Multi-objective energy management of island microgrids with D-FACTS devices considering clean energy, storage systems and electric vehicles

被引:0
作者
Moradi, Mahyar [1 ]
Abardeh, Mohamad Hoseini [1 ]
Vahedi, Mojtaba [1 ]
Salehi, Nasrin [2 ]
Azarfar, Azita [1 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Shahrood Branch, Shahrood, Iran
[2] Islamic Azad Univ, Dept Basic Sci, Shahrood Branch, Shahrood, Iran
来源
CLEAN ENERGY | 2023年 / 7卷 / 05期
关键词
microgrid; D-FACTS; clean energy; battery; electric vehicles; evolutionary algorithm; OPTIMIZATION; ALGORITHM; DESIGN;
D O I
10.1093/ce/zkad045
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The development of microgrids is progressing due to intelligent load demands, clean energy, batteries and electric vehicles. The presence of such systems in microgrids causes power balance inconsistency, leading to increased power losses and deviation in voltage. In this paper, a mixed-integer non-linear programming model is proposed for modelling island microgrid energy management considering smart loads, clean energy resources, electric vehicles and batteries. Similarly, a flexible distributed AC transmission system device is proposed to prevent voltage deviation and reduce power losses. A scenario-based multi-objective function has been proposed to decrease energy losses and voltage deviations and energy outages of clean energy resources, reduce emissions from fossil-fired distributed generation and finally decrease load outages to reduce the vulnerability of the islanded microgrid. Regarding the proposed mixed-integer non-linear model and the high number of variables and constraints, a modified evolutionary algorithm based on particle swarm optimization has been proposed to solve the proposed model, which can be more efficient than other algorithms to achieve global optimal solutions. The model presented is implemented on a 33-node island microgrid and the results illustrate that the proposed algorithm and model are effective in reducing energy losses and voltage deviation, as well as reducing the vulnerability of the microgrid. The simulation results demonstrate that the proposed approach can lead to significant improvements in the performance of the microgrid. Specifically, the approach can result in a 27% reduction in losses, a 6% reduction in pollution and a 31% improvement in voltage. Additionally, the approach allows maximum utilization of renewable energy sources, making it a promising solution for sustainable energy management. Graphical Abstract A mixed-integer non-linear programming model is used to model an island microgrid. A flexible distributed AC transmission system device prevents voltage deviation and reduce power losses. A scenario-based multi-objective function decreases energy losses, voltage deviations and energy outages.
引用
收藏
页码:1046 / 1057
页数:12
相关论文
共 34 条
[1]   Adaptive LFC Incorporating Modified Virtual Rotor to Regulate Frequency and Tie-Line Power Flow in Multi-Area Microgrids [J].
Abubakr, Hussein ;
Guerrero, Josep M. ;
Vasquez, Juan C. ;
Mohamed, Tarek Hassan ;
Mahmoud, Karar ;
Darwish, Mohamed M. F. ;
Dahab, Yasser Ahmed .
IEEE ACCESS, 2022, 10 :33248-33268
[2]   Using genetic alghoritm for distributed generation allocation to reduce losses and improve voltage profile [J].
Alinejad-Beromi, Y. ;
Sedigliizadeh, M. ;
Bayat, M. R. ;
Khodayar, M. E. .
2007 42ND INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, VOLS 1-3, 2007, :954-959
[3]   Design Optimization of a Residential PV-Battery Microgrid With a Detailed Battery Lifetime Estimation Model [J].
Alramlawi, Mansour ;
Li, Pu .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2020, 56 (02) :2020-2030
[4]   Weibull distribution-based analysis for reliability assessment of an isolated power micro-grid system [J].
Amuta, E. O. ;
Wara, S. T. ;
Agbetuyi, A. F. ;
Sawyerr, B. A. .
MATERIALS TODAY-PROCEEDINGS, 2022, 65 :2215-2220
[5]   Hybrid Microgrid Many-Objective Sizing Optimization With Fuzzy Decision [J].
Cao, Bin ;
Dong, Weinan ;
Lv, Zhihan ;
Gu, Yu ;
Singh, Surjit ;
Kumar, Pawan .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 28 (11) :2702-2710
[6]   Uncertain Scenario Based MicroGrid Optimization via Hybrid Levy Particle Swarm Variable Neighborhood Search Optimization (HL_PS_VNSO) [J].
Dabhi, Dharmesh ;
Pandya, Kartik .
IEEE ACCESS, 2020, 8 :108782-108797
[7]   Energy Management Optimization of Microgrid Cluster Based on Multi-Agent-System and Hierarchical Stackelberg Game Theory [J].
Dong, Xin ;
Li, Xianshan ;
Cheng, Shan .
IEEE ACCESS, 2020, 8 :206183-206197
[8]   Real-Time Implementation of Self-Adaptive Salp Swarm Optimization-Based Microgrid Droop Control [J].
Ebrahim, M. A. ;
Fattah, Reham Mohamed Abdel ;
Saied, Ebtisam Mostafa Mohamed ;
Maksoud, Samir Mohamed Abdel ;
El Khashab, Hisham .
IEEE ACCESS, 2020, 8 :185738-185751
[9]   Operation Loss Minimization Targeted Distributed Optimal Control of DC Microgrids [J].
Fan, Zhen ;
Fan, Bo ;
Peng, Jiangkai ;
Liu, Wenxin .
IEEE SYSTEMS JOURNAL, 2021, 15 (04) :5186-5196
[10]   Intelligent voltage and frequency control of islanded micro-grids based on power fluctuations and communication system uncertainty [J].
Ghasemi, Arvin ;
Sedighizadeh, Mostafa ;
Fakharian, Ahmad ;
Nasiri, Mohammad Reza .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2022, 143