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

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Title: Risk averse optimal operation of a virtual power plant using two stage stochastic programming
Authors: Tajeddini, Mohammad Amin
Rahimi-Kian, Ashkan
Soroudi, Alireza
Permanent link: http://hdl.handle.net/10197/6116
Date: 14-Aug-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
Copyright (published version): 2014 Elsevier
Keywords: VPP;Two-stage stochastic programming;Risk;CVaR;Scenario based modelling;Uncertainty
DOI: 10.1016/j.energy.2014.06.110
Language: en
Status of Item: Peer reviewed
Appears in Collections:Electrical and Electronic Engineering Research Collection

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