Distributed robust optimization strategy for multi-energy virtual power plant clusters.

ABSTRACT: As renewable energy penetration continues to rise, the demand for coordinated optimization of decentralized source-load-storage. Virtual power plant (VPP) addresses this need by aggregating and coordinating diverse resources. However, effective mechanisms for multi-agent VPP coordination remain limited. To address this, this paper proposes a distributed robust optimization strategy for multi-energy VPP clusters in high-altitude regions. This strategy combines a dual-norm uncertainty set with a Nash bargaining mechanism to coordinate multi-agent interactions and mitigate operational risks. First, addressing the integrated planning-operation problem for multi-energy VPPs, a two-stage distributed robust optimization model is established. The dual-norm uncertainty set characterizes scenario pr

SUBMITTER: Wang Z 

PROVIDER: S-EPMC12764923 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature