Adaptive Volt–Var Control in Smart PV Inverter for Mitigating Voltage Unbalance at PCC Using Multiagent Deep Reinforcement Learning

Abstract

Modern distribution networks face an increasing number of challenges in maintaining balanced grid voltages because of the rapid increase in single-phase distributed generators. Because of the proliferation of inverter-based resources, such as photovoltaic (PV) resources, in distribution networks, a novel method is proposed for mitigating voltage unbalance at the point of common coupling by tuning the volt–var curve of each PV inverter through a day-ahead deep reinforcement learning training platform with forecast data in a digital twin grid. The proposed strategy uses proximal policy optimization, which can effectively search for a global optimal solution. Deep reinforcement learning has a major advantage in that the calculation time required to derive an optimal action in the smart inverter can be significantly reduced. In the proposed framework, multiple agents with multiple inverters require information on the load consumption and active power output of each PV inverter. The results demonstrate the effectiveness of the proposed control strategy on the modified IEEE 13 standard bus systems with time-varying load and PV profiles. A comparison of the effect on voltage unbalance mitigation shows that the proposed inverter can address voltage unbalance issues more efficiently than a fixed droop inverter.

Comprehensive review and a novel technique on voltage unbalance compensation

“…The optimal Volt‐VAr droop control of each PV inverter to mitigate the voltage unbalance at the PCC is proposed in ref. [108] through day‐ahead deep reinforcement learning. The developed platform procedure mainly includes two stages: the training stage and the implementation stage.…”

“…The power charging on a single-phase connected EV [27] as a function voltage, that is, P(V) droop control, has been applied to reduce the impact of a single-phase on-board charger causing the voltage deviation among the three phases. The Volt-VAr curve [108] has also been utilised and optimised through day-ahead deep reinforcement learning. In ref.…”

Voltage Optimization in PV-Rich Distribution Networks—A Review

“…However, some researchers [30,31] suggest that the aforementioned strategies may not be effective for prosumer-based DNs due to their slow response. The application of PV inverters represents a promising solution and in combination with already present control mechanisms can give results, so several studies have proposed their use for voltage optimization [32][33][34][35][36]. Different modes of operation are possible for PV inverters and the authors of [30] distinguish the following:…”

“…Objectives Variables [65] single-objective min VD PV inverter reactive power, OLTC [38] multi-objective min losses, min VD, min VUF, min PV generation cost, min PV APC cost PV inverter reactive power [66] multi-objective min losses, min VD, improvement VSI PV inverter reactive power and static compensator [53,54,[67][68][69] multi-objective min losses, min VD PV inverter reactive power [70] multi-objective min VD, min losses PV inverter reactive power, CBs, and OLTC [71] single-objective min VUF PV inverter active and reactive power, power injected by TS [72] single-objective min VD PV inverter reactive power [73] multi-objective min losses, min cost of APC and generated/consumed reactive power, min VD PV inverter reactive power [74] multi-objective min VD, min voltage unbalance PV inverter reactive power, OLTC, VR, and CB [75] multi-objective min losses, min VD, min VUF PV inverter reactive power [32] single-objective min VUF PV inverter reactive power [76] single-objective min VD PV inverter reactive power, OLTC [77] multi-objective min losses, min VD, min control action of OLTC and SC PV inverter reactive power, OLTC, SC [78] single-objective min VD PV inverter reactive power, OLTC [79] multi-objective min VD, min losses PV inverter reactive power, OLTC, and SC [57] multi-objective min VD, min losses, min reactive power injection, and absorption PV inverter reactive power [80] multi-objective min VD, min losses PV inverter reactive power, OLTC [81] single-objective min VD PV inverter reactive power, OLTC, and VR [58] multi-objective min VD, min losses, min APC PV inverter reactive power, OLTC and CB [55] multi-objective min VD, min losses PV and EV inverter reactive power, the compensation device [56] multi-objective min VD, min OLTC tap operation PV inverter reactive power, OLTC [82] single-objective min VD PV inverter reactive power, charge/discharge rate of ESS [83] multi-objective min losses, min VUF PV inverter reactive power [34] multi-objective min cost, min losses, min cost associated with active power s...…”