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Communication Dans Un Congrès Année : 2020

Agent-based Modeling for Optimizing CO2 Reduction in Commercial Greenhouse Production with the Implicit Demand Response

Résumé

Industries are identified as major potentials to reduce the CO2 emission due to their large energy consumption and the possibility of providing energy flexibility with optimization and smart control. Commercial greenhouses are considered as one of the industries that have large energy flexibility potentials with the heavily used artificial lighting (around 75% of the electricity consumption coming from artificial lighting). This paper investigates the CO2 reduction potential in the commercial greenhouses with a case study of the Danish commercial greenhouses via participation in the implicit Demand Response. Agent-Based modeling is used to simulate the greenhouse production and the response to the electricity spot price signals. The result shows that the potential of CO2 reduction in 2018 was 0.33% (equals to 170 thousand tonnes) of the total Danish emission when 50% (equals to 181 growers) of the Danish commercial greenhouses participate in the implicit Demand Response. The last 50% of the commercial greenhouses have a relatively slow adoption rate and account for only a small amount of CO2 reductions. Meanwhile, the largest reduction of the CO2 emission is not in chronological order as commercial greenhouses' financial saving because the electricity spot price and solar irradiation do not follow each other.
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Dates et versions

hal-03051658 , version 1 (17-12-2020)

Identifiants

  • HAL Id : hal-03051658 , version 1

Citer

Kristoffer Christensen, Zheng Ma, Yves Demazeau, Bo Nørregaard Jørgensen. Agent-based Modeling for Optimizing CO2 Reduction in Commercial Greenhouse Production with the Implicit Demand Response. 6th IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization, SAMCON 2020, Mar 2020, Tokyo, Japan. ⟨hal-03051658⟩
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