Computing and Informatics

Currently, renewable energy sources (RES) have been widely deployed in the smart grid, especially in the active distribution network (ADN). However, the inherent uncertainty of the renewable energy output significantly impacts the economy of the ADN operation. It is suggested that the utilization of flexible resources (FR) can effectively even out the uncertainty of RES. Nevertheless, the non-marketization of FR may prevent the emerging park-level integrated energy systems (PIES), important entities in ADN, from sufficiently offering their potential flexibilities. Therefore, this paper presents a two-stage local flexibility trading mechanism for motivating multi-PIESs to provide their flexible resources (PFR) to improve the operational flexibility of ADN. The first stage determines the dispatching plan of ADN according to the day-ahead forecasted values of RES. The second stage enables the multi-PIESs to trade their PFR with ADN to adjust the day-ahead dispatching plan in real-time to correct the forecasted errors of RES. In terms of implementing the two stages, firstly, the capacity of PFR with involving the adjustable tie line power of PIES is quantified using an optimization-based assessment model. Secondly, based on the change of the operation cost before and after the sale of PFR, a pricing model of PFR is established. And then, to determine the trading amount of PFR, a real-time ADN economic dispatching model with the network constraints is further constructed, which aims at minimizing the comprehensive operation cost. Afterwards, a marginal-based method is employed to obtain the clearing price of PFR. Finally, to ensure the feasibility of the trading results and to provide the accurate dispatching strategies for the PFR trading in next time interval, a rolling dispatch for the multi-PIESs is carried out. Case studies demonstrate that the presented flexibility trading mechanism significantly reduces the power curtailment of ADN, the operation costs of ADN and the multi-PIESs.