Publication result detail

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

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

Original Title

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

English Title

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

Type

WoS Article

Original Abstract

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.

English abstract

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.

Keywords

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

Key words in English

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

Authors

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

RIV year

2023

Released

06.04.2022

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Location

PISCATAWAY

ISBN

2168-6777

Periodical

IEEE Journal of Emerging and Selected Topics in Power Electronics

Volume

10

Number

5

State

United States of America

Pages from

5762

Pages to

5772

Pages count

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"
}