What question did this study set out to answer?

This research aims to develop an optimal energy management strategy for integrating renewable energy into Alexandria's urban transportation system.

March 3, 2026Open Access

Reinforcement Learning-Based Energy Management for Sustainable Electrified Urban Transportation with Renewable Energy Integration: A Case Study of Alexandria, Egypt

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Authors

AEAmany El-ZONKOLY

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Implication

This case study shows the economic potential of renewable energy in urban transportation, suggesting improved efficiency in Alexandria's transit system.

Key Points

This research aims to develop an optimal energy management strategy for integrating renewable energy into Alexandria's urban transportation system.
Integration of photovoltaic systems and green hydrogen-powered turbines into the energy system.
Implementation of demand-side management for electric vehicle loads.
Modified multi-agent reinforcement learning approach to handle uncertainty in decision-making processes.
Simulation of economic impacts related to energy management strategies.
Achieved a 40.2% reduction in average daily energy consumption costs.
Demonstrated the economic benefits of integrating renewable energy sources into urban transportation.

Cite This Study

Amany El-ZONKOLY (2026) studied this question.

synapsesocial.com/papers/69a67eb2f353c071a6f0a18d https://doi.org/10.3390/su18052352

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Implication

This case study shows the economic potential of renewable energy in urban transportation, suggesting improved efficiency in Alexandria's transit system.

Reinforcement Learning-Based Energy Management for Sustainable Electrified Urban Transportation with Renewable Energy Integration: A Case Study of Alexandria, Egypt

Discussion

Member takes

Implication

Key Points

Cite This Study

Reinforcement Learning-Based Energy Management for Sustainable Electrified Urban Transportation with Renewable Energy Integration: A Case Study of Alexandria, Egypt

Discussion

Member takes

Implication

Key Points

Cite This Study

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