Method for improving transmission capacity of power grid with multiple wind farms based on optimized configuration of SSSC

CN116646939BActive Publication Date: 2026-11-03NORTH CHINA ELECTRIC POWER UNIV +4
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Patent Information

Application Number
CN202310651365.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-06-02
Publication Date
2026-11-03
Estimated Expiration
2043-06-02

AI Technical Summary

Technical Problem

The uncertainty and correlation of wind farm output make power system planning and operation control complex. Traditional methods are difficult to achieve flexible adjustment, and the transmission capacity of some lines is not fully utilized, affecting the flexibility, safety and stability of the power grid.

Method used

The SSSC optimization configuration method is adopted. By determining the wind speed probability model and generating typical operating scenarios, the SSSC node power injection model and power flow transfer entropy index are established. The multi-objective optimization model and genetic algorithm are used to optimize the SSSC site selection and capacity determination, so as to achieve optimized control of line power flow.

Benefits of technology

It has increased the available transmission capacity between regions, alleviated transmission congestion, enhanced the flexibility and security of the power grid, and guided trading decisions in the electricity market.

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Abstract

The application discloses a power transmission capacity improving method based on SSSC optimal configuration containing multiple wind farms, and belongs to the technical field of electrical engineering, and particularly relates to the following steps: determining a probability model of wind speed and fan output; generating an initial scene, reducing the scene, and extracting representative typical operation scenes; establishing a SSSC node power injection model and a power flow transfer entropy index, taking the power flow transfer entropy index as an indirect optimization target to select the SSSC; determining a base state power flow based on an economic dispatching model, defining the power flow transfer entropy index to represent ATC, establishing a multi-objective optimization model, and solving the model by using a non-dominated sorting genetic algorithm with elitist strategy; and sorting a Pareto solution set to determine an optimal configuration line of the SSSC; and establishing a SSSC capacity determination model to solve and determine control parameters of the SSSC under each scene, and the maximum operation capacity of the SSSC under each scene is the configuration capacity. The application realizes the improvement of the power transmission capacity between regions, relieves power transmission congestion, and improves the flexibility of the power grid.
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