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Flexibility Aggregation and Optimal Trading Strategy for Distributed Energy Resources in Coupled Multi‐Electricity Markets

Xiaoyang HuangSchool of Electric Power South China University of Technology Guangzhou ChinaYing XueSchool of Electric Power South China University of Technology Guangzhou ChinaZexiang CaiSchool of Electric Power South China University of Technology Guangzhou ChinaXiaohua LiSchool of Electric Power South China University of Technology Guangzhou ChinaYun LiElectric Power Dispatching & Control Center Shenzhen Power Supply Co., Ltd. Shenzhen ChinaJunqiang GongElectric Power Dispatching & Control Center Shenzhen Power Supply Co., Ltd. Shenzhen ChinaAshurov AbdulahadFerghana State UniversityNIGMATOV ULUGBEKFerghana Polytechnical Institute
2026en
ABI

Аннотация

ABSTRACT With the increasing penetration of renewable energy, the demand for flexibility in power systems has grown significantly. However, existing studies typically model individual types of distributed energy resources (DERs) in isolation, lacking a unified representation of their heterogeneous power–energy characteristics and response mechanisms. This limitation hinders the effective aggregation of flexibility and restricts the full realisation of DERs’ value in electricity markets. To address this issue, this paper starts from the intrinsic formation mechanisms of flexibility and develops a unified aggregation modelling framework for distributed energy storage, flexible loads and quasi‐energy storage (e.g., a crusher with warehousing in ceramic production) resources. The flexibility of DERs is characterised along three key dimensions, namely maximum capacity, response speed and response duration. Based on this representation, an aggregation model is proposed to achieve a unified and tractable description of heterogeneous DERs’ flexibility. Furthermore, considering the coupling relationships among different electricity markets, an optimal scheduling model for DERs participation in multi‐market trading is established. Case studies demonstrate that the proposed approach achieves high utilisation levels for distributed energy storage (average 49.17%–56.80% SOC) and quasi energy storage (average 46.73%–60.79% warehousing state), while delivering annual total revenues of 71.90 million CNY across coupled multi‐electricity markets.

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