DOI:10.1007/s40565-018-0384-6 |
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Maximum entropy based probabilistic load flow calculation for power system integrated with wind power generation |
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Net amount: 1172 |
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Author:
Bingyan SUI1,2, Kai HOU2, Hongjie JIA2, Yunfei MU2, Xiaodan YU2
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Author Affiliation:
1.Shanghai Electric Power Design Institute Co. Ltd., Shanghai 200025, China;
2.School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
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Foundation: |
This work was supported by National Natural
Science Foundation of China (No. 51625702, No. 51377117, No.
51677124) and National High-tech R&D Program of China (863
Program) (No. 2015AA050403). |
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Abstract: |
Distributed generation including wind turbine
(WT) and photovoltaic panel increased very fast in recent
years around the world, challenging the conventional way
of probabilistic load flow (PLF) calculation. Reliable and
efficient PLF method is required to take into account such
changing. This paper studies the maximum entropy probabilistic
density function reconstruction method based on
cumulant arithmetic of linearized load flow formulation,
and then develops a maximum entropy based PLF (MEPLF)
calculation algorithm for power system integrated
with wind power generation (WPG). Comparing to traditional
Gram–Charlier expansion based PLF (GC-PLF)
calculation method, the proposed ME-PLF calculation
algorithm can obtain more reliable and accurate probabilistic
density functions (PDFs) of bus voltages and branch
flows in various WT parameter scenarios. It can solve the
limitation of GC-PLF calculation method that mistakenly
gaining negative values in tail regions of PDFs. Linear
dependence between active and reactive power injections
of WPG can also be effectively considered by the modified
cumulant calculation framework. Accuracy and efficiency
of the proposed approach are validated with some test
systems. Uncertainties yielded by the wind speed variations,
WT locations, power factor fluctuations are
considered. |
Keywords: |
Maximum entropy, Probabilistic load flow,
Probability density function, Wind power generation,
Monte Carlo simulation |
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Online Time:2018/09/22 |
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