Embedded Intelligent Reactive Power Control for Distributed Controllable Loads to Support Grid Voltage Considering Islanding Conditions

Abstract

The increasing integration of distributed energy resources (DERs) along with distributed controllable loads (DCLs), presents significant challenges for maintaining grid stability and effectively incorporating these resources. Traditionally, DERs have supported microgrid (MG) stability primarily through active power control loops, which has limited their ability to manage power output effectively. This paper introduces a novel embedded intelligent reactive power control framework for DCLs, designed to bolster grid voltage stability during islanding conditions. This framework seamlessly integrates reactive power control loops as ancillary services within DCLs, which can also support other grid-forming (GFM) resources. The DCL is modeled with grid-following (GFL) control loops, which incorporate an embedded intelligent reactive power control loop into the voltage control system. The proposed intelligent framework applies a modified long-short term memory neural network to imitate reactive power behavior. The network is trained with the special loss function to minimize voltage variation. This enables the intelligent GFL control to accurately follow voltage and frequency references from the GFM resources and adapt to unexpected islanding scenarios. Simulation results in a low-inertia MG with DERs confirm the superiority of the proposed framework. It outperforms conventional methods, including mixed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{2}/H_{\infty }$ </tex-math></inline-formula> strategy, model predictive control, and convolutional neural network. Through a comprehensive evaluation, the proposed strategy shows superior performance in transient response, voltage stability, power dynamics, statistical analysis, and damping performance.