Risk assessment by security-constrained unit commitment for hybrid wind-thermal by pair copula approach in reserve power market: a stochastic approach

作     者：Panda, Rajesh Tiwari, Prashant Kumar 

作者机构：NIT Silchar Elect Engn Silchar Assam India Motilal Nehru Natl Inst Technol Allahabad Elect Engn Dept Prayagraj UP India 

出 版 物：《IET GENERATION TRANSMISSION & DISTRIBUTION》 (IET发电，输电与配电)

年 卷 期：2020年第14卷第26期

页      面：6639-6649页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

主　　题：wind power plants power generation economics power markets power generation scheduling linear programming risk management power system security integer programming power generation dispatch thermal power stations hybrid power systems load (electric) profitability stochastic programming risk assessment reserve power market stochastic approach market participants bivariate pair copula-based security-constrained unit commitment economic dispatch wind power generations ancillary service market wind farms conditional value-at-risk optimal placement risk-based SCUCED model optimal bidding strategy profit GENCO independent system operator mixed integer linear programming Pareto tail factor bivariate marginal distribution modified IEEE 30 bus system ramp-down optimal reserve curves ramp-up optimal reserve curves 

摘      要：High volatility renewable penetration increases the security risk of the market participants. In order to ensure the security of the reserve market under uncertainties, the authors have proposed a novel optimal bidding strategy based on bivariate pair copula-based security-constrained unit commitment economic dispatch (SCUCED) for the generation companies (GENCOs) while considering the volatility of wind power generations and load variations under different (N - k) contingencies in ancillary service market. The expected profit of GENCOs are based on the ramp-up and ramp-down optimal reserve curves in each time interval are submitted to the independent system operator. The profit of wind farms is obtained and the risks due to uncertainties with wind farms are also analysed while participating in the reserve market. Conditional value-at-risk is considered for the optimal placement of wind farms in the network. The risk-based SCUCED model is solved by mixed integer linear programming. Moreover, a factor called joint Pareto tail factor has been also developed to provide information regarding the fat tails in the lower end of the bivariate marginal distribution of different GENCOs. The effectiveness of the proposed approach has been tested on a modified IEEE 30 bus system.