Journal
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 8, Issue 3, Pages 1000-1009Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2016.2640340
Keywords
Copula; probabilistic load flow; active distribution system; uncertainty; correlation; discrete convolution; dependent; sequence operation theory
Categories
Funding
- National Key Research and Development Program of China [2016YFB0900105]
- National Science Foundation of China [51307092, 51325702]
- Science-Technology Project of State Grid Corporation of China [GHJS1500009]
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Active distribution system (ADS) plays a significant role in enabling the integration of distributed generation. The stochastic nature of renewable energy resources injects the complex uncertainties of power flow into ADS. This paper proposes a discrete convolution methodology for probabilistic load flow (PLF) of ADS considering correlated uncertainties. First, the uncertainties of load and renewable energy are modeled using the distribution of the corresponding forecasting error, and the correlation is formulated using a Copula function. A novel reactive power-embedded DC power flow model with high accuracy in both branch flow and node voltage is introduced into ADS. Finally, the distribution of power flow is calculated using dependent discrete convolution, which is capable of handling nonanalytical probability distribution functions. In addition, a reduced dimension approximation method is proposed to further reduce the computational burden. The proposed PLF algorithm is tested on the IEEE 33-nodes system and 123-nodes system, and the results show that the proposed methodology requires less computation and produces higher accuracy compared with current methods.
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