Examining the Utilization of Clean Energies for Sustainable Development: A Case Study of Saudi Arabia, United Arab Emirates, and Qatar

Jamaledini, Ashkan and Bayat, Alireza (2024): Examining the Utilization of Clean Energies for Sustainable Development: A Case Study of Saudi Arabia, United Arab Emirates, and Qatar.

Abstract

In recent years, sustainable development has emerged as a cornerstone of global development efforts, emphasizing ecological preservation alongside economic growth. Developed countries have long prioritized sustainable practices, integrating environmental conservation, resource management, and social equity into their policies. This commitment addresses critical global challenges, including climate change and resource depletion, while striving to balance growth and ecological preservation. Oil-rich nations in the Persian Gulf, such as Saudi Arabia, the UAE, and Qatar, are also advancing sustainability by diversifying their economies and reducing reliance on fossil fuels. These countries are leveraging their renewable energy potential to transition towards cleaner energy systems. Saudi Arabia's Vision 2030 aims to generate 50% of its energy from renewable sources by 2030, with significant investments in solar and wind projects. The UAE leads with initiatives like the Mohammed bin Rashid Solar Park and Barakah Nuclear Power Plant, while Qatar invests heavily in solar technologies. These efforts highlight how clean energy technologies and sustainable strategies foster innovation, environmental preservation, and economic diversification. By adopting renewable energy, Gulf nations exemplify how sustainability can drive a greener future. Together, global efforts underscore the shared responsibility of ensuring a sustainable world for future generations.

• Item Type: MPRA Paper
• Language: English
• Keywords: Sustainable development, Development studies, Environmental preservation; Developed countries; Policy frameworks; National agendas; Environmental protection.
• Subjects: A - General Economics and Teaching > A1 - General Economics; A - General Economics and Teaching > A1 - General Economics > A10 - General; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q0 - General; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q40 - General; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q47 - Energy Forecasting

References

[1] Kavousi-Fard, Abdollah, et al. "Digital Twin for mitigating solar energy resources challenges: A Perspective Review." Solar Energy 274 (2024): 112561.

[2] Wang, Boyu, et al. "AI-enhanced multi-stage learning-to-learning approach for secure smart cities load management in IoT networks." Ad Hoc Networks 164 (2024): 103628.

[3] Razmjoui, Pouyan, , et al. "A blockchain-based mutual authentication method to secure the electric vehicles’ TPMS." IEEE Transactions on Industrial Informatics 20, no. 1 (2023): 158-168.

[4] Lumin Shi, Edmund Ntom UdembaImed Boukhris, “Mediating role of finance amidst resource and energy policies in carbon control: A sustainable development study of Saudi Arabia”, Resources Policy7 April 2023

[5] Anwar A. Gasim, Paolo AgnolucciVincenzo De Lipsis, “Modeling final energy demand and the impacts of energy price reform in Saudi Arabia”, Energy Economics24 February 2023

[6] Ghazala Aziz, Suleman Sarwar, Mohd Saeed Khan, “Influence of tech-industry, natural resources, renewable energy and urbanization towards environment footprints: A fresh evidence of Saudi Arabia”, Resources Policy5 May 2023

[7] Tarifa Almulhim, Mohammed Al Yousif, “Scenario analysis for renewable energy investment using a hybrid framework: A case study in Saudi Arabia”, Renewable Energy Focus26 June 2023

[8] Mohammadi, Hossein, et al. "A Deep Learning‐to‐learning Based Control system for renewable microgrids." IET Renewable Power Generation (2023).

[9] Esapour, Khodakhast, et al. "A novel energy management framework incorporating multi‐carrier energy hub for smart city." IET Generation, Transmission & Distribution 17, no. 3 (2023): 655-666.

[10] Moeini, Amirhossein, et al. "Artificial neural networks for asymmetric selective harmonic current mitigation-PWM in active power filters to meet power quality standards." IEEE Transactions on Industry Applications (2020).

[11] Tahmasebi, Dorna, et al. "A security-preserving framework for sustainable distributed energy transition: Case of smart city." Renewable Energy Focus 51 (2024): 100631.

[12] Wang, Boyu, et al. "Cybersecurity enhancement of power trading within the networked microgrids based on blockchain and directed acyclic graph approach." IEEE Transactions on Industry Applications 55, no. 6 (2019): 7300-7309.

[13] Jafari, Mina, et al. "A survey on deep learning role in distribution automation system: a new collaborative Learning-to-Learning (L2L) concept." IEEE Access 10 (2022): 81220-81238.

[14] Mohammadi, Mojtaba, et al. "Effective management of energy internet in renewable hybrid microgrids: A secured data driven resilient architecture." IEEE Transactions on Industrial Informatics 18, no. 3 (2021): 1896-1904.

[15] Ashkaboosi, Maryam, et al. "An optimization technique based on profit of investment and market clearing in wind power systems." American Journal of Electrical and Electronic Engineering 4, no. 3 (2016): 85-91.

[16] Dabbaghjamanesh, Morteza, et al. "A novel distributed cloud-fog based framework for energy management of networked microgrids." IEEE Transactions on Power Systems 35, no. 4 (2020): 2847-2862.

