Achieving sustainable development goals (SDGs) in Africa through the Impact of renewable energy utilization and artificial intelligence.
UNITED NATIONS

Achieving sustainable development goals (SDGs) in Africa through the Impact of renewable energy utilization and artificial intelligence.

Enormous wind and solar power from North African countries, the Sahel and South Africa, geothermal from East Africa, hydro from Central and West Africa. Renewable Energy latent has not been tapped in a substantive amount.

The 17 sustainable development goals (SDGs) to transform our world:

GOAL 1: No Poverty

GOAL 2: Zero Hunger

GOAL 3: Good Health and Well-being

GOAL 4: Quality Education

GOAL 5: Gender Equality

GOAL 6: Clean Water and Sanitation

GOAL 7: Affordable and Clean Energy

GOAL 8: Decent Work and Economic Growth

GOAL 9: Industry, Innovation, and Infrastructure

GOAL 10: Reduced Inequality

GOAL 11: Sustainable Cities and Communities

GOAL 12: Responsible Consumption and Production

GOAL 13: Climate Action

GOAL 14: Life Below Water

GOAL 15: Life on Land

GOAL 16: Peace and Justice Strong Institutions

GOAL 17: Partnerships to Achieve the Goal

Africa is not left behind as many countries around the world are planning to reach 100% renewable energy use by 2050. In this context and due to the recent sharp increase in Renewable Energy utilization in the Africa energy mix along with its progressive impact on the Africa energy sector, the evaluation and investigation of its effect on achieving sustainable development goals (SDG) have not prospected sufficiently. There are 169 targets of the 17 SDGs agreed internationally in the sustainable development agenda 2030. ?Valuation of the emerging role of artificial intelligence (AI) for renewable energy utilization toward achieving SDGs should be explored in Africa. Renewable energy has a positive impact on achieving a lot of targets across all sustainable development goals (SDGs).

Artificial intelligence can help renewable energy enable the attainment of the substantive number of the 169 targets. However, with the current exponential growth of renewable energy share and artificial intelligence development and addressing certain present limitations, this impact may cover additional targets in the future. The exponential growth of renewable energy share and rapid evolution of artificial intelligence need to be accompanied through the requisite regulatory insight and technology regulation to cover additional targets in the future.

Introduction.

Issues concerning the utilization and supply of energy are related to global warming and environmental challenges, such as forest destruction, air pollution, acid precipitation, ozone depletion, greenhouse gases (GHGs), water and land use, wildlife loss, and radioactive emissions.

With the use of Renewable Energy sources in Africa, the environmental, economic, and social issues can be reduced. These options are considered to help achieve an environmentally sound technology; affordable electricity cost; job creation; improved health; community development, especially in Africa; no or little emission production of poisonous and exhaust gases, such as sulfur dioxide, carbon monoxide, and carbon dioxide.

The Artificial Intelligence applications and approaches for developing Renewable Energy include cost reduction, safety, and reliability improvement, strategies to reduce environmental and climate impacts, increase the energy efficiency, expand Renewable Energy market, improve integration of micro-grids (MG) and smart grid, produce more accurate predictions of Renewable Energy, and optimal operation of Renewable Energy sources?The Renewable Energy utilization and AI-based Renewable Energy have a role in the future of sustainability, either for long- or short-term.

Assessment on the impacts of Renewable Energy utilization toward achieving SDGs

AI use in Renewable Energy has a positive role and may act as an enabler toward achieving some of the 169 targets, commonly by technical enhancement, which can allow these existing limitations to be overcome. Renewable Energy projects are enhancing environmental impacts. For example, carbon dioxide gas elimination and climate change understanding within the world population and contribute toward achieving the related SDGs effectively.

AI mapping techniques should be used for Renewable Energy potential maps to predict the proper locations for the expansion of Renewable Energy source-based facilities and land protection. The optimized machine learning technique is used to enhance the battery-based Renewable Energy systems to reduce their degradation and environmental impact. Some studies have shown the genetic algorithm gives a good performance to find appropriate areas for the construction of wind turbines with negligible effects on forest, fauna, and flora, including migratory bird pathways.

Concerning AI role, the digital and intelligent energy systems, drawing on the ever-increasing data on energy demand and supply, identifying who needs energy and whom to supply it at the right time, in the right place, and at the lowest cost will be possible. Also, AI plays an important role in reducing cost according to smart scheduling based on the weather condition to guarantee the continuous power supply and enable consumers to respond to load management signals when operated under the supervision of a scheduling coordinator.

This year, a Kenyan team presented a paper during the 10th ITB international Geothermal Workshop 2021 on their ongoing study on Machine Learning applications on geothermal. Machine Learning Model for Energy Analysis of a Wellhead Geothermal Plant: A Case of Kenya. The results showed that machine learning can effectively be used in the performance prediction of wellhead geothermal single flash power plants. Embedding machine learning in a geothermal environment can improve operations.

