A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster
A novel, fully distributed controller with a rapid convergence rate is developed to ensure the optimal loading dispatch for interconnected DC MGs. It comprises local and global-control levels, handling the economic load allocations in a finite-time manner, for distinct MGs and cluster of MGs, respec...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/15/11/3994 |
| _version_ | 1797493600220610560 |
|---|---|
| author | Mohamed Zaery Panbao Wang Wei Wang Dianguo Xu |
| author_facet | Mohamed Zaery Panbao Wang Wei Wang Dianguo Xu |
| author_sort | Mohamed Zaery |
| collection | DOAJ |
| description | A novel, fully distributed controller with a rapid convergence rate is developed to ensure the optimal loading dispatch for interconnected DC MGs. It comprises local and global-control levels, handling the economic load allocations in a finite-time manner, for distinct MGs and cluster of MGs, respectively. The local-control layer guarantees MG’s economic operation by matching the incremental costs (ICs) of all DGs, respecting the power equilibrium among generations and demands, DGs’ generation limits, as well as the transmission line losses. Furthermore, the economic operation of battery energy sources is considered, in the optimization problem, to strengthen the overall reliability and maximize energy arbitrage. The global controller adjusts MGs’ voltage references to determine the optimal exchanged power, between MGs, for reducing the global total generation cost (TGC). A rigorous analysis is developed to confirm the stable convergence of the developed controller. Extensive simulation case studies demonstrate the superiority of the proposed control system. |
| first_indexed | 2024-03-10T01:22:21Z |
| format | Article |
| id | doaj.art-cfe6eed229c74099af739561130c6a85 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T01:22:21Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-cfe6eed229c74099af739561130c6a852023-11-23T13:58:34ZengMDPI AGEnergies1996-10732022-05-011511399410.3390/en15113994A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids ClusterMohamed Zaery0Panbao Wang1Wei Wang2Dianguo Xu3Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, EgyptDepartment of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaDepartment of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaDepartment of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaA novel, fully distributed controller with a rapid convergence rate is developed to ensure the optimal loading dispatch for interconnected DC MGs. It comprises local and global-control levels, handling the economic load allocations in a finite-time manner, for distinct MGs and cluster of MGs, respectively. The local-control layer guarantees MG’s economic operation by matching the incremental costs (ICs) of all DGs, respecting the power equilibrium among generations and demands, DGs’ generation limits, as well as the transmission line losses. Furthermore, the economic operation of battery energy sources is considered, in the optimization problem, to strengthen the overall reliability and maximize energy arbitrage. The global controller adjusts MGs’ voltage references to determine the optimal exchanged power, between MGs, for reducing the global total generation cost (TGC). A rigorous analysis is developed to confirm the stable convergence of the developed controller. Extensive simulation case studies demonstrate the superiority of the proposed control system.https://www.mdpi.com/1996-1073/15/11/3994DC microgrids clustereconomic dispatchdistributed controlfinite-time consensus protocolbattery energy sources |
| spellingShingle | Mohamed Zaery Panbao Wang Wei Wang Dianguo Xu A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster Energies DC microgrids cluster economic dispatch distributed control finite-time consensus protocol battery energy sources |
| title | A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster |
| title_full | A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster |
| title_fullStr | A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster |
| title_full_unstemmed | A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster |
| title_short | A Novel Optimal Power Allocation Control System with High Convergence Rate for DC Microgrids Cluster |
| title_sort | novel optimal power allocation control system with high convergence rate for dc microgrids cluster |
| topic | DC microgrids cluster economic dispatch distributed control finite-time consensus protocol battery energy sources |
| url | https://www.mdpi.com/1996-1073/15/11/3994 |
| work_keys_str_mv | AT mohamedzaery anoveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT panbaowang anoveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT weiwang anoveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT dianguoxu anoveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT mohamedzaery noveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT panbaowang noveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT weiwang noveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster AT dianguoxu noveloptimalpowerallocationcontrolsystemwithhighconvergenceratefordcmicrogridscluster |