Risk constrained self-scheduling of hydro/wind units for short term electricity markets considering intermittency and uncertainty

被引:63
作者
Ghadikolaei, Hadi Moghimi [2 ]
Ahmadi, Abdollah [3 ]
Aghaei, Jamshid [1 ]
Najafi, Meysam [2 ]
机构
[1] Shiraz Univ Technol, Dept Elect & Elect Engn, Shiraz, Iran
[2] Iran Univ Sci & Technol, Dept Elect Engn, Tehran, Iran
[3] Islamic Azad Univ, Parsian Branch, Dept Elect Engn, Parsian, Iran
关键词
ARIMA processes; Expected downside risk; Hydro scheduling; Hydro-wind power system; Renewable energy resources; Risk assessment; Stochastic programming; TIME-SERIES MODELS; WIND-SPEED; STOCHASTIC SECURITY; POWER; GENERATION; PRODUCER; ENERGY;
D O I
10.1016/j.rser.2012.04.019
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 participants' 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). (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4734 / 4743
页数:10
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