A method for optimizing long-term trading electricity in a wind farm and related device

By establishing a multi-scenario power optimization model in wind farms, considering the levelized cost of electricity over the entire life cycle of energy storage, and with the optimization objective of maximizing average revenue, the uncertainty of long-term contract power allocation in wind farms is resolved, thereby improving the economic benefits and market transaction efficiency of wind farms.

CN122178437APending Publication Date: 2026-06-09CHINA ELECTRIC POWER RESEARCH INSTITUTE CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA ELECTRIC POWER RESEARCH INSTITUTE CO LTD
Filing Date
2026-02-24
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

The existing methods for allocating medium- and long-term contract power in wind farms do not take into account the characteristics of wind-storage power stations with built-in energy storage. This results in power allocation being limited by the randomness of wind power output and the anti-peak-shaving characteristics, making it impossible to allocate power reasonably to high-yield periods. Furthermore, the existing methods do not consider the cost factors of energy storage deployment, leading to market congestion and reduced wind farm revenue.

Method used

A method for optimizing the medium- and long-term trading volume of wind farms is adopted. By obtaining the output and price curves of wind farms, a multi-scenario volume optimization model is established, taking into account the cost per kilowatt-hour of energy storage over its entire life cycle. The optimization objective is to maximize the average revenue of wind farms under various scenarios. The model is solved by combining particle swarm optimization algorithm or genetic algorithm to realize the shifting and allocation of electricity at different time periods.

Benefits of technology

It significantly improves the economic benefits of wind farms, avoids the problem of pursuing short-term gains while ignoring the loss of energy storage equipment, makes power allocation more in line with actual operating scenarios, solves the problem of market congestion, and fully leverages the ability of energy storage to regulate the volatility of wind power.

✦ Generated by Eureka AI based on patent content.

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Abstract

This invention belongs to the field of power market optimization and dispatching technology, and discloses a method and related apparatus for optimizing medium- and long-term trading volume of wind farms. The method includes: acquiring the wind farm output prediction curve and the predicted electricity price curve; solving the wind farm power optimization model based on the wind farm output prediction curve and the predicted electricity price curve to obtain an optimized power allocation scheme for the wind farm in medium- and long-term contracts and the spot market; the wind farm power optimization model aims to maximize the average revenue of the wind farm under various scenarios; the calculation of the average revenue under various scenarios considers the levelized cost of electricity (LCOE) of energy storage charging and discharging throughout its entire lifecycle. The technical solution disclosed in this invention can be used to optimize the allocation of medium- and long-term contract power in the wind farm power market. It considers the optimization capability of wind farms in allocating their own power after the installation of energy storage, and can significantly improve the economic benefits of wind farms.
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