Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price

The world’s growing demand for food can be met by agricultural technology. Use of artificial light to supplement natural sunlight in greenhouse cultivation is one of the most common techniques to increase greenhouse production of food crops. However, artificial light requires significant electrical...

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Main Authors: Mehdi Mahdavian, Naruemon Wattanapongsakorn
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2017/6862038
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spelling doaj-9d3f5bec3f394f2b97148682eb8b7d272020-11-25T00:20:19ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472017-01-01201710.1155/2017/68620386862038Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market PriceMehdi Mahdavian0Naruemon Wattanapongsakorn1Department of Computer Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha-Utid Rd., Bangmod, Toongkru, Bangkok 10140, ThailandDepartment of Computer Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha-Utid Rd., Bangmod, Toongkru, Bangkok 10140, ThailandThe world’s growing demand for food can be met by agricultural technology. Use of artificial light to supplement natural sunlight in greenhouse cultivation is one of the most common techniques to increase greenhouse production of food crops. However, artificial light requires significant electrical energy, which increases the cost of greenhouse production and can reduce profit. This paper models the increments to greenhouse productivity as well as the increases in cost from supplemental electric lighting, in a situation where the greenhouse is one of the elements of a smart grid, a system where the electric energy market is dynamic and prices vary over time. We used our models to calculate the optimum values for supplemental light and the required electrical energy for HPS lamps in the greenhouse environment, using cherry tomato cultivation as a case study crop. We considered two optimization techniques: iterative search (IS) and genetic algorithm (GA). The two approaches produced similar results, although the GA method was much faster. Both approaches verify the advantages of using optimal supplemental light in terms of increasing production and hence profit.http://dx.doi.org/10.1155/2017/6862038
collection DOAJ
language English
format Article
sources DOAJ
author Mehdi Mahdavian
Naruemon Wattanapongsakorn
spellingShingle Mehdi Mahdavian
Naruemon Wattanapongsakorn
Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price
Mathematical Problems in Engineering
author_facet Mehdi Mahdavian
Naruemon Wattanapongsakorn
author_sort Mehdi Mahdavian
title Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price
title_short Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price
title_full Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price
title_fullStr Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price
title_full_unstemmed Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price
title_sort optimizing greenhouse lighting for advanced agriculture based on real time electricity market price
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2017-01-01
description The world’s growing demand for food can be met by agricultural technology. Use of artificial light to supplement natural sunlight in greenhouse cultivation is one of the most common techniques to increase greenhouse production of food crops. However, artificial light requires significant electrical energy, which increases the cost of greenhouse production and can reduce profit. This paper models the increments to greenhouse productivity as well as the increases in cost from supplemental electric lighting, in a situation where the greenhouse is one of the elements of a smart grid, a system where the electric energy market is dynamic and prices vary over time. We used our models to calculate the optimum values for supplemental light and the required electrical energy for HPS lamps in the greenhouse environment, using cherry tomato cultivation as a case study crop. We considered two optimization techniques: iterative search (IS) and genetic algorithm (GA). The two approaches produced similar results, although the GA method was much faster. Both approaches verify the advantages of using optimal supplemental light in terms of increasing production and hence profit.
url http://dx.doi.org/10.1155/2017/6862038
work_keys_str_mv AT mehdimahdavian optimizinggreenhouselightingforadvancedagriculturebasedonrealtimeelectricitymarketprice
AT naruemonwattanapongsakorn optimizinggreenhouselightingforadvancedagriculturebasedonrealtimeelectricitymarketprice
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