Optimization of microgrid operation based on two-level probabilistic scheduling with benders decomposition

被引:7
作者
Dashtdar, Masoud [1 ]
Flah, Aymen [2 ]
Hosseinimoghadam, Seyed Mohammad Sadegh [1 ]
Zangoui Fard, Mohammad [1 ]
Dashtdar, Majid [1 ]
机构
[1] Islamic Azad Univ, Bushehr Branch, Dept Elect Engn, Bushehr, Iran
[2] Univ Gabes, Natl Sch Engn Gabes, Gabes 6072, Tunisia
关键词
Optimal microgrid scheduling; Renewable energy sources; Island operation; Main grid connection operation; Bander's decomposition; Adjustable loads; ENERGY-STORAGE; LOAD;
D O I
10.1007/s00202-022-01540-5
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, a two-level model for probabilistic microgrid scheduling, considering the uncertainties of electricity price and predicted load, is present for microgrid performance in both island mode and connection to the main grid. The two-level model of ideal microgrid scheduling using the Banders decomposition method is decomposing into the main problem for operation in the main grid connection mode and subproblems for performance in island mode. The primary problem's objective function is to reduce the cost of microgrid performance, while the subproblem's objective function looks at the adequacy of microgrid production and the microgrid's ability to serve loads without interruption in the case of islands. In this method, if there is not enough power to supply loads in the mode of existing islands, a cut is added to the main issue to revise the microgrid performance program. Finally, the simulation results for both the microgrid connection mode to the main grid and the islands mode are present. In both modes, the modeling results demonstrate excellent microgrid performance.
引用
收藏
页码:3225 / 3239
页数:15
相关论文
共 22 条
[1]   Multi-Objective Energy Management of a Micro-Grid Considering Stochastic Nature of Load and Renewable Energy Resources [J].
Ahmed, Deyaa ;
Ebeed, Mohamed ;
Ali, Abdelfatah ;
Alghamdi, Ali S. ;
Kamel, Salah .
ELECTRONICS, 2021, 10 (04) :1-22
[2]   Modeling and Simulation of Microgrid [J].
Alzahrani, Ahmad ;
Ferdowsi, Mehdi ;
Shamsi, Pourya ;
Dagli, Cihan H. .
COMPLEX ADAPTIVE SYSTEMS CONFERENCE WITH THEME: ENGINEERING CYBER PHYSICAL SYSTEMS, CAS, 2017, 114 :392-400
[3]  
Azim R, 2016, ASIA-PAC POWER ENERG, P2620, DOI 10.1109/APPEEC.2016.7779964
[4]   Probabilistic Microgrid Energy Management with Interval Predictions [J].
Cheng, Jiayu ;
Duan, Dongliang ;
Cheng, Xiang ;
Yang, Liuqing ;
Cui, Shuguang .
ENERGIES, 2020, 13 (12)
[5]   Probabilistic multi-objective microgrid planning methodology for optimizing the ancillary services provision [J].
Contreras, Sergio F. ;
Cortes, Camilo A. ;
Myrzik, Johanna M. A. .
ELECTRIC POWER SYSTEMS RESEARCH, 2020, 189
[6]   Probabilistic planning for participation of virtual power plants in the presence of the thermal power plants in energy and reserve markets [J].
Dashtdar, Masoud ;
Najafi, Mojtaba ;
Esmaeilbeig, Mostafa .
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2020, 45 (01)
[7]   Calculating the locational marginal price and solving optimal power flow problem based on congestion management using GA-GSF algorithm [J].
Dashtdar, Masoud ;
Najafi, Mojtaba ;
Esmaeilbeig, Mostafa .
ELECTRICAL ENGINEERING, 2020, 102 (03) :1549-1566
[8]   Optimal scheduling of a microgrid with a fuzzy logic controlled storage system [J].
Fossati, Juan P. ;
Galarza, Ainhoa ;
Martin-Villate, Ander ;
Echeverria, Jose M. ;
Fontan, Luis .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2015, 68 :61-70
[9]   A Review of Optimization of Microgrid Operation [J].
Gao, Kaiye ;
Wang, Tianshi ;
Han, Chenjing ;
Xie, Jinhao ;
Ma, Ye ;
Peng, Rui .
ENERGIES, 2021, 14 (10)
[10]  
Hosseinimoghadam SMS, 2020, 8TH INTERNATIONAL CONFERENCE ON SMART GRID (ICSMARTGRID2020), P67, DOI [10.1109/icSmartGrid49881.2020.9144968, 10.1109/icsmartgrid49881.2020.9144968]