Bidding Strategy for Flexible Aggregation of Distributed Energy Resources

Efficient aggregation of distributed energy resources (DERs) can improves their market-participation efficiency, thereby enabling more effective responses to price and control signals and optimizing economic returns. This paper selects typical resources such as distributed photovoltaic (PV), diesel generators (DG), air-conditioning (AC) loads, and distributed energy storage, and establishes mathematical models to describe their individual feasible regions based on the operational characteristics. To enable efficient aggregation, the individual feasible regions of DERs are inner-approximated using a Zonotope-based model. By leveraging the convexity and additive properties of Zonotopes, the aggregation of DER feasible regions can be performed efficiently and accurately. Furthermore, considering the aggregated DERs participate in electricity market as the aggregator, a bi-level optimization model is developed to characterize the decision-making process of the distributed energy resources aggregators (DERA) and to derive its optimal bidding strategy. Simulations are conducted on a modified IEEE 39-bus test system. The results demonstrate that the proposed aggregation method significantly reduces computational complexity while maintaining accuracy. Moreover, the strategy-oriented bidding model allows the DERA to fully exploit the flexibility potential of DERs in response to price signals, thereby enhancing coordination and mutual support between distributed resources and the power grid.