Resource Modeling, Market Participation, and Coordinated Operation of Virtual Power Plants: A Review

Virtual power plants coordinate distributed energy resources to provide market services, but the value of a scheduling strategy depends on consistency between physical capabilities, market commitments, uncertainty treatment, and participant incentives. This review examines resource modeling, coordinated market bidding, uncertainty-aware scheduling, benefit allocation, and distributed and learning-based implementation. The reviewed approaches are compared by their operating assumptions, information requirements, computational demands, and application limits. Three connections emerge. First, commitments across energy and ancillary-service markets must share the same resource, network, and delivery constraints; adding revenue streams alone does not establish realizable gains. Second, stochastic, robust, and distributionally robust formulations address different information and risk considerations, while rolling-horizon optimization provides a complementary updating framework. Third, the distributable surplus and the incentives for cooperation depend on the dispatch and cost assumptions used to calculate it. Application examples illustrate how these decisions interact. Research priorities include validated aggregate flexibility models, consistent settlement and degradation representations, calibrated out-of-sample risk assessment, and reproducible evaluation of scalable scheduling methods. The review provides conditional guidance for selecting compatible methods; heterogeneous simulation settings limit direct performance rankings and conclusions about field deployment.