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posted on 04.08.2020by Jian Zhang, Mingjian Cui, Yigang He, Fangxing (Fran) Li
Connecting a large number of
intermittent distributed generators (DGs) and electric vehicles (EVs) to a distribution
network increases uncertainty and seriously threatens the safety and economic
operation of that distribution network. Robust optimization is an important method
of hedging against the adverse effects of uncertainty. However, the existing
literature on robust optimization of distribution networks has not taken into
account constraints on the travel distances of regulating equipment. In
response to this deficiency, this paper considers constraints on the cycle period of energy
storage systems (ESSs), travel distances of switchable capacitors and reactors, and load tap changers (OLTCs)
and step voltage regulators (SVRs). A two-stage multi-period mixed-integer
second-order cone robust model for coordinated active and reactive power
optimization of a distribution network is formulated based on branch flow
equations. There are not any dummy variables in the second stage model. In
contrast to the deficiency of the low computational rate of the column-and-constraint
generation (CCG) method, an iterative solution to the first and second stage
models is proposed based on the cutting plane. Increases to the variables and
constraints are not needed to solve the first stage model. For the second stage
multi-period model, only the model of each single period needs to be solved first.
Then the results of the two models are accumulated. Overall, the computational
speed is significantly enhanced. The capabilities of the proposed method are
validated by three simulation cases.