Detail publikačního výsledku

Power Flow Management With Q-Learning for a Grid Integrated Photovoltaic and Energy Storage System

KHAN, M.; HAQUE, A.; KURUKURU, V.

Originální název

Power Flow Management With Q-Learning for a Grid Integrated Photovoltaic and Energy Storage System

Anglický název

Power Flow Management With Q-Learning for a Grid Integrated Photovoltaic and Energy Storage System

Druh

Článek WoS

Originální abstrakt

This article develops a fuzzy Q-learning (FQL) approach-based power flow management algorithm for a single-phase grid-connected (GC) photovoltaic (PV) system with an energy storage unit (ESU). The FQL coordinates the PV power generation, which is based on the mission profile, the state of charge (SOC) of ESU, and the load profile such that a power balance is achieved in the network. Furthermore, the transition between standalone (SA) and GC modes during the power flow management is achieved using a proportional capacitor current feedback. While operating in the SA mode, the control action for the load voltage is achieved by an outer current loop. This combination of coordinated and transition control achieves power balance and smooth transition between the SA and GC modes. To verify the effectiveness of the proposed control strategy, a 4 - kWp PV system is operated along with an ESU in both SA and GC modes for a varying mission and load profile. The simulation and experimental results validated the multifunctional features of the proposed method.

Anglický abstrakt

This article develops a fuzzy Q-learning (FQL) approach-based power flow management algorithm for a single-phase grid-connected (GC) photovoltaic (PV) system with an energy storage unit (ESU). The FQL coordinates the PV power generation, which is based on the mission profile, the state of charge (SOC) of ESU, and the load profile such that a power balance is achieved in the network. Furthermore, the transition between standalone (SA) and GC modes during the power flow management is achieved using a proportional capacitor current feedback. While operating in the SA mode, the control action for the load voltage is achieved by an outer current loop. This combination of coordinated and transition control achieves power balance and smooth transition between the SA and GC modes. To verify the effectiveness of the proposed control strategy, a 4 - kWp PV system is operated along with an ESU in both SA and GC modes for a varying mission and load profile. The simulation and experimental results validated the multifunctional features of the proposed method.

Klíčová slova

Load flow; Batteries; Voltage control; State of charge; Inverters; Microgrids; Energy management; Energy management system; grid-connected (GC); photovoltaic (PV) systems; standalone (SA); transition control

Klíčová slova v angličtině

Load flow; Batteries; Voltage control; State of charge; Inverters; Microgrids; Energy management; Energy management system; grid-connected (GC); photovoltaic (PV) systems; standalone (SA); transition control

Autoři

KHAN, M.; HAQUE, A.; KURUKURU, V.

Rok RIV

2023

Vydáno

06.04.2022

Nakladatel

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Místo

PISCATAWAY

ISSN

2168-6777

Periodikum

IEEE Journal of Emerging and Selected Topics in Power Electronics

Svazek

10

Číslo

5

Stát

Spojené státy americké

Strany od

5762

Strany do

5772

Strany počet

11

URL

https://ieeexplore.ieee.org/abstract/document/9750098

BibTex

@article{BUT178394,
  author="Mohammed Ali {Khan} and Ahteshamul {Haque} and V S Bharath {Kurukuru}",
  title="Power Flow Management With Q-Learning for a Grid Integrated Photovoltaic and Energy Storage System",
  journal="IEEE Journal of Emerging and Selected Topics in Power Electronics",
  year="2022",
  volume="10",
  number="5",
  pages="5762--5772",
  doi="10.1109/JESTPE.2022.3165173",
  issn="2168-6777",
  url="https://ieeexplore.ieee.org/abstract/document/9750098"
}