Bidding Strategy for Distribution System Operator Considering V2G Operation in Electricity Market Based on Two Stage Robust Optimization

Distribution system operators (DSOs) occupy a pivotal role in electricity markets, particularly within policydriven environments such as China, attributed to their robust resilience, customer loyalty, and high value-added capabilities. Nevertheless, DSOs have incurred considerable financial losses due to an escalation in aggregate forecast deviations precipitated by demand-side enterprises. To address this issue, a two-stage robust optimization model with a min-max-min structure has been devised to maximize DSO revenue under the uncertainty of conventional load within the electricity market. This model integrates conventional loads, electric vehicles, and incentivebased demand response, with the objective of enhancing the operational efficacy of DSO. A crucial parameter, termed the budget of uncertainty, has been introduced to adjust the conservatism level of the robust solution against modeled uncertainties. The optimization model is decomposed into a master problem and a subproblem, both featuring a mixedinteger linear structure, and is resolved using the column-andconstraint generation algorithm and strong duality theory. Numerical case studies validate the superiority of the proposed method over deterministic optimization approaches, particularly as prediction errors increase. The resulting day-ahead bidding strategy exhibits enhanced robustness and a heightened capacity to mitigate the risks associated with real-time price fluctuations.