An Uncertainty-Based Voltage Control Model of a Smart Active Network in
the Presence of Electric Vehicles: A Distributed Optimization Approach
Abstract
Nowadays, Distributed Energy Resources (DERs) and Electric Vehicles
(EVs) are being increasingly used in smart distribution networks. There
are concerns regarding the use of DERs and EVs which are twofold: (i)
they may lead to grid voltage variation and (ii) they have uncertainty
in power production. In this paper, a distributed voltage control method
is proposed in the simultaneous presence of DERs and EVs preserving the
independence and reducing the communications between them while
considering probabilistic behaviors. The proposed objective function
improves the system voltage profile with the lowest rate of change in
the active and reactive power of DERs and EVs. For this purpose, a
method is developed for converting the centralized optimization problem
to the distributed optimization problem using Dual-Decomposition (DD)
and Alternating Direction Method of Multipliers (ADMM) algorithms based
on Peer-to-Peer (P2P) communication capabilities of DERs and EVs. The
uncertainty of DERs and EVs are modelled by utilizing a scenario-based
approach and a Two-Point Estimation Method (2PEM), respectively. The
results on the modified IEEE 69-bus test system show that the proposed
method can improve the voltage deviation of the worst bus by about 7%,
and also reduce grid losses by about 48%.