A flexibility-oriented bidding strategy for virtual power plants incorporating local energy communities: A bi-level stochastic-robust methodology

Recent increases in flexibility requirements for power systems with high penetration of renewable energy sources (RESs) highlight the substantial potential of market mechanisms to unlock customer flexibility. However, market-based frameworks inherently involve conflicting objectives among players and face significant challenges in coordinating demand-side flexibility under uncertainty, where the virtual power plant (VPP) concept can offer surplus benefits to various players. This paper proposes a risk-aware bidding and pricing strategy for VPPs to enable market-based flexibility provision concerning the cost and availability of distributed energy resources (DERs), which fully reveals the role of local energy communities (LECs). To this end, a novel bi-level stochastic-robust method is developed that optimizes bidding strategy for VPP aggregators in both the day-ahead (DA) energy and flexibility markets while managing risk to reach acceptable levels. In the proposed structure, the VPP manages energy trading and exploits the locational flexibility of resources to maximize its profit at the upper level. In contrast, the energy cost of the participating LECs is minimized at the lower level based on dynamic retail prices. A two-stage stochastic-robust approach is used to cope with the uncertainties associated with the DERs and risk of bidding strategy. The proposed model has been formulated mathematically as a mixed integer linear programming (MILP) problem, ensuring the globally optimal solution is obtained. Through several numerical studies using IEEE standard test systems, the obtained results show that the flexible robust strategy bidding is profitable while reducing the risk for VPP, considering the community manager’s preference.