The application discloses an
algorithm electricity collaborative
demand response bidding decision method and
system based on
large model training tasks, and relates to the technical field of power
system dispatching. First, the
power grid invitation
signal is received and analyzed to construct an invitation
signal feature set. Then, the state of the intelligent
algorithm center is collected, and the computing power shadow price of each
large model training task is calculated; the
state space and action space are constructed according to the distribution characteristics of the invitation
signal feature set and the computing power shadow price, the PPO
algorithm is used to solve the optimal bid, and the optimal bidding strategy is output. If the bidding is successful, the adjusted task set is selected in the order from low to high according to the computing power shadow price of each
large model training task, and hierarchical control is performed as needed. Through the hierarchical response mechanism and cost consideration, when interruption must be performed, the large model training task that has just completed the "checkpoint saving" is automatically locked and suspended through the computing power shadow price sorting, the
impact on the training progress is minimized, and the safety of the
model parameters is ensured.