Adaptive Intelligent Supplemental Light Optimization based on Fluctuating Electricity Prices

Jan Corfixen Sørensen*, Eva Reybroeck

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

Growers cannot compromise product quality by saving energy, but increasing electricity prices pose an economic challenge. Greenhouse climate control systems must support advanced strategies to optimize these dynamic conflicting goals, but they do not currently do so. The approach utilizes existing hardware and integrates with local climate data, electricity price forecasts, and outdoor weather forecasts, enables advanced multi-objective optimization of climate parameters without requiring new hardware investments. In December 2022, researchers conducted a greenhouse experiment to evaluate the proposed system. Using dynamic multi-objective optimization, they were able to produce a variety of cultivars and save energy without sacrificing quality
Original languageEnglish
Title of host publication2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)
Number of pages7
PublisherIEEE
Publication dateMay 2024
ISBN (Electronic)979-8-3503-6623-5
DOIs
Publication statusPublished - May 2024
Event2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) - Madrid, Spain
Duration: 23. May 202424. May 2024

Conference

Conference2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)
Country/TerritorySpain
CityMadrid
Period23/05/202424/05/2024
SeriesIEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)
ISSN2330-4863

Keywords

  • dynamic multi-objective optimization
  • genetic algorithm
  • greenhouse climate control
  • software engineering

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