Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

Journal Article · Fri Jul 17 04:00:00 EDT 2020 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/TSG.2020.3010130· OSTI ID:1762475

Zhang, Ying; Wang, Xinan; Wang, Jianhui; Zhang, Yingchen

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1762475
• Report Number(s): NREL/JA-5D00-78897; MainId:32814; UUID:ba58bcd2-684a-4c9c-bf19-062af1c806db; MainAdminID:19199
• Journal Information: IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 1 Vol. 12
• Country of Publication: United States
• Language: English

Related Subjects

41 EE - Solar Energy Technologies Office (EE-4S)
artificial intelligence
deep reinforcement learning
smart inverter
unbalanced distribution systems
volt-VAR optimization
voltage regulation