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May 13, 2026Scientific Reports2 citationsOpen Access

Economic environmental-based flexible energy scheduling in smart grid with renewable units and integrated system considering vehicles refueling stations

MAMohammad K.K. AlabdullhHKHiba Abdulkareem KhamisEAEhsan Akbari

Key Points

  • The main aim is to reduce energy losses in a smart distribution network while integrating renewable energy and refueling stations.
  • Developed a framework addressing AC power flow, operational constraints, and environmental considerations.
  • Utilized scenario-based stochastic optimization to manage uncertainties in load demand and renewable generation.
  • Integrated electric vehicle charging and hydrogen storage systems for coordinated energy management.
  • Reduced voltage deviations by approximately 10.2%, enhancing voltage security.
  • Decreased power losses by about 32.8%, improving overall system efficiency.
  • Lowered peak load capacity by around 38.3% compared to traditional load flow analyses.

Abstract

This study explores sustainable energy management approaches for a smart distribution network that combines multiple infrastructures, such as electric vehicle charging stations, hydrogen refueling facilities for fuel cell vehicles, and renewable energy systems integrated with hydrogen storage. These components are managed in a coordinated manner to satisfy both operational requirements and security criteria defined by the distribution system operator. A key feature of the hydrogen storage unit is its dual functionality, as it not only stores electrical energy but also supplies hydrogen to end users. The primary objective is to reduce overall energy losses within the distribution system. To accomplish this, the research considers several important factors, including AC power flow modeling, grid voltage operational and security constraints, system flexibility, environmental restrictions, operational characteristics of electric vehicles charging and hydrogen stations, and performance models of renewable energy systems coupled with hydrogen storage. Furthermore, the proposed framework accounts for uncertainties related to load demand, renewable generation, and variations in the number of electric vehicles by applying a scenario-based stochastic optimization technique. The findings demonstrate significant enhancements in both system performance and security. In particular, the proposed method decreases voltage deviations, power losses, and peak load capacity by approximately 24.4%, 32.8%, and 38.3%, respectively, compared to conventional load flow analyses. Moreover, voltage security within the network is improved by nearly 10.2%, confirming the efficiency of the proposed integrated energy management strategy.

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Cite This Study

Alabdullh et al. (2026) studied this question.

synapsesocial.com/papers/6a0415aa79e20c90b444567ehttps://doi.org/10.1038/s41598-026-52241-z
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