Uncertainty-averse TRANSCO planning for accommodating renewable energy in CO2 reduction environment

Chunyu Zhang, Yi Ding, Qi Wang, Yusheng Xue, Jacob Østergaard

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Abstract

The concern of the environment and energy sustainability requests a crucial target of CO2 abatement and results in a relatively high penetration of renewable energy generation in the transmission system. For maintaining system reliability and security, the transmission company (TRANSCO) has to make strategic planning to handle the uncertainty challenges from the intermittent renewable energy resources. In this paper, a stochastic multi-period multi-objective transmission planning (MPMOTP) model is proposed to reduce correlated uncertainties from renewable energy generation, conventional generation, demand-side variations, market price volatility, and transmission configuration. Three objectives, i.e. social CO2 reduction benefit, energy purchase and network expansion cost and power delivery profit, are optimized simultaneously by a developed two-phase multi-objective particle swarm optimization (MOPSO) method. The feasibility and effectiveness of the proposed uncertainty-averse MPMOTP model have been verified by the IEEE 24-bus test system.
Original languageEnglish
JournalJournal of Modern Power Systems and Clean Energy
Volume3
Issue number1
Pages (from-to)24–32
Number of pages9
ISSN2196-5625
DOIs
Publication statusPublished - 2015

Bibliographical note

© The Author(s) 2015. This article is published with open access at
Springerlink.com

Keywords

  • CO2 reduction
  • Renewable energy
  • Uncertainty
  • Multi-objective planning
  • TRANSCO
  • MOPSO

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