Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems

TL;DR

This paper introduces a decentralized optimization framework for controlling residential PV inverters, enabling improved voltage regulation and loss minimization while reducing computational load and communication requirements.

Contribution

It develops a novel decentralized algorithm based on ADMM for optimal inverter dispatch, scalable to large distribution networks with limited communication.

Findings

Effective decentralized control of PV inverters demonstrated

Reduced computational burden compared to centralized methods

Scalable approach suitable for large distribution systems

Abstract

Decentralized methods for computing optimal real and reactive power setpoints for residential photovoltaic (PV) inverters are developed in this paper. It is known that conventional PV inverter controllers, which are designed to extract maximum power at unity power factor, cannot address secondary performance objectives such as voltage regulation and network loss minimization. Optimal power flow techniques can be utilized to select which inverters will provide ancillary services, and to compute their optimal real and reactive power setpoints. Leveraging advances in semidefinite relaxation techniques and sparsity-promoting regularizations, such problems can be solved with reduced computational burden and with optimality guarantees. To enable large-scale implementation, a novel algorithmic framework is introduced - based on the so-called alternating direction method of multipliers - by which the optimal power flow problem in this setting can be systematically decomposed into sub-problems that can be solved in a decentralized fashion by the utility and customer-owned PV systems with limited exchanges of information. Since the computational burden is shared among multiple devices and the requirement of all-to-all communication can be circumvented, the proposed optimization approach scales to large distribution networks.