A Stackelberg Game-Based Optimal Scheduling Model for Multi-Microgrid Systems Considering Photovoltaic Consumption and Integrated Demand Response

To enhance the interests of all stakeholders in the multi-microgrid integrated energy system and to promote photovoltaic consumption, this paper proposes a master–slave game operation optimization strategy for a multi-microgrid system considering photovoltaic consumption and integrated demand response. Initially, an energy interaction model was established to delineate the relationships between each microgrid and the distribution network, as well as the interactions among the microgrids. Additionally, an integrated demand response model for end-users was developed. This framework leads to the formulation of a one-leader multi-follower interaction equilibrium model, wherein the multi-microgrid system acts as the leader and the users of the multi-microgrid serve as followers. It is proven that a unique equilibrium solution for the Stackelberg game exists. The upper level iteratively optimizes variables such as energy-selling prices, equipment output, and energy interactions among microgrids, subsequently announcing the energy-selling prices to the lower level. The lower level is responsible for optimizing energy load and returning the actual load demand to the upper level. Finally, the rationality and effectiveness of the proposed strategy are demonstrated through the case analysis. Thus, the profitability of the multi-microgrid system is enhanced, along with the overall benefits for each microgrid user, and the amount of photovoltaic curtailment is significantly reduced.

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Publication Details

Journal
Energies
Published
2024-11-28
DOI
https://doi.org/10.3390/en17236002
Citations
7
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
1.46

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article

A Stackelberg Game-Based Optimal Scheduling Model for Multi-Microgrid Systems Considering Photovoltaic Consumption and Integrated Demand Response

Yafei Li, Yunpeng Xiao, Shengyue Ji, Jie Li et al.
7 citations
Energies
Smart Grid Energy Management
1.46
article

A Stackelberg Game-Based Optimal Scheduling Model for Multi-Microgrid Systems Considering Photovoltaic Consumption and Integrated Demand Response

Yafei Li, Yunpeng Xiao, Shengyue Ji, Jie Li, Hengyuan Zhang, Xiuli Wang, Xiaojie Qian
article en
7 citations

Abstract

To enhance the interests of all stakeholders in the multi-microgrid integrated energy system and to promote photovoltaic consumption, this paper proposes a master–slave game operation optimization strategy for a multi-microgrid system considering photovoltaic consumption and integrated demand response. Initially, an energy interaction model was established to delineate the relationships between each microgrid and the distribution network, as well as the interactions among the microgrids. Additionally, an integrated demand response model for end-users was developed. This framework leads to the formulation of a one-leader multi-follower interaction equilibrium model, wherein the multi-microgrid system acts as the leader and the users of the multi-microgrid serve as followers. It is proven that a unique equilibrium solution for the Stackelberg game exists. The upper level iteratively optimizes variables such as energy-selling prices, equipment output, and energy interactions among microgrids, subsequently announcing the energy-selling prices to the lower level. The lower level is responsible for optimizing energy load and returning the actual load demand to the upper level. Finally, the rationality and effectiveness of the proposed strategy are demonstrated through the case analysis. Thus, the profitability of the multi-microgrid system is enhanced, along with the overall benefits for each microgrid user, and the amount of photovoltaic curtailment is significantly reduced.

EnergiesVol. 17(23)
Xi'an Jiaotong University (CN)
Science and Technology Project of State Grid, State Grid Jiangsu Electric Power
Affordable and clean energy
Openalex Percentile: Top 17%
Smart Grid Energy Management
1.46
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