Management of Voltage Flexibility from Inverter-Based Distributed Generation Using Multi-Agent Reinforcement Learning

Nikita Tomin,Nikolai Voropai,Christian Rehtanz,Victor Kurbatsky

doi:10.3390/en14248270

Nikita Tomin, Nikolai Voropai + Show 2 more

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https://doi.org/10.3390/en14248270

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Abstract

The increase in the use of converter-interfaced generators (CIGs) in today’s electrical grids will require these generators both to supply power and participate in voltage control and provision of grid stability. At the same time, new possibilities of secondary QU droop control in power grids with a large proportion of CIGs (PV panels, wind generators, micro-turbines, fuel cells, and others) open new ways for DSO to increase energy flexibility and maximize hosting capacity. This study extends the existing secondary QU droop control models to enhance the efficiency of CIG integration into electrical networks. The paper presents an approach to decentralized control of secondary voltage through converters based on a multi-agent reinforcement learning (MARL) algorithm. A procedure is also proposed for analyzing hosting capacity and voltage flexibility in a power grid in terms of secondary voltage control. The effectiveness of the proposed static MARL control is demonstrated by the example of a modified IEEE 34-bus test feeder containing CIGs. Experiments have shown that the decentralized approach at issue is effective in stabilizing nodal voltage and preventing overcurrent in lines under various heavy load conditions often caused by active power injections from CIGs themselves and power exchange processes within the TSO/DSO market interaction.

Highlights

The aim of this paper is to extend the existing multi-agent systems (MAS) models of decentralized inverter-based secondary voltage control to improve converter-interfaced generators (CIGs)-associated integration problems in active distribution networks and microgrids
Based on the analysis of these works, in this paper, we have developed a multi-agent reinforcement learning (MARL)-based model-free approach for decentralized inverter-based secondary voltage control to manage flexibility services and increase hosting capacity
Hosting capacity generally refers to various types of CIGs, in this paper, we focus on the classical PV hosting capacity analysis to assess the performance of a decentralized MARL-based inverter control method

Summary

Introduction

Demand behavior and the presence of distributed energy resources (DERs) have a considerable impact on voltage. In this case, an increase in the number of DERs creates completely new power flows, alters the voltage profiles in the distribution system, and can diminish power quality. An increase in the number of DERs creates completely new power flows, alters the voltage profiles in the distribution system, and can diminish power quality In this context, there is an elevated need for flexible solutions to maintain the required voltage level at busbars. Ancillary services from distributed inverter-based generation and energy storage systems can be instrumental solutions for voltage stabilization in systems with DERs [1]

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