A multi-objective optimization approach to risk-constrained energy and reserve procurement using demand response

N.G. Paterakis, M. Gibescu, A.G. Bakirtzis, J.P.S. Catalao

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
1 Downloads (Pure)

Abstract

Large-scale integration of wind generation in power systems increases the need for reserve procurement in order to accommodate its highly uncertain nature, a fact that may overshadow its environmental and economic benefits. In this study, a joint energy and reserve day-ahead market structure based on two-stage stochastic programming is presented. The developed model incorporates explicitly the participation of demand side resources in the provision of load following reserves. Since a load that incurs a demand reduction may need to recover this energy in other periods, different types of the load recovery effect are modeled. Furthermore, in order to evaluate the risk associated with the decisions of the system operator and to assess the effect of procuring and compensating load reductions, the conditional value-at-risk (CVaR) metric is employed. To solve the resulting multi-objective optimization problem, a new approach based on an improved variant of the epsilon-constraint method is adopted. This study demonstrates that the proposed approach to risk management presents conceptual advantages over the commonly used weighted sum method.

Original languageEnglish
Pages (from-to)3940-3954
JournalIEEE Transactions on Power Systems
Volume33
Issue number4
DOIs
Publication statusPublished - 1 Jul 2018

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Multiobjective optimization
Stochastic programming
LSI circuits
Risk management
Mathematical operators
Recovery
Economics

Keywords

  • augmented epsilon-constraint method
  • conditional value-at-risk
  • day-ahead market
  • demand side reserves
  • Load management
  • load recovery
  • Power transmission lines
  • Procurement
  • risk management
  • Spinning
  • stochastic optimization
  • Stochastic processes
  • wind power
  • Wind power generation

Cite this

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abstract = "Large-scale integration of wind generation in power systems increases the need for reserve procurement in order to accommodate its highly uncertain nature, a fact that may overshadow its environmental and economic benefits. In this study, a joint energy and reserve day-ahead market structure based on two-stage stochastic programming is presented. The developed model incorporates explicitly the participation of demand side resources in the provision of load following reserves. Since a load that incurs a demand reduction may need to recover this energy in other periods, different types of the load recovery effect are modeled. Furthermore, in order to evaluate the risk associated with the decisions of the system operator and to assess the effect of procuring and compensating load reductions, the conditional value-at-risk (CVaR) metric is employed. To solve the resulting multi-objective optimization problem, a new approach based on an improved variant of the epsilon-constraint method is adopted. This study demonstrates that the proposed approach to risk management presents conceptual advantages over the commonly used weighted sum method.",
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A multi-objective optimization approach to risk-constrained energy and reserve procurement using demand response. / Paterakis, N.G.; Gibescu, M.; Bakirtzis, A.G.; Catalao, J.P.S.

In: IEEE Transactions on Power Systems, Vol. 33, No. 4, 01.07.2018, p. 3940-3954 .

Research output: Contribution to journalArticleAcademicpeer-review

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