Uncertainty-output virtual power plant participates in multi-electricity market considering the improved Shapley value distribution method
Yi Shang, Xiaolan Li, Tianqi Xu, Lin Cui
Abstract
The trading mechanism for virtual power plants to participate in the electricity market is imperfect, accompanied by uncertain output of distributed energy resources, and has difficulty in achieving reasonable profit distribution. This study proposes a bi-level optimization framework for virtual power plant participation in multiple electricity markets considering the post-transaction profit distribution and the uncertain output of wind turbines and photovoltaics. In this framework, the virtual power plant incorporates wind turbine, photovoltaic, energy storage system and pumped storage power station, and participates in the day-ahead energy, frequency modulation and peaking markets. Subsequently, a ladder Shapley value distribution method is proposed as a means of achieving a reasonable profit distribution based on the capacity participating in the day-ahead market. Finally, an emergency reserve interval decision method is proposed for evaluating the uncertain output of wind turbine and photovoltaic. The proposed framework is analyzed and discussed. The results demonstrate that the proposed framework enhances the profitability of all market participants by an average of 3.83%, while concurrently reducing the wind turbine and photovoltaic uncertainty penalty costs by approximately 26.4% and 24.5%, respectively. • A bi-level optimization framework is constructed for virtual power plant participation in multiple electricity markets. • A ladder Shapley value distribution method is designed for application to profit distribution after the day-ahead market. • An emergency reserve interval decision based on wind turbine and photovoltaic prediction intervals is established.