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Optimal Generation Scheduling with Dynamic Profiles for the Sustainable Development of Electricity Grids

Author

Listed:
  • Carlos Roldán-Blay

    (Institute for Energy Engineering, Universitat Politècnica de València, Camino de Vera, s/n, edificio 8E, escalera F, 5ª planta, 46022 Valencia, Spain)

  • Vladimiro Miranda

    (Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), R. Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal
    Faculty of Engineering of the University of Porto, R. Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal)

  • Leonel Carvalho

    (Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), R. Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal)

  • Carlos Roldán-Porta

    (Institute for Energy Engineering, Universitat Politècnica de València, Camino de Vera, s/n, edificio 8E, escalera F, 5ª planta, 46022 Valencia, Spain)

Abstract

The integration of renewable generation in electricity networks is one of the most widespread strategies to improve sustainability and to deal with the energy supply problem. Typically, the reinforcement of the generation fleet of an existing network requires the assessment and minimization of the installation and operating costs of all the energy resources in the network. Such analyses are usually conducted using peak demand and generation data. This paper proposes a method to optimize the location and size of different types of generation resources in a network, taking into account the typical evolution of demand and generation. The importance of considering this evolution is analyzed and the methodology is applied to two standard networks, namely the Institute of Electrical and Electronics Engineers (IEEE) 30-bus and the IEEE 118-bus. The proposed algorithm is based on the use of particle swarm optimization (PSO). In addition, the use of an initialization process based on the cross entropy (CE) method to accelerate convergence in problems of high computational cost is explored. The results of the case studies highlight the importance of considering dynamic demand and generation profiles to reach an effective integration of renewable resources (RRs) towards a sustainable development of electric systems.

Suggested Citation

  • Carlos Roldán-Blay & Vladimiro Miranda & Leonel Carvalho & Carlos Roldán-Porta, 2019. "Optimal Generation Scheduling with Dynamic Profiles for the Sustainable Development of Electricity Grids," Sustainability, MDPI, vol. 11(24), pages 1-26, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7111-:d:296888
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    References listed on IDEAS

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    Cited by:

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    2. Viktor Koval & Viktoriia Khaustova & Stella Lippolis & Olha Ilyash & Tetiana Salashenko & Piotr Olczak, 2023. "Fundamental Shifts in the EU’s Electric Power Sector Development: LMDI Decomposition Analysis," Energies, MDPI, vol. 16(14), pages 1-22, July.
    3. Masoud Dashtdar & Aymen Flah & Seyed Mohammad Sadegh Hosseinimoghadam & Hossam Kotb & Elżbieta Jasińska & Radomir Gono & Zbigniew Leonowicz & Michał Jasiński, 2022. "Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony," Sustainability, MDPI, vol. 14(11), pages 1-26, May.
    4. Alaa Farah & Hamdy Hassan & Alaaeldin M. Abdelshafy & Abdelfatah M. Mohamed, 2020. "Optimal Scheduling of Hybrid Multi-Carrier System Feeding Electrical/Thermal Load Based on Particle Swarm Algorithm," Sustainability, MDPI, vol. 12(11), pages 1-21, June.

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