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

Carlos Roldán-Blay, Vladimiro Miranda, Leonel Carvalho, Carlos Roldán-Porta

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Article number7111
JournalSustainability (Switzerland)
Volume11
Issue number24
DOIs
Publication statusPublished - 1 Dec 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

Keywords

  • Cross entropy
  • Microgrid planning
  • Optimal generation location
  • Optimal generation sizing
  • Particle swarm optimization
  • Sustainable development
  • Sustainable generation

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