Strategies to reduce electricity consumption on dairy farms : an economic and environmental assessment

J.R. Upton

Research output: Thesisinternal PhD, WUAcademic

Abstract

The aim of this thesis was to assess how, and to what extent, do managerial and technology changes affect electricity consumption, associated costs and greenhouse gas (GHG) emissions of dairy farms. Dairy farms in Ireland are expected to expand in the future, due to policy incentives and the abolishment of European Union milk quotas in 2015, which will result in an increased use of resources such as land, water, and energy, and increased emissions to the environment. In order to develop strategies to reduce electricity consumption associated costs and GHG emissions, it was necessary to understand the consumption trends and the hot-spots of electricity consumption within the farm. Therefore, we performed a life cycle assessment by quantifying the energy use on 22 commercial Irish dairy farms, from cradle-to-farm-gate. This analysis demonstrated that a total of 31.7 MJ of energy was required to produce one kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity consumption was found to represent 12% of total cradle-to-farm-gate energy use or 60% of direct energy, and was centered on milk harvesting. Following this analysis we devised two main groups of strategies, i.e. ‘cost strategies’ and ‘energy strategies’. ‘Cost strategies’ consisted of measures that could save on-farm costs but no energy or related emissions, such as, moving to a new electricity tariff or decoupling large electricity users, such as water heating, from milking times and shifting them to off-peak periods when electricity price is lower. Examples of ‘energy strategies’ are; the use of variable speed vacuum pumps on the milking machine, pre-cooling of milk and solar thermal technologies to provide hot water for cleaning purposes. A mechanistic model of electricity consumption that simulates farm equipment on an hourly and monthly basis was developed to further evaluate the ‘cost’ and ‘energy’ strategies. We used this model to show that a Day & Night electricity tariff minimised annual electricity costs, while a Flat tariff would increase the electricity costs by between 16% and 34%, depending on farm size. We also discovered that milking earlier in the morning and later in the evening reduced the simulated annual electricity consumption and related GHG emissions by between 5% and 7%, depending on farm size.  An analysis of ‘energy strategies’ was carried out which revealed that that the ideal blend of technologies to maximise farm profitability while also reducing electricity consumption and GHG emissions, consisted of a direct expansion milk tank with pre-cooling of milk with well water to 15°C, electrical water heating and standard vacuum pumps. An individual farmer can also choose to increase his or her use of renewable energy by adding solar thermal water heating with the trade-off of reduced profitability and negative return on investment figures. This analysis highlighted the need for an investment appraisal approach to technology investments on dairy farms.

LanguageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • de Boer, Imke, Promotor
  • Groot Koerkamp, Peter, Promotor
  • Shalloo, L., Co-promotor, External person
Award date1 Oct 2014
Place of PublicationWageningen
Publisher
Print ISBNs9789462570771
Publication statusPublished - 2014

Fingerprint

environmental assessment
electricity
dairy farming
economics
energy
greenhouse gas emissions
tariffs
heat
milk
vacuum pumps
farms
farm size
water
milking
cooling
farm profitability
milking machines
milk tanks
life cycle assessment
agricultural machinery and equipment

Keywords

  • electricity
  • energy consumption
  • dairy farming
  • reduction
  • costs
  • technology
  • innovations
  • economic analysis
  • environmental assessment

