Security and reliability constrained power management of virtual power plant considering ancillary services and energy markets models in smart grid

This study investigates the operation of a flexible renewable virtual power plant (VPP) with inverter-based system in a smart distribution network while considering the technical and economic objectives of the distribution system operator and maximizing the VPP’s participation in energy, reactive power, and reserve markets. A bi-level optimization framework is proposed in which the upper level minimizes a weighted combination of voltage security, power loss, and expected energy not supplied by incorporating AC optimal power flow and network security constraints. The lower level maximizes the VPP’s profit subject to inverter capabilities and operational and reserve constraints. The bi-level problem is transformed into a single-level formulation using the Karush-Kuhn-Tucker conditions. To address uncertainties in load, renewable generation, mobile storage characteristics, market prices, and equipment availability, a hybrid stochastic-robust optimization framework is employed. Equipment availability is modeled stochastically to accurately assess reliability, whereas the remaining uncertainties are handled through robust optimization to improve resilience against forecasting errors. The proposed approach is distinguished by its inverter-based VPP model, integration of multiple technical performance indices, hybrid uncertainty modeling, and coordinated use of flexible resources for energy management. Simulation results demonstrate that the proposed framework enhances both network performance and VPP profitability. Compared with conventional load flow analysis, it significantly improves operational performance, voltage security, and reliability through coordinated inverter control. Even under the worst-case uncertainty level of 17%, the proposed method achieves improvements of approximately 36–43%, 8.6%, and 90.5%, respectively.