The Power Matchmaking Transaction Based on Generation Algorithm Optimization

2013 ◽  
Vol 848 ◽  
pp. 161-165
Author(s):  
Yin Fang ◽  
Chao Ma ◽  
Yong Dai ◽  
Ying Ying Zhai ◽  
Zhen Liao Lv
Keyword(s):  
Social Welfare ◽  
Electricity Market ◽  
Power Market ◽  
Transformation Model ◽  
Power Transformation ◽  
Algorithm Optimization ◽  
Generation Algorithm ◽  
Welfare Maximization ◽  
Social Welfare Maximization ◽  
The Social

In regional electricity market environment, power market matchmaking transaction mechanism is used widely. The power transformation model of competitive integration market is built to meet the various needs, maintain the existing price system and make the social welfare maximization. The power matchmaking transaction based on generation algorithm is used in this paper to find a set of allocation, to maximize the search to the social welfare in numerous electrical distributions. For the purpose of minimizing the transaction risk, definitions of trust, an optimized matchmaking transaction based on generation algorithm are given in this paper.

Power-Transformation Model to Additivity in Regression

2005 ◽  
Vol 32 (2) ◽  
pp. 111-125 ◽  
Author(s):  
Toshimitsu Hamasaki ◽  
Masashi Goto
Keyword(s):  
Transformation Model ◽  
Power Transformation

Monte Carlo Algorithms for Moments of Transition Arrays

1988 ◽  
Vol 102 ◽  
pp. 79-81
Author(s):  
A. Goldberg ◽  
S.D. Bloom
Keyword(s):  
Monte Carlo ◽  
State Vector ◽  
Basis Vector ◽  
Collective State ◽  
Dispersion Characteristics ◽  
Dipole Strength ◽  
The Third ◽  
Monte Carlo Algorithms ◽  
Third Moment ◽  
Very High

AbstractClosed expressions for the first, second, and (in some cases) the third moment of atomic transition arrays now exist. Recently a method has been developed for getting to very high moments (up to the 12th and beyond) in cases where a “collective” state-vector (i.e. a state-vector containing the entire electric dipole strength) can be created from each eigenstate in the parent configuration. Both of these approaches give exact results. Herein we describe astatistical(or Monte Carlo) approach which requires onlyonerepresentative state-vector |RV> for the entire parent manifold to get estimates of transition moments of high order. The representation is achieved through the random amplitudes associated with each basis vector making up |RV>. This also gives rise to the dispersion characterizing the method, which has been applied to a system (in the M shell) with≈250,000 lines where we have calculated up to the 5th moment. It turns out that the dispersion in the moments decreases with the size of the manifold, making its application to very big systems statistically advantageous. A discussion of the method and these dispersion characteristics will be presented.

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