Abstract
This manuscript proposes a novel distributed cooperative control to optimize generation costs in DC microgrids, with consideration of time delays. Artstein's reduction method is employed to transform the time-delay system into an equivalent delay-free model. Building on this, a finite-time distributed control algorithm is introduced to minimize generation cost by aligning the incremental costs of distributed generation units (DGUs) within an accelerated convergence timeframe, while respecting both the capacity limits of DGUs and the transmission line losses. Additionally, a distributed control approach is developed to ensure finite-time voltage stability, balancing generation and consumption across the microgrid. A key feature of the proposed control approach is incorporating a prescribed performance function, ensuring that the system's transient and steady-state responses consistently meet the required performance criteria. This ensures enhanced reliability and operational effectiveness of the system. The superiority and robustness of the proposed strategy are demonstrated through extensive simulation case studies.
| Original language | English |
|---|---|
| Title of host publication | 2024 Saudi Arabia Smart Grid, SASG 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331576301 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 Saudi Arabia Smart Grid, SASG 2024 - Riyadh, Saudi Arabia Duration: 16 Dec 2024 → 18 Dec 2024 |
Publication series
| Name | 2024 Saudi Arabia Smart Grid, SASG 2024 |
|---|
Conference
| Conference | 2024 Saudi Arabia Smart Grid, SASG 2024 |
|---|---|
| Country/Territory | Saudi Arabia |
| City | Riyadh |
| Period | 16/12/24 → 18/12/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Artstein reduction
- DC Microgrids
- Finite-time controller
- Optimal Operation
- prescribed performance
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Control and Optimization
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