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Two-stage robust market clearing procedure model for day-ahead energy and reserve auctions of wind–thermal systems

Author

Listed:
  • Vieira, Matheus Pereira
  • Martins, André Christóvão Pio
  • Soler, Edilaine Martins
  • Balbo, Antonio Roberto
  • Nepomuceno, Leonardo

Abstract

The progressive increase of clean and renewable energy sources is demanding new market policies and structures. Novel market clearing procedures (MCP) for day-ahead energy market are necessary to account for inherent uncertainties associated with these sources. In this paper we propose a novel two-stage robust MCP model for wind–thermal systems which co-optimizes energy and reserves, where the uncertainties in wind power sources (WPS) are handled by robust optimization and a detailed representation is adopted for thermal units, transmission system and reserves. An approach based on the dualization and Benders’ decomposition methods is proposed for solving the robust MCP model. Also, a model for simulating the impact of commitment decisions obtained by the MCP model is developed which evaluates the expected number/level of infeasibility in real time operation. This model allows for evaluating the effective real time security and reliability of the MCP decisions, associated with the uncertainties in WPS. The robust MCP approach is compared to the reserve adjustment approach generally adopted by system operators, using the IEEE 24-bus test system. The results have shown that the proposed robust approach assures higher levels of real time security and reliability, with just slight reductions in the social welfare function, even with high levels of wind power penetration.

Suggested Citation

  • Vieira, Matheus Pereira & Martins, André Christóvão Pio & Soler, Edilaine Martins & Balbo, Antonio Roberto & Nepomuceno, Leonardo, 2023. "Two-stage robust market clearing procedure model for day-ahead energy and reserve auctions of wind–thermal systems," Renewable Energy, Elsevier, vol. 218(C).
    • Handle: RePEc:eee:renene:v:218:y:2023:i:c:s0960148123011916
    DOI: 10.1016/j.renene.2023.119276
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