Cite this

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title = "Strategies to reduce electricity consumption on dairy farms : an economic and environmental assessment",
abstract = "The aim of this thesis was to assess how, and to what extent, do managerial and technology changes affect electricity consumption, associated costs and greenhouse gas (GHG) emissions of dairy farms. Dairy farms in Ireland are expected to expand in the future, due to policy incentives and the abolishment of European Union milk quotas in 2015, which will result in an increased use of resources such as land, water, and energy, and increased emissions to the environment. In order to develop strategies to reduce electricity consumption associated costs and GHG emissions, it was necessary to understand the consumption trends and the hot-spots of electricity consumption within the farm. Therefore, we performed a life cycle assessment by quantifying the energy use on 22 commercial Irish dairy farms, from cradle-to-farm-gate. This analysis demonstrated that a total of 31.7 MJ of energy was required to produce one kg of milk solids, of which 20{\%} was direct and 80{\%} was indirect energy use. Electricity consumption was found to represent 12{\%} of total cradle-to-farm-gate energy use or 60{\%} of direct energy, and was centered on milk harvesting. Following this analysis we devised two main groups of strategies, i.e. ‘cost strategies’ and ‘energy strategies’. ‘Cost strategies’ consisted of measures that could save on-farm costs but no energy or related emissions, such as, moving to a new electricity tariff or decoupling large electricity users, such as water heating, from milking times and shifting them to off-peak periods when electricity price is lower. Examples of ‘energy strategies’ are; the use of variable speed vacuum pumps on the milking machine, pre-cooling of milk and solar thermal technologies to provide hot water for cleaning purposes. A mechanistic model of electricity consumption that simulates farm equipment on an hourly and monthly basis was developed to further evaluate the ‘cost’ and ‘energy’ strategies. We used this model to show that a Day & Night electricity tariff minimised annual electricity costs, while a Flat tariff would increase the electricity costs by between 16{\%} and 34{\%}, depending on farm size. We also discovered that milking earlier in the morning and later in the evening reduced the simulated annual electricity consumption and related GHG emissions by between 5{\%} and 7{\%}, depending on farm size.  An analysis of ‘energy strategies’ was carried out which revealed that that the ideal blend of technologies to maximise farm profitability while also reducing electricity consumption and GHG emissions, consisted of a direct expansion milk tank with pre-cooling of milk with well water to 15°C, electrical water heating and standard vacuum pumps. An individual farmer can also choose to increase his or her use of renewable energy by adding solar thermal water heating with the trade-off of reduced profitability and negative return on investment figures. This analysis highlighted the need for an investment appraisal approach to technology investments on dairy farms.",
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author = "J.R. Upton",
note = "WU thesis 5857",
year = "2014",
language = "English",
isbn = "9789462570771",
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Upton, JR 2014, 'Strategies to reduce electricity consumption on dairy farms : an economic and environmental assessment', Doctor of Philosophy, Wageningen University, Wageningen.

Strategies to reduce electricity consumption on dairy farms : an economic and environmental assessment. / Upton, J.R.

Wageningen : Wageningen University, 2014. 171 p.

Research output: Thesisinternal PhD, WUAcademic

TY - THES

T1 - Strategies to reduce electricity consumption on dairy farms : an economic and environmental assessment

AU - Upton, J.R.

N1 - WU thesis 5857

PY - 2014

Y1 - 2014

N2 - The aim of this thesis was to assess how, and to what extent, do managerial and technology changes affect electricity consumption, associated costs and greenhouse gas (GHG) emissions of dairy farms. Dairy farms in Ireland are expected to expand in the future, due to policy incentives and the abolishment of European Union milk quotas in 2015, which will result in an increased use of resources such as land, water, and energy, and increased emissions to the environment. In order to develop strategies to reduce electricity consumption associated costs and GHG emissions, it was necessary to understand the consumption trends and the hot-spots of electricity consumption within the farm. Therefore, we performed a life cycle assessment by quantifying the energy use on 22 commercial Irish dairy farms, from cradle-to-farm-gate. This analysis demonstrated that a total of 31.7 MJ of energy was required to produce one kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity consumption was found to represent 12% of total cradle-to-farm-gate energy use or 60% of direct energy, and was centered on milk harvesting. Following this analysis we devised two main groups of strategies, i.e. ‘cost strategies’ and ‘energy strategies’. ‘Cost strategies’ consisted of measures that could save on-farm costs but no energy or related emissions, such as, moving to a new electricity tariff or decoupling large electricity users, such as water heating, from milking times and shifting them to off-peak periods when electricity price is lower. Examples of ‘energy strategies’ are; the use of variable speed vacuum pumps on the milking machine, pre-cooling of milk and solar thermal technologies to provide hot water for cleaning purposes. A mechanistic model of electricity consumption that simulates farm equipment on an hourly and monthly basis was developed to further evaluate the ‘cost’ and ‘energy’ strategies. We used this model to show that a Day & Night electricity tariff minimised annual electricity costs, while a Flat tariff would increase the electricity costs by between 16% and 34%, depending on farm size. We also discovered that milking earlier in the morning and later in the evening reduced the simulated annual electricity consumption and related GHG emissions by between 5% and 7%, depending on farm size.  An analysis of ‘energy strategies’ was carried out which revealed that that the ideal blend of technologies to maximise farm profitability while also reducing electricity consumption and GHG emissions, consisted of a direct expansion milk tank with pre-cooling of milk with well water to 15°C, electrical water heating and standard vacuum pumps. An individual farmer can also choose to increase his or her use of renewable energy by adding solar thermal water heating with the trade-off of reduced profitability and negative return on investment figures. This analysis highlighted the need for an investment appraisal approach to technology investments on dairy farms.

