Abstract:

To fully tap the flexible scheduling potential of distributed resources and address the volatility challenges brought by the large-scale integration of new energy into the distribution networks, this study proposes a distribution locational marginal price (DLMP) signal-driven orientated inner approximation (OIA)-based aggregation optimization scheduling method for distributed resources in distribution networks. Firstly, the aggregation direction is guided by minimizing the operating cost, and a small amount of feasible region space is selectively sacrificed during the OIA aggregation process to obtain higher-quality solutions, which overcomes the limitation of existing maximum inner approximation-based aggregation methods that pursue the maximization of feasible regions while ignoring the optimality of scheduling objectives. Meanwhile, a bi-level cooperative operation optimization framework between distribution network operators and load aggregators is proposed: the upper-level distribution network operator conducts the optimization scheduling with the goal of minimizing the total operation cost, including the power purchase cost of the distribution network and the wind/solar curtailment costs, and calculates the DLMP through Lagrange relaxation, which reflects the supply-demand balance status and operating costs of the distribution network from both spatial and temporal dimensions; the lower-level load aggregator receives the DLMP signal and updates the power consumption plans of distributed resources such as electric vehicles, variable-frequency air conditioners, and user-side energy storage within the cluster feasible region obtained by OIA aggregation, aiming to minimize the power consumption cost of agent users. The two parties use the DLMP signals as the medium for cooperative optimization, ultimately achieving the dual goals of secure and economic operation of distribution network and tapping the flexible potential of distributed resources. Case studies based on the IEEE 33-bus system show that the proposed method effectively guides the balances load distribution of the distribution network, reduces the power consumption cost of users represented by load aggregators, and lowers the network loss, node voltage deviation, and operating cost of the distribution network.

Key words: new distribution network, distributed resources, aggregation optimization, orientated inner approximation, distribution locational marginal price, bi-level optimization