Zhu Minghui / State Grid Shaanxi Electric Power Research Institute
Yang Meng / School of Electrical Engineering, Xi'an Jiaotong University
Chen Yajun / Power Transaction Center of Shaanxi Electric Power Company
Zhou Lei / School of Electrical Engineering, Xi'an Jiaotong University
Chen Danhui / Power Transaction Center of Shaanxi Electric Power Company
Jiang Yufeng / School of Electrical Engineering, Xi'an Jiaotong University
With the reform of power market and the large-scale grid connection of renewable energy, the operational risk assessment and risk suppression of the power market have received extensive attention. Taking the impact of renewable energy grid connection on the electricity market into account, this paper establishes an indicator system for the operational risks of power generation enterprises, power grid enterprises, electricity-sales companies and large users in the long-term electricity market, and evaluates their respective risk levels through AHP and fuzzy comprehensive evaluation. Moreover, considering the user-side demand response and double uncertainties in purchasing and selling businesses of electricity-sales companies, a comprehensive profit stochastic optimization model is presented in this paper, in which conditional value of risk (CVaR) methodology is utilized to measure the risks. Then, this paper puts forward risk suppression measures from the aspects of medium and long term contract trading, power futures, renewable energy binding traditional power generation and so on. Using test dataset, the proposed approach is applied to a case study to demonstrate the effectiveness of the proposed model and its satisfactory impact on the risk assessment and suppression of the long-term power market.