Distributed cooperative control for global power sharing management of interconnected microgrids in flexible multi-terminal DC connection scheme

Meng, Xiaoxiao; Wang, Yuchen; Shao, Bingbing; Mao, Xun; Wang, Qianggang

doi:10.1016/j.epsr.2024.110969

Electric Power Systems Research

2024

DOI: 10.1016/j.epsr.2024.110969

|View full text |Cite

Distributed cooperative control for global power sharing management of interconnected microgrids in flexible multi-terminal DC connection scheme

Xiaoxiao Meng,

Yuchen Wang,

Bingbing Shao

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

The Study of Scheduling Optimization for Multi-Microgrid Systems Based on an Improved Differential Algorithm

Dong,

Lee

2024

Electronics

View full text Add to dashboard Cite

As traditional power grids are unable to meet growing demand, extensive research on multi-microgrid scheduling has begun to address the issues present in conventional power grids. However, existing studies on the scheduling of grid-connected multi-microgrids still lack sufficient focus on system demand-side and interaction-side aspects. At the same time, the uncertainties of renewable energy and demand-side responses further complicate this research. To address this, this paper proposes an operational scheduling strategy based on an improved differential evolution algorithm, aiming to incorporate power interactions between microgrids, demand-side responses, and the uncertainties of renewable energy, thus enhancing the operational reliability and economic efficiency of multi-microgrid systems. The research in this paper is divided into the following steps: (1) constructing a multi-microgrid model primarily based on renewable energy; (2) formulating an optimization model with the objective of minimizing economic costs while ensuring stable system operation and solving it; (3) proposing an improved differential evolution algorithm for optimizing system scheduling; (4) testing and validating the improved differential algorithm; and (5) designing an operational strategy that accounts for the uncertainties of renewable energy and load demand. Through the application of real-world cases, the feasibility and effectiveness of the operational scheduling strategy based on the improved differential evolution algorithm are verified.

show abstract

The Study of Scheduling Optimization for Multi-Microgrid Systems Based on an Improved Differential Algorithm

Dong,

Lee

2024

Electronics

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Distributed cooperative control for global power sharing management of interconnected microgrids in flexible multi-terminal DC connection scheme

Cited by 1 publication

References 26 publications

The Study of Scheduling Optimization for Multi-Microgrid Systems Based on an Improved Differential Algorithm

The Study of Scheduling Optimization for Multi-Microgrid Systems Based on an Improved Differential Algorithm

Contact Info

Product

Resources

About