DynaGrow: Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses

Jan Corfixen Sørensen; Katrine Heinsvig Kjær; Carl-Otto Ottosen; Bo Nørregaard Jørgensen

doi:10.1007/978-3-319-99283-9_2

DynaGrow: Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses

Jan Corfixen Sørensen, Katrine Heinsvig Kjær, Carl-Otto Ottosen, Bo Nørregaard Jørgensen

Institut for Fødevarer - Planter, Fødevarer og Klima

Publikation: Bidrag til bog/antologi/rapport/proceeding › Bidrag til bog/antologi › Forskning

2 Citationer (Scopus)

Abstract

It is not possible for growers to compromise product quality by saving
energy but the increasing electricity prices challenge the growers economically.Optimization
of such multiple conflicting goals requires advanced strategies that are
currently not supported in existing greenhouse climate control systems. DynaGrow
is built on top of the existing climate control computers and utilizes the existing
hardware. By integrating with exiting hardware it is possibly to support advanced
multi-objective optimization of climate parameters without investing in new hardware.
Furthermore, DynaGrow integrates with local climate data, electricity price
forecasts and outdoor weather forecasts, in order to formulate advanced control
objectives. In September 2014 and February 2015 two greenhouse experiments were
run to evaluate the effects of DynaGrow. By applying multi-objective optimization,
it was possible to produce a number of different cultivars and save energy without
compromising quality. The best energy savings were achieved in the February 2015
experiment where the contribution from natural light was limited.

Originalsprog	Engelsk
Titel	Computational Intelligence : International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016. Revised Selected Papers
Redaktører	Juan Julian Merelo, Fernando Melício, José M. Cadenas, António Dourado, Kurosh Madani, António Ruano, Joaquim Filipe
Antal sider	20
Forlag	Springer
Publikationsdato	2019
Sider	25-44
ISBN (Trykt)	978-3-319-99282-2
ISBN (Elektronisk)	978-3-319-99283-9
DOI	https://doi.org/10.1007/978-3-319-99283-9_2
Status	Udgivet - 2019

Navn	Studies in Computational Intelligence
Vol/bind	792
ISSN	1860-949X

Adgang til dokumentet

10.1007/978-3-319-99283-9_2

Andre filer og links

http://www.scopus.com/inward/record.url?scp=85054367072&partnerID=8YFLogxK

Citationsformater

Sørensen, J. C., Kjær, K. H., Ottosen, C.-O., & Nørregaard Jørgensen, B. (2019). DynaGrow: Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses. I J. J. Merelo, F. Melício, J. M. Cadenas, A. Dourado, K. Madani, A. Ruano, & J. Filipe (red.), Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016. Revised Selected Papers (s. 25-44). Springer. https://doi.org/10.1007/978-3-319-99283-9_2

Sørensen, Jan Corfixen ; Kjær, Katrine Heinsvig ; Ottosen, Carl-Otto et al. / DynaGrow : Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses. Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016. Revised Selected Papers. red. / Juan Julian Merelo ; Fernando Melício ; José M. Cadenas ; António Dourado ; Kurosh Madani ; António Ruano ; Joaquim Filipe. Springer, 2019. s. 25-44 (Studies in Computational Intelligence, Bind 792).

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abstract = "It is not possible for growers to compromise product quality by savingenergy but the increasing electricity prices challenge the growers economically.Optimizationof such multiple conflicting goals requires advanced strategies that arecurrently not supported in existing greenhouse climate control systems. DynaGrowis built on top of the existing climate control computers and utilizes the existinghardware. By integrating with exiting hardware it is possibly to support advancedmulti-objective optimization of climate parameters without investing in new hardware.Furthermore, DynaGrow integrates with local climate data, electricity priceforecasts and outdoor weather forecasts, in order to formulate advanced controlobjectives. In September 2014 and February 2015 two greenhouse experiments wererun to evaluate the effects of DynaGrow. By applying multi-objective optimization,it was possible to produce a number of different cultivars and save energy withoutcompromising quality. The best energy savings were achieved in the February 2015experiment where the contribution from natural light was limited.",

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Sørensen, JC, Kjær, KH, Ottosen, C-O & Nørregaard Jørgensen, B 2019, DynaGrow: Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses. i JJ Merelo, F Melício, JM Cadenas, A Dourado, K Madani, A Ruano & J Filipe (red), Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016. Revised Selected Papers. Springer, Studies in Computational Intelligence, bind 792, s. 25-44. https://doi.org/10.1007/978-3-319-99283-9_2

DynaGrow: Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses. / Sørensen, Jan Corfixen; Kjær, Katrine Heinsvig; Ottosen, Carl-Otto et al.
Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016. Revised Selected Papers. red. / Juan Julian Merelo; Fernando Melício; José M. Cadenas; António Dourado; Kurosh Madani; António Ruano; Joaquim Filipe. Springer, 2019. s. 25-44 (Studies in Computational Intelligence, Bind 792).

Publikation: Bidrag til bog/antologi/rapport/proceeding › Bidrag til bog/antologi › Forskning

TY - CHAP

T1 - DynaGrow

T2 - Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses

AU - Sørensen, Jan Corfixen

AU - Kjær, Katrine Heinsvig

AU - Ottosen, Carl-Otto

AU - Nørregaard Jørgensen, Bo

PY - 2019

Y1 - 2019

N2 - It is not possible for growers to compromise product quality by savingenergy but the increasing electricity prices challenge the growers economically.Optimizationof such multiple conflicting goals requires advanced strategies that arecurrently not supported in existing greenhouse climate control systems. DynaGrowis built on top of the existing climate control computers and utilizes the existinghardware. By integrating with exiting hardware it is possibly to support advancedmulti-objective optimization of climate parameters without investing in new hardware.Furthermore, DynaGrow integrates with local climate data, electricity priceforecasts and outdoor weather forecasts, in order to formulate advanced controlobjectives. In September 2014 and February 2015 two greenhouse experiments wererun to evaluate the effects of DynaGrow. By applying multi-objective optimization,it was possible to produce a number of different cultivars and save energy withoutcompromising quality. The best energy savings were achieved in the February 2015experiment where the contribution from natural light was limited.

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Sørensen JC, Kjær KH, Ottosen CO, Nørregaard Jørgensen B. DynaGrow: Next Generation Software for Multi-Objective and Energy Cost-Efficient Control of Supplemental Light in Greenhouses. I Merelo JJ, Melício F, Cadenas JM, Dourado A, Madani K, Ruano A, Filipe J, red., Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016. Revised Selected Papers. Springer. 2019. s. 25-44. (Studies in Computational Intelligence, Bind 792). doi: 10.1007/978-3-319-99283-9_2