Multi-agent benefit equilibrium method for virtual power plant based on double-layer game model

By constructing a two-layer game model and using blockchain technology, the dynamic evolution of strategies and distribution of interests among multiple stakeholders in a virtual power plant are simulated. This solves the problems of interest balance and protocol execution among multiple stakeholders in a virtual power plant, and achieves systematic, dynamic interest balance and reliable scheduling plans.

CN122134057AActive Publication Date: 2026-06-02STATE GRID SHANGHAI INTEGRATED ENERGY SERVICE CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
STATE GRID SHANGHAI INTEGRATED ENERGY SERVICE CO LTD
Filing Date
2026-04-30
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing technologies struggle to simulate the dynamic processes of multi-stakeholder interactions in short- and long-term interactions within virtual power plants, making it impossible to achieve fair distribution of benefits and reliable execution of agreements. Furthermore, they lack effective handling of uncertainties surrounding renewable energy.

Method used

A two-layer game model-based approach is adopted to construct an upper-layer asymmetric evolutionary game and a lower-layer stochastic Stackelberg game. By combining the fuzzy Shapley value method and blockchain smart contracts, the dynamic evolution of strategies and the distribution of benefits among multiple parties are simulated, and the execution of the protocol is ensured through blockchain.

Benefits of technology

It achieves long-term stability and balance of interests among multiple stakeholders in the virtual power plant, reduces the risk of scheduling plans, and improves the reliability and fairness of protocol execution.

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Abstract

This invention discloses a method for balancing the interests of multiple stakeholders in a virtual power plant based on a two-layer game model, belonging to the field of power system optimization and operation technology. The method includes the following steps: constructing an upper-layer asymmetric evolutionary game model, introducing strategy entropy and habituation coefficients, simulating the long-term cooperative strategy evolution of stakeholders such as distributed power sources, flexible loads, and energy storage systems, and outputting an evolutionarily stable strategy; inputting the evolutionarily stable strategy as a modulation parameter into a lower-layer stochastic Stackelberg game model, using a typical scenario method to handle uncertainty, and optimizing short-term scheduling plans and internal electricity prices; allocating cooperative surplus based on fuzzy Shapley values, with staker membership determined by historical cooperative tendencies; verifying execution using blockchain smart contracts, and implementing automatic punishment through a dynamic penalty function linking "deviation degree and credit score". This method achieves dynamic and reliable interest balance among multiple stakeholders on both long and short-term scales, significantly improving the stability and economy of the virtual power plant alliance.
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