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Volt-VAR Optimization in Distribution Networks Using Twin Delayed Deep Reinforcement Learning

Conference · · 2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
 [1];  [2];  [2];  [2];  [2]
  1. University of Nevada,Department of Electrical & Biomedical Engineering,Reno; NV Energy
  2. University of Nevada,Department of Electrical & Biomedical Engineering,Reno
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Modern distribution grids are undergoing new challenges due to the stochastic nature of distributed energy resources (DERs). High penetration of DERs has a significant impact on Volt-VAR profile and system power losses. This work proposes a deep reinforcement learning (DRL)-based Volt-VAR optimization approach for improving voltage profile and reducing system power loss under high penetration of distributed energy resources, such as battery energy storage and solar photovoltaic units in distribution grids. The twin delayed deep deterministic policy gradient (TD3) method-based DRL agent is proposed to configure optimal set-points of reactive power outputs of fast responding smart inverters. The agent schedules the reactive power of inverters according to their physical capabilities, such as minimum allowed power factor, e.g., 0.9 leading/lagging. The reward function of the proposed DRL scheme is designed carefully to ensure a proper voltage profile of the grids with effective scheduling of reactive power outputs from inverters. The performance of the proposed model is verified on modified IEEE 34- and 123-bus systems and compared with base case with no reactive supply by inverters, and local droop Volt-VAR control approach. The results show that the proposed method performs better than the local droop control and deep deterministic policy gradient (DDPG)-based DRL method for reducing voltage fluctuation and minimizing power loss.

Research Organization:
NV Energy
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
EE0009022
OSTI ID:
1894929
Journal Information:
2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Journal Name: 2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Country of Publication:
United States
Language:
English

References (7)

Volt/var control algorithm for modern distribution management system journal January 1995
DeepGrid: Robust Deep Reinforcement Learning-based Contingency Management conference February 2020
Distributed Volt/VAr Control by PV Inverters journal August 2013
Robust Volt/VAr Control With Photovoltaics journal May 2019
Three-Stage Robust Inverter-Based Voltage/Var Control for Distribution Networks With High-Level PV journal January 2019
Hierarchically-Coordinated Voltage/VAR Control of Distribution Networks Using PV Inverters journal July 2020
Two-Stage Volt/Var Control in Active Distribution Networks With Multi-Agent Deep Reinforcement Learning Method journal July 2021

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