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Risk averse optimal operation of a virtual power plant using two stage stochastic programming

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  • Tajeddini, Mohammad Amin
  • Rahimi-Kian, Ashkan
  • Soroudi, Alireza

Abstract

VPP (Virtual Power Plant) is defined as a cluster of energy conversion/storage units which are centrally operated in order to improve the technical and economic performance. This paper addresses the optimal operation of a VPP considering the risk factors affecting its daily operation profits. The optimal operation is modelled in both day ahead and balancing markets as a two-stage stochastic mixed integer linear programming in order to maximize a GenCo (generation companies) expected profit. Furthermore, the CVaR (Conditional Value at Risk) is used as a risk measure technique in order to control the risk of low profit scenarios. The uncertain parameters, including the PV power output, wind power output and day-ahead market prices are modelled through scenarios. The proposed model is successfully applied to a real case study to show its applicability and the results are presented and thoroughly discussed.

Suggested Citation

  • Tajeddini, Mohammad Amin & Rahimi-Kian, Ashkan & Soroudi, Alireza, 2014. "Risk averse optimal operation of a virtual power plant using two stage stochastic programming," Energy, Elsevier, vol. 73(C), pages 958-967.
    • Handle: RePEc:eee:energy:v:73:y:2014:i:c:p:958-967
    DOI: 10.1016/j.energy.2014.06.110
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    References listed on IDEAS

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