Title of article
Risk constrained self-scheduling of hydro/wind units for short term electricity markets considering intermittency and uncertainty
Author/Authors
Moghimi Ghadikolaei، نويسنده , , Hadi and Ahmadi، نويسنده , , Abdollah and Aghaei، نويسنده , , Jamshid and Najafi، نويسنده , , Meysam، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2012
Pages
10
From page
4734
To page
4743
Abstract
In view of the intermittency and uncertainty associated with both the electricity production sector of restructured power system and their competitive markets, it is necessary to develop an appropriate risk managing scheme. So that it is desirable to trade-off between optimum utilization of intermittent generation resources (i.e. renewable energy resources), uncertain market prices and related risks in order to maximize participantsʹ benefits and minimize the corresponding risks in the multi-product market environment. The main goal of this paper is to investigate risk management by introducing a novel multi-risk index to quantify expected downside risk (EDR) which is caused by both the wind power and market price uncertainties. Value-at-Risk (VaR) method is used to assess the mentioned risk issue by the proposed weighted EDR, so that an optimal trade-off between the profit and risk is made for the system operations. Also, the roulette wheel mechanism is employed for random market price scenario generation wherein the stochastic procedure is converted into its respective deterministic equivalents. Moreover, the autoregressive integrated moving average (ARIMA) model is employed to characterize the stochastic wind farm (WF) generation by predetermined mean level and standard deviation of wind behavior as well as temporal correlation. The problem is formulated as a mixed-integer stochastic framework for a hydro-wind power system scheduling and tested on a generation company (GENCO).
Keywords
Hydro-wind power system , Renewable energy resources , risk assessment , ARIMA processes , Expected downside risk , hydro scheduling , stochastic programming
Journal title
Renewable and Sustainable Energy Reviews
Serial Year
2012
Journal title
Renewable and Sustainable Energy Reviews
Record number
1501288
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