Intelligent settlement system and method for short-term power transactions in an electricity spot market

By combining the Q-learning algorithm and the long short-term memory network algorithm with the intelligent settlement system, the settlement problem of the existing power trading system in complex and ever-changing scenarios has been solved. It has achieved accurate prediction and flexible settlement of power supply and demand and price fluctuations, ensuring the accuracy of settlement results and market adaptability.

CN121685116BActive Publication Date: 2026-07-24QINGDAO FANGTIAN TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
QINGDAO FANGTIAN TECH CO LTD
Filing Date
2025-12-08
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing short-term power trading systems and methods struggle to accurately grasp intraday and recent days' power supply and demand and price fluctuations when faced with complex and ever-changing power trading scenarios. The settlement process cannot flexibly respond to complex and ever-changing market conditions and lacks self-learning and dynamic adjustment capabilities, resulting in a disconnect between settlement results and actual market conditions.

Method used

An intelligent settlement system is adopted, including data acquisition, preprocessing, predictive analysis, dynamic adjustment factor generation, settlement strategy selection, and settlement module. The system uses the Q-learning algorithm to select the optimal settlement strategy, combines the long short-term memory network algorithm to predict power load and price fluctuations, and calculates the load change rate, output fluctuation coefficient, and subsidy change through the dynamic adjustment factor generation module to achieve self-learning and dynamic adjustment.

Benefits of technology

It can accurately predict short-term power load and price fluctuations, formulate economically reasonable settlement plans, flexibly respond to complex and ever-changing market conditions, and ensure that settlement results are accurately aligned with actual market conditions, thereby improving the efficiency and security of power resource allocation.

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Abstract

The application discloses an intelligent settlement system and method for short-term electricity transaction of a power spot market, and the method comprises the following steps: step one, data acquisition and preprocessing; step two, prediction analysis and output of a prediction result; step three, generation of a dynamic adjustment factor; step four, acquisition of an optimal settlement strategy and automatic settlement; and step five, generation of a settlement report and notification of both transaction parties. The long short-term memory network algorithm is adopted to predict power load and price fluctuation in a short term, data support is provided for short-term market trend prediction, and the method is favorable for assisting in formulating an economically reasonable settlement scheme. Through the introduction of the dynamic adjustment factor, the load change rate, the output fluctuation coefficient and the subsidy change amount are comprehensively considered, so that the settlement process can be flexibly adapted to complex and changeable market conditions. Through the self-learning and dynamic adjustment capability of the settlement system, the optimal settlement strategy can be adopted according to real-time market feedback in a short-term transaction scene, so that the settlement result is ensured to be closely matched with the actual market condition.
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Citation Information

Patent Citations

  • Power settlement method and device based on double-settlement framework, electronic equipment and medium

    CN117876004A

  • Rule engine-based intelligent configuration method for power transaction settlement strategy

    CN119671606A