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Considering forecasting errors in flexibility-oriented distribution network expansion planning using the spherical simplex unscented transformation
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DOI：10.1049/iet-gtd.2020.0702.png)
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摘要
En 中文
The rapid rise in the grid integration of low-carbon technologies, e.g. renewable energy sources (RESs) and plug-in electric vehicles (PEVs), has led to several challenges in distribution networks (DNs). This is due to the intermittent generation of RESs and uncertain loads of PEVs, both of which necessitate enhancing the flexibility requirements at the distribution level so as to accommodate the high penetration of these clean technologies in the future. To address such issues, this study proposes a mixed-integer linear programming-based expansion planning model for DNs considering the impact of high RES and PEV penetration, the associated uncertainties, and providing flexibility requirements at the distribution level. In this respect, the spherical simplex unscented transformation, an analytical uncertainty modelling method, is implemented in the planning model to take into account the forecasting errors of the uncertain green technologies. Also, in order to estimate the electric vehicle parking lot demand at each load node of the network, a new approach for PEV-charging model is suggested. To investigate the effectiveness and efficiency of the proposed probabilistic planning model, it is implemented on two test DNs, and the obtained results are thoroughly discussed.
Keyword:
linear programming
Kalman filters
renewable energy sources
battery powered vehicles
power distribution planning
load forecasting
integer programming
electric vehicle charging
high RES
PEV penetration
associated uncertainties
flexibility requirements
distribution level
spherical simplex unscented transformation
analytical uncertainty modelling method
forecasting errors
uncertain green technologies
electric vehicle
PEV-charging model
probabilistic planning model
test DNs
flexibility-oriented distribution network expansion planning
grid integration
renewable energy sources
RESs
distribution networks
intermittent generation
uncertain loads
clean technologies
mixed-integer linear programming expansion planning model
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IF:
2.6
论文数:
271
被引数:
1.0W
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