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Reliability Based Min-Max Regret Stochastic Optimization Model for Capacity Market with Renewable Energy and Practice in China

  • Runzhao Lu
  • , Tao Ding*
  • , Boyu Qin
  • , Jin Ma
  • , Rui Bo
  • , Zhaoyang Dong
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Capacity market is a long-term clearing model to coordinate the traditional thermal generation and the renewable energy generation, which minimizes the total capacity cost of traditional generation, while satisfying the operational constraints and reliability requirement. Furthermore, to address the uncertainties in the long-term optimal decision, min-max regret is employed to find the optimal solution under the worst regret, generating several representable scenarios that can help generation companies to understand how these scenarios would impact on the future generation planning. Finally, a decomposition method is proposed to solve this reliability based min-max regret stochastic optimization model by bisection. The test results on one regional grid in China show the effectiveness of the proposed model. © 2018 IEEE.
Original languageEnglish
Pages (from-to)2065-2074
JournalIEEE Transactions on Sustainable Energy
Volume10
Issue number4
Online published26 Oct 2018
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes

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
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Research Keywords

  • Capacity market
  • min-max regret
  • reliability evaluation
  • renewable energy
  • stochastic programming

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