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Thursday, July 3, 2025

Electric Vehicles and Renewable Energy in Egypt

Electric Vehicles and Renewable Energy in Egypt
Electric Vehicles and Renewable Energy in Egypt



 Electric Vehicles and Renewable Energy: An Egyptian Study Offers Solutions to Electricity Grid Challenges


With the global expansion in reliance on electric vehicles and renewable energy sources, electricity grid operators face increasing challenges to ensure optimal operation and meet the growing demand for energy in a reliable and cost-effective manner.


In this context, a recent doctoral study at Benha University has proposed two innovative solutions to address these challenges, demonstrating the potential for significant savings in generation costs and improved smart grid management.


Researcher Mostafa Hassanein, in his doctoral thesis at the Department of Electrical Engineering, Faculty of Engineering, Benha University, addressed the issue of optimal operation of power generation units in light of the increasing reliance on renewable energy and the integration of electric vehicles. Hassanein presented two new approaches based on computational optimization algorithms to reduce costs and enhance grid operation efficiency.


Best Operating Scenarios


Dr. Mohamed Mounes explained that the study seeks to develop solutions to the technical challenges resulting from the instability of renewable energy sources and the irregular demand resulting from the expansion of electric vehicles. This is achieved through AOT technology and its improved version, IAOT, which enables optimal scheduling of generation units based on improved mathematical equations.


The study results show that both approaches can reduce operating costs by between 0.2% and 6.26% in most models, with savings reaching up to 5.6% in large systems with 80 to 100 generating units, reflecting their efficiency across networks of varying sizes and generation densities.


The study analyzed four case studies representing 12 realistic energy distribution scenarios, both during peak and low periods, and examined the reliance on renewable energy and electric vehicles. This enabled optimal operational decisions supported by key performance indicators, most notably the total daily cost and cost-effectiveness ratio.


Moanes emphasized that this type of computational modeling provides a powerful tool for decision-makers in the energy sector to identify the best operating scenarios that achieve sustainability and reduce reliance on conventional sources, without compromising grid stability.


Future Recommendations


In remarks to the Energy Platform, Professor of Electrical Power Systems Dr. Muhammad Mu'nis indicated that the study yielded several recommendations, most notably: The possibility of expanding the application of innovative AOT and IAOT algorithms to smart energy systems that incorporate storage solutions and emerging technologies such as green hydrogen.


Enhancing the ability of grids to absorb renewable energy and achieve greater demand balance by anticipating consumer behavior and reacting to changes in real time. Integrating new inference techniques to address intermittent energy sources, such as wind and solar, to achieve greater efficiency and sustainability.


The study revealed that the two proposed models are not only effective in terms of performance, but are also applicable in real time, enhancing the ability of grids to respond quickly and providing strong support to decision-makers in managing electrical grid operations amid accelerating energy transitions.


The study results also confirmed the applicability and superiority of the selected technologies in finding the best solutions, enabling decision-makers in the energy sector and electricity grid operators to achieve optimal economic outcomes and enhance the integration of renewable energy and electric vehicles into electricity grids.

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