Multi-timescale optimal scheduling of active distribution network based on source-grid-load-storage coordination
With the integration of source-grid-load-storage, to lower the impact of prediction error on distribution network scheduling, this paper proposes a multi-timescale optimization scheduling strategy of active distribution network with source-grid-load-storage coordination. First, the response model of electric vehicles participating in dispatching is built and classified according to the operating characteristics of flexible loads to adapt to multiple time scales. On the day-ahead time scale, a dispatch plan is made with the lowest operating cost of the distribution network. On the intraday scale, with thorough consideration of achieving higher economy and increasing consumption of new energy, the rolling optimization is employed to revise the day-ahead scheduling plan with large forecast error. In the real-time phase, combined with intraday planning, a fine-tuning model with minimal output deviation is built. Finally, the entropy weight method is employed to empower each target, and Yalmip+Cplex is used to seek the model solution, demonstrating its superior economy.
source-grid-load-storagedemand responsescroll optimizationmulti-timescaleactive distribution network
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