A Stackelberg Game Framework for Energy Internet System by Operator Approach

This paper proposes a Stackelberg game framework for managing an Energy Internet System that integratesrenewable energy generation, energy conversion, and energy trading. The system comprises hubs controlled by competing energy companies, incorporating both external energy trading and peer-to-peer energy exchanges. It involves multiple stakeholders whose decisions are interdependent, creating challenges in decision-making. To tackle these challenges, we propose a networked Stackelberg game framework with two main objectives. First, from the energy companies' perspective, the companies make decisions by considering strategic interactions with other companies while accounting for the best responses of passive consumers within peer-to-peer constraints. Second, from the consumer side, consumers adjust their decisions based on their observations of the companies' strategies. The framework adopts a hierarchical decision-making structure in which energy companies act as leaders, formulating strategies that anticipate consumer demand responses, while competing within a Nash game. Meanwhile, consumer clusters, managed by demand management centers, modify their energy usage based on an incentive price mechanism. To search for the equilibrium, we develop an operator-theoretic approach that combines implicit gradient methods with proximal operator splitting techniques, and prove its convergence. Numerical studies and simulations on a combined IEEE 37-bus and gas source model with multiple energy hubs validate the model's effectiveness and the efficiency of the proposed algorithms. The results demonstrate the operational efficiency and strategic stability of the system, emphasizing the advantages of active market participation for both energy companies and consumers.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Network Science and Engineering
Published
2025-03-29
DOI
https://doi.org/10.1109/tnse.2025.3555604
Citations
4
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
2.92
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Stackelberg Game Framework for Energy Internet System by Operator Approach

Xiangjun Li, Peng Yi, Yue Chen, Jinlong Lei
4 citations
IEEE Transactions on Network Science and Engineering
Smart Grid Energy Management
2.92
article

A Stackelberg Game Framework for Energy Internet System by Operator Approach

Xiangjun Li, Peng Yi, Yue Chen, Jinlong Lei
article en
4 citations

Abstract

This paper proposes a Stackelberg game framework for managing an Energy Internet System that integratesrenewable energy generation, energy conversion, and energy trading. The system comprises hubs controlled by competing energy companies, incorporating both external energy trading and peer-to-peer energy exchanges. It involves multiple stakeholders whose decisions are interdependent, creating challenges in decision-making. To tackle these challenges, we propose a networked Stackelberg game framework with two main objectives. First, from the energy companies' perspective, the companies make decisions by considering strategic interactions with other companies while accounting for the best responses of passive consumers within peer-to-peer constraints. Second, from the consumer side, consumers adjust their decisions based on their observations of the companies' strategies. The framework adopts a hierarchical decision-making structure in which energy companies act as leaders, formulating strategies that anticipate consumer demand responses, while competing within a Nash game. Meanwhile, consumer clusters, managed by demand management centers, modify their energy usage based on an incentive price mechanism. To search for the equilibrium, we develop an operator-theoretic approach that combines implicit gradient methods with proximal operator splitting techniques, and prove its convergence. Numerical studies and simulations on a combined IEEE 37-bus and gas source model with multiple energy hubs validate the model's effectiveness and the efficiency of the proposed algorithms. The results demonstrate the operational efficiency and strategic stability of the system, emphasizing the advantages of active market participation for both energy companies and consumers.

IEEE Transactions on Network Science and EngineeringVol. 12(4)
Tongji University (CN), North China Electric Power University (CN), China Electric Power Research Institute
Affordable and clean energy
Openalex Percentile: Top 10%
Smart Grid Energy Management
2.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.