DocumentCode :
1754888
Title :
Multi-Attribute Partitioning of Power Networks Based on Electrical Distance
Author :
Cotilla-Sanchez, Eduardo ; Hines, Paul D. H. ; Barrows, Clayton ; Blumsack, Seth ; Patel, Mitesh
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Oregon State Univ., Corvallis, OR, USA
Volume :
28
Issue :
4
fYear :
2013
fDate :
Nov. 2013
Firstpage :
4979
Lastpage :
4987
Abstract :
Identifying coherent sub-graphs in networks is important in many applications. In power systems, large systems are divided into areas and zones to aid in planning and control applications. But not every partitioning is equally good for all applications; different applications have different goals, or attributes, against which solutions should be evaluated. This paper presents a hybrid method that combines a conventional graph partitioning algorithm with an evolutionary algorithm to partition a power network to optimize a multi-attribute objective function based on electrical distances, cluster sizes, the number of clusters, and cluster connectedness. Results for the IEEE RTS-96 show that clusters produced by this method can be used to identify buses with dynamically coherent voltage angles, without the need for dynamic simulation. Application of the method to the IEEE 118-bus and a 2383-bus case indicates that when a network is well partitioned into zones, intra-zone transactions have less impact on power flows outside of the zone; i.e., good partitioning reduces loop flows. This property is particularly useful for power system applications where ensuring deliverability is important, such as transmission planning or determination of synchronous reserve zones.
Keywords :
IEEE standards; evolutionary computation; graph theory; load flow; power transmission planning; 118-bus case; 2383-bus case; IEEE RTS-96; cluster connectedness; coherent subgraphs; control applications; deliverability; dynamically coherent voltage angles; electrical distance; evolutionary algorithm; graph partitioning algorithm; hybrid method; intrazone transactions; multiattribute objective function; multiattribute partitioning; power flows; power networks; power systems; synchronous reserve zones; transmission planning; Electrical distance; evolutionary algorithms; network clustering; power network partitioning;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2013.2263886
Filename :
6523971
Link To Document :
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