A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices

Hui Xiang, Xiao Liao, Yanjie Wang, Hui Cao, Xianjing Zhong (), Qingshu Guan and Weiyun Ru
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Hui Xiang: State Grid Information & Telecommunication Group Co., Ltd., Beijing 610041, China
Xiao Liao: State Grid Information & Telecommunication Group Co., Ltd., Beijing 610041, China
Yanjie Wang: State Grid Information & Telecommunication Group Co., Ltd., Beijing 610041, China
Hui Cao: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Xianjing Zhong: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Qingshu Guan: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Weiyun Ru: School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Energies, 2024, vol. 17, issue 21, 1-20

Abstract: The advancement of hydrogen technology and rising environmental concerns have shifted research toward renewable energy for green hydrogen production. This study introduces a novel tri-level transaction methodology for microgrid clusters, addressing uncertainties and price fluctuations in hydrogen. We establish a comprehensive microgrid topology with distributed power generation and hydrogen production facilities. A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. Additionally, we propose a tri-level game-theoretic framework for analyzing stakeholder interactions in microgrid clusters, incorporating supply–demand dynamics and a master–slave structure for microgrids and users. A distributed algorithm, “KKT & supply-demand ratio”, solves large-scale optimization problems by integrating Karush–Kuhn–Tucker conditions with a heuristic approach. Our simulations validate the methodology, demonstrating that accounting for uncertainties and dynamic hydrogen prices enhances renewable energy use and economic efficiency, optimizing social welfare for operators and economic benefits for microgrids and users.

Keywords: microgrid cluster; game theory; uncertainty optimization; dynamic hydrogen price; demand response (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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