AB - The aim of this thesis was to assess how, and to what extent, do managerial and technology changes affect electricity consumption, associated costs and greenhouse gas (GHG) emissions of dairy farms. Dairy farms in Ireland are expected to expand in the future, due to policy incentives and the abolishment of European Union milk quotas in 2015, which will result in an increased use of resources such as land, water, and energy, and increased emissions to the environment. In order to develop strategies to reduce electricity consumption associated costs and GHG emissions, it was necessary to understand the consumption trends and the hot-spots of electricity consumption within the farm. Therefore, we performed a life cycle assessment by quantifying the energy use on 22 commercial Irish dairy farms, from cradle-to-farm-gate. This analysis demonstrated that a total of 31.7 MJ of energy was required to produce one kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity consumption was found to represent 12% of total cradle-to-farm-gate energy use or 60% of direct energy, and was centered on milk harvesting. Following this analysis we devised two main groups of strategies, i.e. ‘cost strategies’ and ‘energy strategies’. ‘Cost strategies’ consisted of measures that could save on-farm costs but no energy or related emissions, such as, moving to a new electricity tariff or decoupling large electricity users, such as water heating, from milking times and shifting them to off-peak periods when electricity price is lower. Examples of ‘energy strategies’ are; the use of variable speed vacuum pumps on the milking machine, pre-cooling of milk and solar thermal technologies to provide hot water for cleaning purposes. A mechanistic model of electricity consumption that simulates farm equipment on an hourly and monthly basis was developed to further evaluate the ‘cost’ and ‘energy’ strategies. We used this model to show that a Day & Night electricity tariff minimised annual electricity costs, while a Flat tariff would increase the electricity costs by between 16% and 34%, depending on farm size. We also discovered that milking earlier in the morning and later in the evening reduced the simulated annual electricity consumption and related GHG emissions by between 5% and 7%, depending on farm size.  An analysis of ‘energy strategies’ was carried out which revealed that that the ideal blend of technologies to maximise farm profitability while also reducing electricity consumption and GHG emissions, consisted of a direct expansion milk tank with pre-cooling of milk with well water to 15°C, electrical water heating and standard vacuum pumps. An individual farmer can also choose to increase his or her use of renewable energy by adding solar thermal water heating with the trade-off of reduced profitability and negative return on investment figures. This analysis highlighted the need for an investment appraisal approach to technology investments on dairy farms.

KW - elektriciteit

KW - energiegebruik

KW - melkveehouderij

KW - reductie

KW - kosten

KW - technologie

KW - innovaties

KW - economische analyse

KW - milieutoets

KW - electricity

KW - energy consumption

KW - dairy farming

KW - reduction

KW - costs

KW - technology

KW - innovations

KW - economic analysis

KW - environmental assessment

M3 - internal PhD, WU

SN - 9789462570771

PB - Wageningen University

CY - Wageningen

ER -