Risk averse optimal operation of a virtual power plant using two stage stochastic programming
| Autor: | Alireza Soroudi, Ashkan Rahimi-Kian, Mohammad Amin Tajeddini |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Risk
Scenario based modelling Mathematical optimization Wind power Two-stage stochastic programming business.industry CVAR Mechanical Engineering Risk measure Uncertainty VPP Building and Construction Pollution Industrial and Manufacturing Engineering Stochastic programming Profit (economics) Virtual power plant Expected shortfall General Energy Economics Electrical and Electronic Engineering business CVaR Integer programming Civil and Structural Engineering |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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