Electric Service Restoration using Microgrids

被引:0
作者
Ansari, Bananeh [1 ]
Mohagheghi, Salman [1 ]
机构
[1] Colorado Sch Mines, Dept Elect Engn & Comp Sci, Golden, CO 80401 USA
来源
2014 IEEE PES GENERAL MEETING - CONFERENCE & EXPOSITION | 2014年
关键词
Distribution network; electric service restoration; demand response; distributed energy resources; Microgrid; mixed-integer nonlinear programming; DISTRIBUTION-SYSTEM; EXPERT-SYSTEM;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A Microgrid-assisted methodology is proposed in this paper for electric service restoration in distribution networks. Success of restoration algorithms is closely tied with the availability of sufficient capacity on the restoration path(s). When the restoration path is at or near full capacity, some capacity relief may be achieved through the usage of Microgrids. By increasing the generation level of its micro-generators, reducing the demand of its demand responsive loads, or, as the last resort, by islanding from the grid, a Microgrid can help alleviate the congestion on the restoration path, and therefore assist the service restoration algorithm. The methodology put forth in this paper considers a potential restoration circuit equipped with Microgrids, and provides the most cost-effective operational solution while achieving the targeted restoration capacity. Network operational constraints, demand variations, and fluctuations in energy pricing are all taken into account. The problem is formulated as a mixed-integer nonlinear programming problem, and is implemented on a modified version of the IEEE 123-node test distribution system.
引用
收藏
页数:5
相关论文
共 27 条
[1]  
Borges T., 2011, P IEEE PES
[2]   A rule-based expert system with colored Petri net models for distribution system service restoration [J].
Chen, CS ;
Lin, CH ;
Tsai, HY .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (04) :1073-1080
[3]   Enhancement of restoration service in distribution systems using a combination fuzzy-GA method [J].
Hsiao, YT ;
Chien, CY .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2000, 15 (04) :1394-1400
[4]   DISTRIBUTION-SYSTEM SERVICE RESTORATION USING THE ARTIFICIAL NEURAL-NETWORK APPROACH AND PATTERN-RECOGNITION METHOD [J].
HSU, YY ;
HUANG, HM .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1995, 142 (03) :251-256
[5]   Evolution of radial basic function neural network for fast restoration of distribution systems with load variations [J].
Huang, Chao-Ming ;
Hsieh, Cheng-Tao ;
Wang, Yung-Shan .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2011, 33 (04) :961-968
[6]   Optimized restoration of unbalanced distribution systems [J].
Khushalani, Sarika ;
Solanki, Jignesh M. ;
Schulz, Noel N. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (02) :624-630
[7]   Improving Service Restoration of Power Distribution Systems Through Load Curtailment of In-Service Customers [J].
Kleinberg, Michael R. ;
Miu, Karen ;
Chiang, Hsiao-Dong .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (03) :1110-1117
[8]  
Kovac M., P 2012 ELEKTRO, P212
[9]   DG Integrated Approach for Service Restoration Under Cold Load Pickup [J].
Kumar, Vishal ;
Kumar, Rohith H. C. ;
Gupta, Indra ;
Gupta, Hari Om .
IEEE TRANSACTIONS ON POWER DELIVERY, 2010, 25 (01) :398-406
[10]   Service restoration in distribution system using non-dominated sorting genetic algorithm [J].
Kumar, Y ;
Das, B ;
Sharma, J .
ELECTRIC POWER SYSTEMS RESEARCH, 2006, 76 (9-10) :768-777