A novel scheme of control commands for smoothing PV power by using ANN

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper proposes a novel scheme of control commands for smoothing photovoltaic generation (PV) power by using ANN. The proposed method decides the power command as follows. The moving average is performed to smooth the selected one-day PV data. The smoothed PV data is shifted by a half period of moving average to compensate for time delay. The smoothed-and-shifted PV data are used as the target outputs for artificial neural networks (ANN). The structure of ANN is decided by the optimization method. The power command for smoothing PV power is decided by using ANN whose structure is led by learning and optimization. The proposed method has improved the time delay compared to the conventional method. The proposed method has reduced the energy storage capacity by 254 MJ compared to the conventional method, although it has increased the power in LFC band by 39.2 kW compared to the conventional method. Energy control has performed to reduce the energy storage capacity while maintaining the power smoothing effect. As a result, the proposed method with energy control has implied a possibility that it can reduce the energy storage capacity by 5.3% compared to the conventional method with energy control.

Original languageEnglish
Pages (from-to)698-704
Number of pages7
JournalIEEJ Transactions on Power and Energy
Volume136
Issue number8
DOIs
Publication statusPublished - 2016

Fingerprint

Power generation
Power control
Energy storage
Neural networks
Time delay

Keywords

  • Artificial neural network
  • Moving average
  • Photovoltaic generation
  • Power smoothing control
  • Time delay

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cite this

A novel scheme of control commands for smoothing PV power by using ANN. / Takahashi, Akiko; Aoki, Kosuke; Funabiki, Shigeyuki.

In: IEEJ Transactions on Power and Energy, Vol. 136, No. 8, 2016, p. 698-704.

Research output: Contribution to journalArticle

@article{834a3e621bcc4c56890e44ec5161b8c6,
title = "A novel scheme of control commands for smoothing PV power by using ANN",
abstract = "This paper proposes a novel scheme of control commands for smoothing photovoltaic generation (PV) power by using ANN. The proposed method decides the power command as follows. The moving average is performed to smooth the selected one-day PV data. The smoothed PV data is shifted by a half period of moving average to compensate for time delay. The smoothed-and-shifted PV data are used as the target outputs for artificial neural networks (ANN). The structure of ANN is decided by the optimization method. The power command for smoothing PV power is decided by using ANN whose structure is led by learning and optimization. The proposed method has improved the time delay compared to the conventional method. The proposed method has reduced the energy storage capacity by 254 MJ compared to the conventional method, although it has increased the power in LFC band by 39.2 kW compared to the conventional method. Energy control has performed to reduce the energy storage capacity while maintaining the power smoothing effect. As a result, the proposed method with energy control has implied a possibility that it can reduce the energy storage capacity by 5.3{\%} compared to the conventional method with energy control.",
keywords = "Artificial neural network, Moving average, Photovoltaic generation, Power smoothing control, Time delay",
author = "Akiko Takahashi and Kosuke Aoki and Shigeyuki Funabiki",
year = "2016",
doi = "10.1541/ieejpes.136.698",
language = "English",
volume = "136",
pages = "698--704",
journal = "IEEJ Transactions on Power and Energy",
issn = "0385-4213",
publisher = "The Institute of Electrical Engineers of Japan",
number = "8",

}

TY - JOUR

T1 - A novel scheme of control commands for smoothing PV power by using ANN

AU - Takahashi, Akiko

AU - Aoki, Kosuke

AU - Funabiki, Shigeyuki

PY - 2016

Y1 - 2016

N2 - This paper proposes a novel scheme of control commands for smoothing photovoltaic generation (PV) power by using ANN. The proposed method decides the power command as follows. The moving average is performed to smooth the selected one-day PV data. The smoothed PV data is shifted by a half period of moving average to compensate for time delay. The smoothed-and-shifted PV data are used as the target outputs for artificial neural networks (ANN). The structure of ANN is decided by the optimization method. The power command for smoothing PV power is decided by using ANN whose structure is led by learning and optimization. The proposed method has improved the time delay compared to the conventional method. The proposed method has reduced the energy storage capacity by 254 MJ compared to the conventional method, although it has increased the power in LFC band by 39.2 kW compared to the conventional method. Energy control has performed to reduce the energy storage capacity while maintaining the power smoothing effect. As a result, the proposed method with energy control has implied a possibility that it can reduce the energy storage capacity by 5.3% compared to the conventional method with energy control.

AB - This paper proposes a novel scheme of control commands for smoothing photovoltaic generation (PV) power by using ANN. The proposed method decides the power command as follows. The moving average is performed to smooth the selected one-day PV data. The smoothed PV data is shifted by a half period of moving average to compensate for time delay. The smoothed-and-shifted PV data are used as the target outputs for artificial neural networks (ANN). The structure of ANN is decided by the optimization method. The power command for smoothing PV power is decided by using ANN whose structure is led by learning and optimization. The proposed method has improved the time delay compared to the conventional method. The proposed method has reduced the energy storage capacity by 254 MJ compared to the conventional method, although it has increased the power in LFC band by 39.2 kW compared to the conventional method. Energy control has performed to reduce the energy storage capacity while maintaining the power smoothing effect. As a result, the proposed method with energy control has implied a possibility that it can reduce the energy storage capacity by 5.3% compared to the conventional method with energy control.

KW - Artificial neural network

KW - Moving average

KW - Photovoltaic generation

KW - Power smoothing control

KW - Time delay

UR - http://www.scopus.com/inward/record.url?scp=84982860449&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84982860449&partnerID=8YFLogxK

U2 - 10.1541/ieejpes.136.698

DO - 10.1541/ieejpes.136.698

M3 - Article

VL - 136

SP - 698

EP - 704

JO - IEEJ Transactions on Power and Energy

JF - IEEJ Transactions on Power and Energy

SN - 0385-4213

IS - 8

ER -