Research on size and location of distributed generation with vulnerable node identification in the active distribution network

被引:46
作者
Zhao, Yuanyuan [1 ]
An, Yiran [1 ]
Ai, Qian [1 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China
关键词
ALLOCATION; PLACEMENT;
D O I
10.1049/iet-gtd.2013.0887
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
This study aims to solve for the optimal location and capacity of distributed generation (DG), taking vulnerable node identification into consideration, in active distribution networks (ADN). Vulnerable nodes exist in the distribution network. Considering that the power fluctuations of those vulnerable nodes will have a significant impact on other nodes, the allocations of the DGs should avoid such nodes. Therefore vulnerable node identification and removal from the network can greatly limit the siting range of DGs. In this study, the vulnerable nodes are identified based on the small-world network theory, which is used as the preliminary location of the DG. Then, a genetic algorithm (GA) is proposed to finally address the optimal location and capacity for grid-connected DG. A GA with voltage boundary constraints is utilised to effectively prevent the bus voltage from reaching its boundary. This method improves the calculation efficiency greatly and is therefore suitable for flexible distribution network topology in ADN. According to the change of the distribution network topology, the corresponding optimal location and capacity limit for the DG can be quickly calculated. Some examples validate the algorithm and prove that it has fast convergence.
引用
收藏
页码:1801 / 1809
页数:9
相关论文
共 22 条
[1]   Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm [J].
Abu-Mouti, Fahad S. ;
El-Hawary, M. E. .
IEEE TRANSACTIONS ON POWER DELIVERY, 2011, 26 (04) :2090-2101
[2]   An analytical approach for DG allocation in primary distribution network [J].
Acharya, Naresh ;
Mahat, Pukar ;
Mithulananthan, N. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2006, 28 (10) :669-678
[3]  
Ahmadigorji M., 2009, WORLD ACAD SCI ENG T, V49, P746
[4]  
An Yi-ran, 2013, East China Electric Power, V41, P537
[5]   Optimal distributed generation allocation in MV distribution networks [J].
Celli, G ;
Pilo, F .
PICA 2001: 22ND IEEE POWER ENGINEERING SOCIETY INTERNATIONAL CONFERENCE ON POWER INDUSTRY COMPUTER APPLICATIONS, 2001, :81-86
[6]   Fuzzy Decision-Making Based on Likelihood-Based Comparison Relations [J].
Chen, Shyi-Ming ;
Lee, Li-Wei .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2010, 18 (03) :613-628
[7]  
Deb K., 2000, Parallel Problem Solving from Nature PPSN VI. 6th International Conference. Proceedings (Lecture Notes in Computer Science Vol.1917), P849
[8]  
Dingwei W., 2007, INTELLIGENT OPTIMIZA
[9]   Optimal placement of multi-distributed generation units including different load models using particle swarm optimization [J].
El-Zonkoly, A. M. .
SWARM AND EVOLUTIONARY COMPUTATION, 2011, 1 (01) :50-59
[10]   Optimal DG placement in deregulated electricity market [J].
Gautam, Durga ;
Mithulananthan, Nadarajah .
ELECTRIC POWER SYSTEMS RESEARCH, 2007, 77 (12) :1627-1636