Hierarchical multi-market coordination of virtual power plants via multi-factor differentiated bidding

With the increasing participation of distributed energy resources and the growing importance of carbon and flexibility services, virtual power plants (VPPs) require market bidding and revenue-allocation mechanisms that reflect heterogeneous operating characteristics. Conventional uniform bidding cannot adequately represent differences in device cost, carbon emissions, storage intertemporal value, and peak-shaving capability. This study therefore proposes a hierarchical market–VPP coordination framework based on multi-factor differentiated bidding. The market-clearing layer determines energy procurement and clearing outcomes according to system supply–demand conditions, resource bids, and peak-shaving requirements. Given these market outcomes, the VPP-response layer optimizes internal resource dispatch, portfolio profit, and subsequent bids. The two layers are coordinated through sequential feedback of bidding and clearing information. Device output, storage opportunity cost, stepwise carbon burden, carbon-capture effects, and technically feasible peak-shaving capacity are incorporated into resource-specific bids, while a two-stage allocation mechanism transfers bidding competitiveness and system-support contributions to internal resources. Compared with the single-level benchmark, the proposed framework reduces market procurement cost by 3.43% while improving VPP profit and controllable-resource revenue. Under the complete multi-factor bidding scenario, total CO 2 emissions decrease by 19.52%. In addition, differentiated bidding improves the revenue position of controllable units such as gas turbines in the tested cases. Profile-perturbation and scalability analyses further indicate consistent economic, low-carbon, and computational performance under the tested conditions.