254 research outputs found
Online decentralized tracking for nonlinear time-varying optimal power flow of coupled transmission-distribution grids
The coordinated alternating current optimal power flow (ACOPF) for coupled
transmission-distribution grids has become crucial to handle problems related
to high penetration of renewable energy sources (RESs). However, obtaining all
system details and solving ACOPF centrally is not feasible because of privacy
concerns. Intermittent RESs and uncontrollable loads can swiftly change the
operating condition of the power grid. Existing decentralized optimization
methods can seldom track the optimal solutions of time-varying ACOPFs. Here, we
propose an online decentralized optimization method to track the time-varying
ACOPF of coupled transmission-distribution grids. First, the time-varying ACOPF
problem is converted to a dynamic system based on Karush-Kuhn-Tucker conditions
from the control perspective. Second, a prediction term denoted by the partial
derivative with respect to time is developed to improve the tracking accuracy
of the dynamic system. Third, a decentralized implementation for solving the
dynamic system is designed based on only a few information exchanges with
respect to boundary variables. Moreover, the proposed algorithm can be used to
directly address nonlinear power flow equations without relying on convex
relaxations or linearization techniques. Numerical test results reveal the
effectiveness and fast-tracking performance of the proposed algorithm.Comment: 18 pages with 15 figure
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