Purchase strategy and pricing mechanism design for risk-limiting balancing market

In response to the challenges posed by the stochastic output from highly penetrated renewable generation, this paper introduces a risk-limiting balancing market aimed at maintaining system stability and mitigating real-time imbalances. The motivation for this work stems from the need to effectively accommodate the diverse risk attitudes of balance responsible parties (BRPs). By incorporating chance constraints, our framework enables both risk-neutral and risk-averse BRPs to operate within acceptable risk parameters. To foster collaboration among BRPs, we propose a collaborative pricing scheme based on total imbalances, which incentivizes cooperative trading and effectively manages the variability inherent in renewable generation. Additionally, we develop a bi-level optimization framework structured as a one-leader-multiple-followers Stackelberg game. In this model, the Transmission System Operator (TSO) sets pricing parameters, while BRPs optimize their purchasing strategies in response to these signals. To achieve stable equilibrium results considering the uncertainties of prices and generation, we employ advanced algorithms based on the Initialization Auxiliary and Pessimistic Trajectory Truncated Gradient Method (IAPTT-GM). This comprehensive approach not only addresses the uncertainties associated with renewable generation and electricity prices but also enhances the overall reliability of the balancing market. Numerical studies validate the effectiveness of these algorithms, offering a robust solution to the integration challenges posed by renewable energy sources.