期刊
IET GENERATION TRANSMISSION & DISTRIBUTION
卷 13, 期 13, 页码 2664-2672出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2018.5043
关键词
load flow; stochastic processes; optimisation; power transmission planning; power system security; power generation planning; wind power plants; polynomials; stochastic optimal transmission; correlated wind power; mitigating transmission congestion; reducing power losses; large-scale renewable energy integration; randomness characteristic; solar power; novel stochastic optimal power flow-based point estimation method; load; polynomial normal transformation; random variables; percentile matching method; integral operation; population sample mean; population sample standard deviation; OTS strategies; bus voltage; reactive power
资金
- National Key R&D Program of China [2016YFB0900100]
- National Science Foundation of China [51337005]
Optimal transmission switching (OTS) is widely used in mitigating transmission congestion and reducing power losses. However, with large-scale renewable energy integration to the grid, making a decision for the randomness characteristic of renewable energy (e.g. wind and solar power) is complicated in OTS. In this study, a novel stochastic optimal power flow-based point estimation method (PEM) is presented to model the uncertainties of wind power and load in OTS. Polynomial normal transformation is introduced to handle the correlations between random variables, and percentile matching method is employed to obtain the coefficients of polynomial normal transformation, which can avoid the integral operation. Moreover, the expected value of power flow obtained by the PEM is applied to the presented model to control the line overload risk. Two indexes, namely, population sample mean and mean of population sample standard deviation, are proposed to investigate the effect of correlations on OTS strategies. The proposed model is finally transformed into a mixed-integer second-order cone programming to consider bus voltage and reactive power, and the modified IEEE RTS 24-bus system and IEEE 118 system are presented to test the model.
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