Medium-and-long-term hidden random scheduling method for cascade hydropower station of combined wind power photovoltaic power station

Abstract

The invention relates to a medium-and-long-term hidden random scheduling method for a cascade hydropower station of a combined wind power photovoltaic power station, and belongs to the technical fieldof hybrid energy system scheduling. According to the method, monthly runoff uncertainty is considered, and a scheduling model is fitted by using a radial basis function neural network through adoption of an implicit hidden random scheduling method. The model reasonably considers the wind power photovoltaic uncertainty and the impact of the reverse peak regulation phenomenon on the power grid, reserves sufficient standby for short-term wind and light uncertainty in medium and long-term scheduling, and allocates enough daily electric quantity to cope with the pressure of the reverse peak regulation phenomenon on the peak regulation of the power grid. The model result of the method is greatly different from the result without consideration of wind power photovoltaic short-term standby, the wind power photovoltaic output and the cascade hydropower station optimal scheduling information can be effectively utilized, and a reference basis with high operability is provided for scientific decision making of the cascade hydropower station under the condition of large-scale new energy grid connection.

Description

Technical field [0001] The invention belongs to the technical field of hybrid energy system dispatching, and specifically relates to a medium and long-term implicit random dispatching method for cascade hydropower stations combined with wind power photovoltaic power stations. Background technique [0002] In order to achieve sustainable development goals, renewable new energy sources such as wind power and photovoltaic power account for an increasing proportion of the power system. Compared with traditional energy, the uncertainty of the output of wind farms and photovoltaic power plants makes it difficult to predict the time and magnitude of peaks and troughs of new energy output. In addition, the intermittent nature of new energy leads to fluctuations in output. To accommodate more intermittent energy, the power system needs to provide more system flexibility. How to use traditional dispatchable energy to provide flexible resources for the power system urgently needs to be stud...

AI Technical Summary

Problems solved by technology

In cascade reservoir scheduling, there is often a non-linear relationship between decision variables and decision factors, and due to the influence of hydraulic connections between reservoirs, each reservoir has many decision factors to choose from. brings difficulties

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