面向虚拟电厂的电能量-备用联合交易模型以缓解裸卖风险

Unregulated naked selling of virtual power plants(VPPs)in day-ahead markets poses inherent risks to grid securi-ty and market fairness.This paper proposes a joint electricity-reserve trading model for VPPs as a strategic measure to miti-gate the negative impacts of naked selling.This model systemat-ically evaluates the economic advantages and risks of naked sell-ing,utilizing metrics such as user comfort and conditional val-ue at risk(CVaR).Furthermore,a sophisticated combination of a data-driven level-set fuzzy approach and advanced algo-rithms,including support vector quantile regression(SVQR)and kernel density estimation(KDE),is employed to quantify the uncertainties related to prices and reserve activation precise-ly.The results of case studies demonstrate that integrating de-fault penalties within the proposed trading model diminishes the overall revenue of VPPs engaging in naked selling,thereby serving as a robust decision for mitigating the adverse effects of the naked selling of VPPs.