者:	Ibrahim, Hanif Auwal.
面頁冊數:	1 online resource (163 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-08, Section: A.
Contained By:	Dissertations Abstracts International85-08A.
標題:	Sustainability. -
電子資源:	click for full text (PQDT)
ISBN:	9798381457131

Optimum Predictive Modelling, Holistic Integration and Analysis of Energy Sources Mix for Power Generation and Sustainability in Developing Economies : = A Case of the Nigerian Power System.
Ibrahim, Hanif Auwal.

Optimum Predictive Modelling, Holistic Integration and Analysis of Energy Sources Mix for Power Generation and Sustainability in Developing Economies :A Case of the Nigerian Power System. - 1 online resource (163 pages)

Source: Dissertations Abstracts International, Volume: 85-08, Section: A.

Thesis (Ph.D.)--University of Pretoria (South Africa), 2023.

Includes bibliographical references

Nigeria being the most populous black nation on earth, with a high birth rate and growing industrial, commercial, transportation, and agricultural activities has been caught up with the dilemma of insufficient power supply which has left the nation lagging in terms of socio-economic development among sister nations. With an aggressive transition to renewables all over the world to meet energy obligations and mitigate greenhouse gas (GHG) emissions, Nigeria is left with no choice but to join the transition in a bid to uphold the Sustainable Development Goals 7 & 13 (clean and affordable energy & climate action). The power generation mix of Nigeria is largely dependent on natural gas hence, largely in conflict with the mentioned SDGs. Despite these sources of electricity being far fetched from meeting the growing demand for power usage, the non-renewable energy source are noted for creating a significant level of environmental pollution, global warming, and health-related risks. As the need to bring down the rising annual global temperatures to 1.5 degrees in various Conference of Parties (COP) grow in awareness, it's obvious that Nigeria has a significant role to play towards the actualization of this mission.The ever-increasing demand for electricity, as well as its impact on the environment, necessitates expanding the generation mix by utilizing indigenous sustainable energy sources. Power generation planning that is sustainable and efficient must meet various objectives, many of which conflict with one another in which multi-objective optimization is one of the techniques used for such optimization problems. Using multi-objective optimization, a model for Nigeria's power supply architecture was developed to integrate indigenous energy sources for a sustainable power generation mix. The model has three competing objectives i.e reducing power generating costs, reducing CO2 emissions and increasing jobs. To solve the multi-objective optimization problem, the Hybrid Structural Interaction Matrix (HSIM) technique was utilized to compute the weights of the three objectives: minimization of costs, minimization of CO2 emissions, and maximization of jobs creation. The General Algebraic Modeling System (GAMS) was used to solve the multi-objective optimization problem. According to the simulations, Nigeria could address its power supply shortage and generate up to 2,100 TWh of power by 2050. Over the projected period, large hydropower plants and solar PV will be the leading option for Nigeria's power generation mix. Furthermore, power generation from solar thermal, incinerator, nuclear, gas plants, combined plants, and diesel engine will all be part of the power supply mix by 2050. In terms of jobs expected to be created, about 2.05 million jobs will be added by 2050 from the construction and operation of power generation plants with CO2 emissions attaining 266 MtCO2 by 2050. The cost of power generation is expected to decline from a maximum of 36 billion US$ in 2030 to 27.1 billion US$ in 2050. Findings in this research concludes that Nigeria can meet its power supply obligations by harnessing indigenous energy sources into an optimal power supply mix.Furthermore, to establish the basis for the power generation mix projection, system drivers responsible for the rising demand of electricity and reduce pace of transition to renewable energy sources were identified from a systems thinking point of view after which they were prioritized using the HSIM concept. Also, the impact of renewable energy on power accessibility, affordability and environmental sustainability was investigated using the system dynamics approach. It was obtained that factors including urbanization, industrialization, agricultural/commercial services growth rates, and pollution are the primary reasons for the rising demand for electricity. The slow transition to renewables in Nigeria is directly linked to the absence of subsidies and government grants, non-existing or few renewable energy financing institutions, scarcity of experienced professionals, barriers to public awareness and information, and ineffective government policies. The outcome from the system dynamics approach on accessibility, affordability, and environmental sustainability of the electricity supply are thought to be enhanced if indeed the country's plan of using 36% renewables in the mix of power sources is to be met.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381457131Subjects--Topical Terms:

793436
Sustainability.
Index Terms--Genre/Form:

554714
Electronic books.

Optimum Predictive Modelling, Holistic Integration and Analysis of Energy Sources Mix for Power Generation and Sustainability in Developing Economies : = A Case of the Nigerian Power System.
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