Machine Learning

The continuous growth of Renewable Energy leads to the development of the industry which means creating more jobs and speeding up economic development. Renewable Energy development can have a positive and tangible impact on jobs because this energy is local and can generally be made accessible without heavy infrastructure being available. Renewable Energy-based remote teaching (schools and institutes electrified by Renewable Energy) would educate more students in underdeveloped African countries with improved performance.

AI could support the use of Smart Grids, which could increase the penetration of Renewable Energy in the system. The advancement of Renewable Energy can contribute toward achieving SDG 6 via the use of solar PV energy and/or hybrid Renewable Energy in pumping the water from the underground wells in the rural and desert areas and thus decreasing the number of people who suffer from water shortages.

The AI can also be used for managing the water pumping via an efficient way for irrigation systems using optimization methods, for example, fuzzy logic optimization to increase the efficient use of water and reduce water waste. The areas with the greatest water scarcity are generally off-grid, remote, and have high solar irradiation. Therefore, a standalone hybrid PV/wind energy system is an effective solution to continuously power a submersible water pump (underground well) to produce drinking water.

For SDG 11, the use of AI in smart cities is going to improve the cost-effectiveness of new and existing energy infrastructure and increase the quality of life.

The utilization and deployment of Renewable Energy offer economic opportunities from using direct labor from remote communities, local materials and enterprises, local owners, and local banks’ services. The jobs created due to Renewable Energy development are expected to compensate for the loss of jobs in sectors, such as the fossil fuels sector because the ones involved in the supply chain of Renewable Energy are typically more dispersed and labor-intensive than the traditional energy market.

Many studies have found that Renewable Energy will positively impact innovation, industry, and infrastructure (SDG 9). Concerning SDG 17, Renewable Energy may help in achieving some targets within this goal, such as strengthening domestic resource mobilization as Renewable Energy diversity of sources began to widespread application, in African countries.

AI, machine learning, and smart communication can be used to succeed in this harmonization effort to have unique standards and requirements concerning Renewable Energy integration around Africa.

The use of AI and related technologies enable smart grids, smart meters, and the Internet of Things (IoT) devices to interact. Such technology can help enhance energy management, energy efficiency, transparency, and the use of Renewable Energy sources.

Furthermore, the role of AI applications can cover different areas of Renewable Energy systems, such as forecasting, emission reduction, cost-minimizing, robust and smooth control, high power quality without fluctuation even when input is intermittent, expansion of novel technologies for the optimal production from available natural resources, awareness of the environment, enhanced energy management, distribution of energy, and energy delivery. For instance, an optimal scheduling controller that uses AI optimization reduced the cost and emission in a micro-grid system that consists of different Renewable Energy sources.

The accelerated deployment of Renewable Energy has been motivated primarily by a wide variety of goals (drivers), including advancing economic growth, enhancing the security of energy and access to electricity, and alleviating climate change.

The development of Renewable Energy resources is theoretically enough to generate electricity and then fill the current energy gap. In addition, the utilization of these renewable sources can contribute toward achieving many targets of the 17 SDGs and provide multiple long-term benefits, including job creation, energy security, economic prospects, environmental development, and global warming prevention.

For SDG goal 17, Renewable Energy will lead to stronger partnerships between Governments, civil society, the private sector, the United Nations system, and other actors, mobilizing all available resources which will contribute to environmental protection and sustainable development by mobilizing resources, sharing knowledge, promoting the creation and transfer of environmentally sound technologies, and building capacity. There is tremendous scope for making the existing financial system more sustainable by integrating the environmental dimension.

People-First Public-Private Partnership (PPP) will be key for delivering such. ImPPPact Global Alliance is already laying down the foundation for such PPP. Africa Project Finance Program is also building the capacity for Africa PPP professionals who will deliver successful Infrastructure projects through Project Finance. This will accelerate People-First PPP energy projects adoption in Africa.

The Renewable Energy strategic policy for Africa should cover four key aims: security of energy, social equity, economic benefits, and protection of the environment.

References.

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  10. UN SDG, 2019. Sustainable development goal 7 | SDG7 affordable and clean energy
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Kipkoech Philemon

Energy enthusiast // Graduate Mechanical and Production Engineer // AFYEL Alumni //

3 年

This's great

Africa Project Finance Program

Project structuring & modelling | Project Finance | Public Private Partnerships

3 年

What an insightful piece there Jesse Nyokabi! Thank you for highlighting the impact we are creating through the Africa Project Finance Program. Proud to have you as an alumnus of the Program!

Leon Gerard Vandenberg (万 利 民)

Director - Stichting Sunified Foundation - Sunified Group B.V.

3 年

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