A distributed control strategy for reactive power compensation in smart microgrids

TL;DR

This paper introduces a distributed, gossip-like optimization algorithm for reactive power compensation in smart microgrids, enabling microgenerators to locally coordinate and minimize power losses efficiently.

Contribution

It presents a novel convex quadratic approximation model and a distributed algorithm for reactive power control that requires only local information and measurements.

Findings

Algorithm converges under specified conditions

Performance improves with neighbor cooperation in radial networks

Numerical simulations validate the model and convergence analysis

Abstract

We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to the microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance can be achieved when we command cooperation among units that are neighbors in the electric topology. Numerical simulations are included to validate the proposed model and to confirm the analytic results about the performance of the proposed algorithm.