Selection of a Critical Time Scale of Real-Time Dispatching for Power Systems With High Proportion Renewable Power Sources

The power prediction error of uncertain renewable energy sources (URESs) affects the power balance of a power grid. In the power systems with high proportion renewable power sources (PSHPRPSs), automatic generation control (AGC) cannot accommodate the day-ahead power prediction error. The dispatching control system (DCS) of PSHPRPSs adds real-time dispatching links to modify the day-ahead dispatching plan so that the grid power error is within the range of AGC accommodation. This paper proposes a critical time scale (CTS) selection algorithm based on time aggregation characteristics for real-time dispatching of PSHPRPSs and calculates the annual CTS of real-time dispatching of power grids. The uncertainty function is used to describe the relationship between the prediction error of the URESs and the prediction lead time. The total uncertainty function is calculated based on the time aggregation characteristics and is used to select the annual CTS of real-time dispatching. The proposed algorithm quantitatively describes the relationship between the CTS and the operation proportion of URESs and also AGC accommodation capacity. The calculated annual CTS not only ensures the power balance of the power grid, but also avoids the daily change of the CTS. Using the data of URESs in the Irish power grid, the feasibility of the proposed method was verified. The research results of this paper are helpful to accommodate the day-ahead power prediction error of URESs and maintain the safe operation of power grid.