Photovoltaic's Hotspot and Partial Shading Detection Algorithm Using Characteristic Curve's Analysis

Jirada Gosumbonggot, Goro Fujita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Photovoltaic (PV) technology achieves great interests from its non-polluted operation and flexible installation. The obstacle is the hotspot on the PV panel's surface which is the consequence of shading, occurs as the heat and cause the damage to the PV's system. The conventional method for detecting the hotspot is the usage of the infrared camera; however, trades of cost and manpower are the main disadvantages. Moreover, the hotspot and partial shading have similar effects to the PV's system which is the reduction of the output current and generated power. It is essential not only to detect but also differentiate the hotspot from partial shading. This paper proposes the algorithm for detecting the hotspot and partial shading on the PV array by analyzing the PV's characteristic curves. Proposed algorithm's efficiency is confirmed by the system implementation and shows success detection in different levels of hotspot defections.

Original languageEnglish
Title of host publication2019 9th International Conference on Power and Energy Systems, ICPES 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728126586
DOIs
Publication statusPublished - 2019 Dec
Event9th International Conference on Power and Energy Systems, ICPES 2019 - Perth, Australia
Duration: 2019 Dec 102019 Dec 12

Publication series

Name2019 9th International Conference on Power and Energy Systems, ICPES 2019

Conference

Conference9th International Conference on Power and Energy Systems, ICPES 2019
Country/TerritoryAustralia
CityPerth
Period19/12/1019/12/12

Keywords

  • hotspot
  • irradiation
  • maximum power point tracking (MPPT)
  • photovoltaic
  • renewable energy
  • shading

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Fuel Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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