Compared with other natural or man-made networks, electric power grid assumes distinct "electric" topology with special small-world properties and electrical parameter settings. In this paper we study the scaling property of power grid in terms of both topology measures and electric parameters, with a number of realistic power grid test cases of different size. The examined measures and parameters include average node degree, average path length, algebraic connectivity, the bus type entropy that characterize relative locations of generation and load buses, generation capacity, total demand, and transmission capacity. Interpreting and testing the scaling property of power grid will help us better understand the intrinsic characteristics of electric energy delivery network of this critical infrastructure; and enable the development of an appropriate synthetic modeling that could be utilized to generate power grid test cases with accurate grid topology and electric parameters.

1 aWang, Zhifang1 aElyas, Seyyed, Hamid uhttp://aisel.aisnet.org/hicss-50/es/monitoring/4/01963nas a2200157 4500008003900000022001400039245008000053210006900133260001200202300001000214520145600224653001301680100002501693700001801718856006901736 2016 d a0885-895000aImproved Synthetic Power Grid Modeling with Correlated Bus Type Assignments0 aImproved Synthetic Power Grid Modeling with Correlated Bus Type c12/2016 a1 - 13 aThis paper presents our study results on the correlated assignment of generation, load, or connection buses in a given grid topology and the development of an optimized search algorithm to improve the proposed synthetic grid model, called RT-nestedSmallWorld. A numerical measure, called "Bus Type Entropy", was proposed in an initial study on this subject to characterize the correlation of bus type assignments in realistic grids. In this paper its definition has been redefined and improved with the help of some newly obtained data of realistic grids so that the scaling property of a real-world grid's entropy value versus the network size can be effectively captured with a curve-fitting approach. With the help of the derived scaling function, we will be able to determine an appropriate target entropy value that a correlated bus type assignment should assume in a specific Nbus grid network. Therefore our previously proposed synthetic power grid modeling has been enhanced with a direct search procedure for the best bus type assignments in a specific Nbus grid topology, saving the mandatory, but most the time unattainable, requirement of a set of realistic grid data with a comparable network size for identifying the search target. Finally the performance of the proposed approach is examined based on some available grid data including the IEEE test cases, the NYISO-2935, the ERCOT-5633 and the WECC-16994 systems.

10aRM14-0031 aElyas, Seyyed, Hamid1 aWang, Zhifang uhttps://certs.lbl.gov/publications/improved-synthetic-power-grid02172nas a2200145 4500008003900000245010600039210006900145260003400214300001600248520163800264653001301902100002501915700001801940856006801958 2016 d00aA Multi-objective Optimization Algorithm for Bus Type Assignments in Random Topology Power Grid Model0 aMultiobjective Optimization Algorithm for Bus Type Assignments i aKoloa, HI, USAbIEEEc01/2016 a2446 - 24553 aOur previous work proposed a random topology power grid model, called RT-nested-smallworld, formulated based on a comprehensive study of the real-world grid topologies and electrical properties. The model can be used to produce a sufficiently large number of power grid test cases with scalable network size and featuring the same kind of small-world topology and electrical characteristics found in realistic grids. However, the proposed RT-power grid model has a shortcoming that is its random assignment of bus types (i.e. Generation, Load, or Connection), which is inconsistent with that of a realistic grid. Because our recent study found that the bus type assignment in a realistic power grid is not random but a correlated one. With the help of Bus Type Entropy, a novel measure which provides a quantitative means to better represent the correlation of bus type assignments in a grid topology, we propose a multi-objective optimization algorithm for the bus type assignments in the random topology power grid modeling. The proposed search algorithm is able to locate the best set of bus type assignments for a given random "electrical" topology generated by RT-nested-smallworld, so that each bus type assignment in the target set will have a Bus Type Entropy value close to that of a realistic grid with comparable network size. In order to demonstrate the performance of the proposed multi-objective algorithm, we experiment our algorithm on three sets of realistic power systems, namely, the IEEE-300 bus system, the NYISO system and the MPC system. The obtained results confirm the validity of our proposed method.

10aRM14-0031 aElyas, Seyyed, Hamid1 aWang, Zhifang uhttps://certs.lbl.gov/publications/multi-objective-optimization01471nas a2200145 4500008003900000245008100039210006900120260004000189300001000229520095700239653001301196100002501209700001801234856007301252 2016 d00aStatistical analysis of transmission line capacities in electric power grids0 aStatistical analysis of transmission line capacities in electric aMinneapolis, MN, USAbIEEEc09/2016 a1 - 53 aThis paper mainly focuses on statistical analysis of transmission line capacities in terms of both topology and electrical parameters. We expand our earlier work on random-topology power grid modeling as a way to generate synthetic grid data to test new concepts and designs. We examine transmission line capacities based on both network topology metrics and a newly proposed electrical index called “neighboring capacity ratio”. The obtained results show that the issue of transfer capacity assignment not only emerges as an electrical optimization concern, but some topological metrics must be considered to find the best line capacity assignment that is consistent with what is manifested in real-world grid. Statistical experiments conducted on the ERCOT and WECC system data help appropriately characterize the transmission line capacity. And the results can be utilized to improve our synthetic power grid models in the future.

10aRM14-0031 aElyas, Seyyed, Hamid1 aWang, Zhifang uhttps://certs.lbl.gov/publications/statistical-analysis-transmission02664nas a2200157 4500008003900000245008200039210006900121260004200190300001000232520211000242653001302352100001802365700002502383700002302408856007502431 2015 d00aA novel measure to characterize bus type assignments of realistic power grids0 anovel measure to characterize bus type assignments of realistic aEindhoven, NetherlandsbIEEEc06/2015 a1 - 63 aElectric power engineers and researchers need appropriate randomly generated grid network topologies for Monte Carlo experiments to test and demonstrate new concepts and methods. Our previous work proposed a random topology power grid model, called RT-nested-small-world, based on a comprehensive study of the real-world grid topologies and electrical properties. The proposed model can be used to produce a sufficiently large number of power grid test cases with scalable network size featuring the same kind of small-world topology and electrical characteristics found in realistic grids. However, the proposed RT-power grid model has a shortcoming that is its random assignment of bus types. And our recent study has shown that the bus type assignment of a realistic power grid is not random but a correlated one. Generally speaking,the buses in a power grid can be grouped into three categories: generation buses (G), load buses (L), and connection buses (C). When studying the dynamics of a grid we need to take into account not only its "electrical" topology but also the generation and load settings including their locations, which are equivalent to the bus type assignments in our model. In this paper we define a novel measure to characterize typical bus type assignments of realistic power grids. The proposed measure will enable the recognition of the specific set of bus type assignments, consistent with that of a realistic grid, from those generated from random permutation. This will prove useful for designing an optimal algorithm to improve our random topology power grid modeling. The proposed measure, called the Bus Type Entropy, incorporates both bus type ratios and the link type ratios. Therefore it provides a quantitative means to identify the presence of correlation among the bus type assignments of a realistic grid. We then experiment with this entropy measure on a NYISO system and the IEEE 300-bus system. The numerical results from both test cases verify the effecti- eness of the proposed measure to characterize the bus type assignment of a real-world power grid.

10aRM14-0031 aWang, Zhifang1 aElyas, Seyyed, Hamid1 aThomas, Robert, J. uhttps://certs.lbl.gov/publications/novel-measure-characterize-bus-type