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Optimal Energy Scheduling in Smart Electrical Systems Considering Economic and Emission Objective Functions

Author

Listed:
  • Y. Romani

    (Universidad Central de Venezuela, Sierra Maestra, Facultad de Ciencias)

  • Rustem Shichiyakh

    (Kuban State Agrarian University Named After I.T. Trubilin)

  • Zokir Mamadiyarov

    (Termez University of Economics and Service
    Alfraganus University
    Tashkent State University of Economics)

  • Bobur Mirzayev

    (Alfraganus University)

  • Shokhjakhon Akhmedov

    (Urgench State University)

  • Saidislom Rashidov

    (Mamun University)

  • Nurbek Matyakubov

    (Urgench Innovation University)

  • I. B. Sapaev

    (” “Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University
    University of Tashkent for Applied Science
    Western Caspian University)

  • Islambek Norbotaev

    (Denov Institute of Entrepreneurship and Pedagogy)

  • Elyor Saitov

    (University of Tashkent for Applied Sciences)

  • Sobir Parmanov

    (National University of Uzbekistan)

Abstract

The relationship between energy and social sustainability, along with economic and environmental factors, has prompted energy operators to conduct various investigations into energy systems. The energy system represents a contemporary approach to energy generation, utilizing different types of energy including plug-in electric vehicles and renewable energy sources in smart electrical distribution networks. This paper focused on optimal participation of the plug-in electric vehicles and renewable energy sources in the smart electrical distribution networks for optimal energy generation considering economic and environmental factors. The participation of the plug-in electric vehicles and renewable energy sources in the electrical distribution networks is modelled for minimization of emission polluting and energy generation costs in power plants. The emission polluting and energy generation costs are modelled as multi-objective functions optimization. The particle swarm optimization algorithm is used for solving proposed approach. To demonstrate the practicality and efficiency of the suggested method, several case studies are examined. The method is evaluated on a 33-bus distribution system. The analysis of the outcomes shows that the recommended smart grid framework optimizes the utilization of renewable energy sources while effectively lowering fuel costs and emissions in power plants. The participation of the PEVs and renewable energies alongside power plant leads to minimization of the costs and emission pollution of the units by 2.91% and 7.36%, respectively.

Suggested Citation

  • Y. Romani & Rustem Shichiyakh & Zokir Mamadiyarov & Bobur Mirzayev & Shokhjakhon Akhmedov & Saidislom Rashidov & Nurbek Matyakubov & I. B. Sapaev & Islambek Norbotaev & Elyor Saitov & Sobir Parmanov, 2025. "Optimal Energy Scheduling in Smart Electrical Systems Considering Economic and Emission Objective Functions," SN Operations Research Forum, Springer, vol. 6(4), pages 1-23, December.
    • Handle: RePEc:spr:snopef:v:6:y:2025:i:4:d:10.1007_s43069-025-00547-5
    DOI: 10.1007/s43069-025-00547-5
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