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

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Author(s)
Tajeddini, Mohammad Amin 
Rahimi-Kian, Ashkan 
Soroudi, Alireza 
Uri
http://hdl.handle.net/10197/6116
Date Issued
14 August 2014
Date Available
07T09:06:35Z November 2014
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.
Type of Material
Journal Article
Publisher
Elsevier
Journal
Energy
Volume
73
Issue
2014
Start Page
958
End Page
967
Copyright (Published Version)
2014 Elsevier
Keywords
  • VPP

  • Two-stage stochastic ...

  • Risk

  • CVaR

  • Scenario based modell...

  • Uncertainty

DOI
10.1016/j.energy.2014.06.110
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Electrical and Electronic Engineering Research Collection
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