Due to the non-convex characteristic of the power system, it may be difficult for power generators to recover costs by following the system operators. Therefore, independent system operators have introduced discriminatory supplementary payments as incentive measures. In this context, convex hull pricing serves as an integrated solution, capable of markedly reducing such additional payouts. For the convex hull pricing problem, we propose a distributed solution method. This algorithm is based on Dantzig–Wolfe decomposition and Benders decomposition. According to the characteristics of different units, the model is decomposed into a master problem and a group of independent subproblems, and the consensus ADMM method is used to solve the master problem. The convex hull pricing problem can still be solved using this method when the data is stored separately or when the independent agents responsible for each unit wish to protect their information privacy. While ensuring the confidentiality of each unit’s information, high-quality solutions can still be obtained with high efficiency. By comparing the numerical results with those of the other three convex hull pricing algorithms, it is evident that our algorithm can obtain high-quality solutions.
Liu et al. (2026) studied this question.