Two-Stage Chance-Constrained Stochastic Thermal Unit Commitment for Optimal Provision of Virtual Inertia in Wind-Storage Systems

  • Tao Ding
  • , Ziyu Zeng
  • , Ming Qu
  • , Joao P.S. Catalao
  • , Mohammad Shahidehpour

Research output: Contribution to journalArticlepeer-review

131 Scopus citations

Abstract

The frequency security problem becomes a critical concern in power systems when the system inertia is lowered due to the high penetration of renewable energy sources (RESs). A wind-storage system (WSS) controlled by power electronics can provide the virtual inertia to guarantee the fast frequency response after a disturbance. However, the provision of virtual inertia might be affected by the variability of wind power generation. To address this concern, we propose a two-stage chance-constrained stochastic optimization (TSCCSO) model to find the optimal thermal unit commitment (i.e., economic operation) and the optimal placement of virtual inertia (i.e., frequency stability) in a power grid using representative power system operation scenarios. An enhanced bilinear Benders decomposition method is employed with strong valid cuts to effectively solve the proposed optimization model. Numerical results on a practical power system show the effectiveness of the proposed model and solution method.

Original languageEnglish
Article number9321704
Pages (from-to)3520-3530
Number of pages11
JournalIEEE Transactions on Power Systems
Volume36
Issue number4
DOIs
StatePublished - Jul 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Bilinear Benders decomposition
  • Chance-constrained stochastic programming
  • Renewable energy
  • Virtual inertia

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