Exploiting flexibility in irrigation while maintaining optimal crop productivity

Diego Kiedanski, Daniel Kofman, Ariel Orda, Jose Horta, Alvaro Otero

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Irrigation in agriculture is a major source of electricity demand flexibility that goes largely unexploited. In this paper we provide a model and a solution to the problem of scheduling irrigation time to minimize electricity costs while satisfying crop water requirements. We propose to apply rebates (aimed to consume renewable energy surplus) that were traditionally offered to the industrial sector, in the agricultural one. Furthermore, an architecture is proposed to overcome some of the limitations that can hinder the adoption of such rebates. The architecture integrates scheduling techniques that have been well studied in the networking literature.Numerical analysis is performed to validate our model and evaluate the proposed scheduling mechanisms, based on real data from a soybean producer and from the corresponding electricity operator. Results indicate that significant cost reductions can be obtained, in particular if the rebates are considered.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2019
ISBN (Electronic)9781538680995
DOIs
StatePublished - Oct 2019
Event2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2019 - Beijing, China
Duration: 21 Oct 201923 Oct 2019

Publication series

Name2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2019

Conference

Conference2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2019
Country/TerritoryChina
CityBeijing
Period21/10/1923/10/19

Keywords

  • Energy Management
  • Flexibility
  • Irrigation
  • Smart Grids

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Optimization
  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Transportation

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