The increasing penetration of the power grid with renewable distributed generation causes significant voltage fluctuations. Providing reactive helps balancing in grid. This paper proposes a novel adaptive volt-var control algorithm on basis deep reinforcement learning. learning agent is an online-learning deterministic policy gradient that applicable under real-time conditions smart inverters f...

Volt-VAR control (VVC) is a critical application in active distribution network management system to reduce losses and improve voltage profile. To remove dependency on inaccurate incomplete models enhance resiliency against communication or controller failure, we propose consensus multi-agent deep reinforcement learning algorithm solve the VVC problem, which determines operation schedules for r...

Volt-var control (VVC) is the problem of operating power distribution systems within healthy regimes by controlling actuators in systems. Existing works have mostly adopted conventional routine representing (a graph with tree topology) as vectors to train deep reinforcement learning (RL) policies. We propose a framework that combines RL neural networks and study benefits limitations graph-based...

Electric distribution grids are seeing an increased penetration of photovoltaic (PV) generation. High PV generation exceeding the grid load demand results in a reverse active power flow grid, which raises voltage level. This paper presents reactive controller to overcome overvoltage problem system. A sequentially coordinated and cooperative volt/var control technique is presented. The proposed ...

The high penetration and uncertainty of distributed energies force the upgrade volt-var control (VVC) to smooth voltage var fluctuations faster. Traditional mathematical or heuristic algorithms are increasingly incompetent for this task because slow online calculation speed. Deep reinforcement learning (DRL) has recently been recognized as an effective alternative it transfers computational pre...

The widespread integration of photovoltaic (PV) units may result in a number of operational issues for the utility distribution system. The advances in smart-grid technologies with better communication and control capabilities may help to mitigate these challenges. The objective of this paper is to evaluate multiple voltage control methods and compare their effectiveness in mitigating the impac...

This paper presents a novel distributed optimal power flow (DOPF) method for fair energy resource (DER) coordination in the context of mandated rooftop PV inverter control modes. In practice, reactive is increasingly required by grid connection codes, which often unfairly curtail generation prosumers towards end low-voltage feeders. Similarly, optimization-based DER methods that aim solely tech...