Title:
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Voltage performance in residential distribution networks with small wind turbines and battery electric vehicles, through probabilistic power flow analysis
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Future electrical low voltage (LV) distribution networks are expected to have higher
penetration of distributed generation (DG) systems, e.g. small wind turbines (SWTs), and
battery electric vehicles (BEVs). The intermittent and time-varying characteristics of
wind speed and BEV charging bring difficulties in evaluating the adverse performance,
e.g. voltage violation and unbalance, on the residential distribution networks (RDNs).
This thesis develops two probabilistic power flow methods, i.e. statistical time series
(STS) and point estimate method (PEM), for evaluating voltage violation and voltage
unbalance in RDNs caused by integration of SWTs and BEVs.
The STS method combines statistical distribution analysis (SDA) and time series
analysis (TSA). PEM is an approximation method using deterministic routines for
solving probabilistic problems. The STS supports the Distribution Network Operators
(DNOs) to obtain daily probability of voltage violations in RDNs, considering the time
varying characteristics of network load, wind speed and BEV charging in a statistical
manner. In PEM, evaluating the voltage unbalance takes into account the disparity of the
loads at the three phases and also the unbalanced distribution of SWT outputs. The PEM
calculation can also obtain daily probability of voltage unbalance factor in RDNs.
The results presented prove that STS and PEM can provide faster evaluation of the
probability of voltage violation and unbalance of a RDN than TSA. Based on the
statistics of one year's seasonal load, wind data, at the same level of time granularity, the
STS method can reduce computational power by over 98%. The assessment difference is
approximately 6%. PEM evaluation, using one year's load and wind speed data, without
distinguishing these data into seasonal categories or weekdays and weekends, reduces
the computational power required by over 97.8%. The evaluation estimate is within 16%.
The proposed methods can provide DNOs with a global picture of the voltage violation
and unbalance profiles of RDNs under various SWT and BEV penetrations. For the
distribution network planning, the quick evaluation of voltage violation and unbalance
can help DNOs determine the maximum capacity of SWTs and BEVs a network can
accommodate without voltage violation or unbalance.
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