A real–time distributed optimization control for power sharing and voltage restoration in inverter–based microgrids

Abstract

This paper presents a distributed control framework for grid–forming (GFM) distributed generations (DGs), considering the objectives of active/reactive power sharing and load feeder voltage regulation in inverter–based microgrids (MGs). Battery energy storage systems (BESSs) are controlled GFM sources while solar–powered DGs are working in grid–following (GFL) mode to provide active power support. The proposed method simplifies the global optimization problem into multiple sub–optimal problems by virtually segregating each GFM source into two decoupled sources. Each sub–problem, containing at most two GFM sources and multiple GFL sources with a single distributed agent, is solvable independently using local and neighboring node information. This feature substantially minimizes computational and communication resources, allowing for solutions using low–cost digital signal processors (DSPs). Moreover, the highly distributed nature of the proposed search algorithm ensures fast solution convergence and real–time implementation in multi–agent systems (MAS). Compared to existing segregation methods like Alternating Direction Method of Multipliers (ADMM) and Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) schemes, which segregate the network into complex sub–networks involving several GFM sources, the proposed approach is more suitable for small–scale inverter–based MGs. The framework’s effectiveness is validated through analytical formulation, MATLAB simulations, and realistic experimental results within a multi–feeder test MG system, which includes numerous load feeders and sparsely available GFM DGs, a scenario that has received limited attention in existing literature.

Keywords

• Multi–feeder microgrids
• Distributed optimization
• Decoupled spherical search method
• battery–powered grid–forming DGs
• solar–powered grid–following DGs
• Power sharing