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A stochastic market-clearing model using semidefinite relaxation

E. F. Álvarez, J.C. López, P.P. Vergara, J.J. Chavez, M.J. Rider

13th PowerTech Conference, Milán (Italia). 23 junio 2019


Resumen:
This paper proposes a two-stage stochastic market clearing (SMC) model based on a semidefinite programming (SDP) relaxation. The SMC model aims at determining the day-ahead schedule (DA) and the real-time (RT) balance settlement that minimize the total expected production cost. The network capacity constraints are considered in the proposed model through an AC power flow formulation, while the uncertainty in the renewable-based generation is taking into account using a set of stochastic scenarios. In order to solve the proposed non-linear programming model, a SDP relaxation is used. An illustrative example (3-bus test system) and the IEEE Reliability 24-bus test system are used to show the effectiveness and accuracy of the proposed model. Results shown that the proposed SDP relaxation introduce a negligible error, when compared with the solution after solving the original non-linear model.


Palabras clave: Stochastic market-clearing, AC optimal power flow, semidefinite relaxation.


DOI: DOI icon 10.1109/PTC.2019.8810418

Fecha de publicación: junio 2019.



Cita:
E. F. Álvarez, J.C. López, P.P. Vergara, J.J. Chavez, M.J. Rider, A stochastic market-clearing model using semidefinite relaxation, 13th PowerTech Conference - PowerTech 2019, Milán (Italia). 23-27 Junio 2019.


    Líneas de investigación:
  • Modelos de mercados eléctricos con alta penetración de generación renovable
  • Modelos de mercados de electricidad y gas natural

IIT-19-143A

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