[17] Khalid Mohammed Almatar, “Towards sustainable green mobility in the future of Saudi Arabia cities: Implication for reducing carbon emissions and increasing renewable energy capacity”, Heliyon24 February 2023

[18] Lamya Albraheem, Lama AlAwlaqi, “Geospatial analysis of wind energy plant in Saudi Arabia using a GIS-AHP technique”, Energy Reports24 May 2023

[19] Hashem A. AlNemer, Besma Hkiri, Kais Tissaoui, “Dynamic impact of renewable and non-renewable energy consumption on CO2 emission and economic growth in Saudi Arabia: Fresh evidence from wavelet coherence analysis”, Renewable Energy5 April 2023

[20] Rida Waheed, Suleman Sarwar, Majid Ibrahim Alsaggaf, “Relevance of energy, green and blue factors to achieve sustainable economic growth: Empirical study of Saudi Arabia”, Technological Forecasting and Social Change2 December 2022

[21] Badr Lami, Ahmad Alferidi, Sami Ben Slama, “Peer-to-peer energy exchange, autonomy goals, and financial rewards in Saudi Arabia households”, Ain Shams Engineering JournalAvailable online 10 July 2023

[22] Dabbaghjamanesh, Morteza, et al. "Stochastic modeling and integration of plug-in hybrid electric vehicles in reconfigurable microgrids with deep learning-based forecasting." IEEE Transactions on Intelligent Transportation Systems 22, no. 7 (2020): 4394-4403.

[23] Tajalli, Seyede Zahra, et al. "DoS-resilient distributed optimal scheduling in a fog supporting IIoT-based smart microgrid." IEEE Transactions on Industry Applications 56, no. 3 (2020): 2968-2977.

[24] Dabbaghjamanesh, Morteza, et al. "A novel two-stage multi-layer constrained spectral clustering strategy for intentional islanding of power grids." IEEE Transactions on Power Delivery 35, no. 2 (2019): 560-570.

[25] Mohammadi, Hossein, et al. "Ai-based optimal scheduling of renewable ac microgrids with bidirectional lstm-based wind power forecasting." arXiv preprint arXiv:2208.04156 (2022).

[26] Kavousi-Fard, Abdollah, Morteza Dabbaghjamanesh, Tao Jin, Wencong Su, and Mahmoud Roustaei. "An evolutionary deep learning-based anomaly detection model for securing vehicles." IEEE Transactions on Intelligent Transportation Systems 22, no. 7 (2020): 4478-4486.

[27] Dabbaghjamanesh, Morteza, et al. "Deep learning-based real-time switching of hybrid AC/DC transmission networks." IEEE Transactions on Smart Grid 12, no. 3 (2020): 2331-2342.

[28] Razmjouei, Pouyan, et al. "DAG-based smart contract for dynamic 6G wireless EVs charging system." IEEE Transactions on Green Communications and Networking 6, no. 3 (2022): 1459-1467.

[29] Kazemi, Behzad, et al. "IoT-enabled operation of multi energy hubs considering electric vehicles and demand response." IEEE Transactions on Intelligent Transportation Systems 24, no. 2 (2022): 2668-2676.

[30] Kavousi-Fard, Abdollah, et al. "IoT-based data-driven fault allocation in microgrids using advanced µPMUs." Ad Hoc Networks 119 (2021): 102520.

[31] Dabbaghjamanesh, Morteza, et al. "High performance control of grid connected cascaded H-Bridge active rectifier based on type II-fuzzy logic controller with low frequency modulation technique." International Journal of Electrical and Computer Engineering 6, no. 2 (2016): 484.

[32] Khazaei, Peyman, et al. "A high efficiency DC/DC boost converter for photovoltaic applications." International Journal of Soft Computing and Engineering (IJSCE) 6, no. 2 (2016): 2231-2307.

[33] Khazaei, Peyman, et al. "Applying the modified TLBO algorithm to solve the unit commitment problem." In 2016 World Automation Congress (WAC), pp. 1-6. IEEE, 2016.

[34] Dabbaghjamanesh, Morteza, et al. "A new efficient stochastic energy management technique for interconnected AC microgrids." In 2018 IEEE Power & Energy Society General Meeting (PESGM), pp. 1-5. IEEE, 2018.

[35] Taherzadeh, Erfan, et al. "New optimal power management strategy for series plug-in hybrid electric vehicles." International Journal of Automotive Technology 19 (2018): 1061-1069.

[36] Tajalli, Seyede Zahra, et al. "A secure distributed cloud-fog based framework for economic operation of microgrids." In 2019 IEEE Texas Power and Energy Conference (TPEC), pp. 1-6. IEEE, 2019.

[37] Dabbaghjamanesh, Morteza, et al. "Networked microgrid security and privacy enhancement by the blockchain-enabled Internet of Things approach." In 2019 IEEE Green Technologies Conference (GreenTech), pp. 1-5. IEEE, 2019.

[38] Ferdowsi, Farzad, et al. "Optimal scheduling of reconfigurable hybrid AC/DC microgrid under DLR security constraint." In 2019 IEEE Green Technologies Conference (GreenTech), pp. 1-5. IEEE, 2019.

[39] Fard, Abdollah Kavousi, et al. "Superconducting fault current limiter allocation in reconfigurable smart grids." In 2019 3rd International Conference on Smart Grid and Smart Cities (ICSGSC), pp. 76-80. IEEE, 2019.