Controlling the energy production at home

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Controlling the energy production at home

• Maurice Bosman
• PhD TW colloquium

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The year is AD 2008

• And electricity is entirely produced by large
  power plants.
• Well not entirely!
• There is a strong trend towards a distributed
  elec-tricity production.

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Energy market

• Liberalised on July 1, 2004
• Competition!
• Electricity producers vs electricity suppliers
  meet on electricity market (APX)
• Grid operators are obliged to allow all suppliers
  in their region
• Entrance possibility distributed production

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Distributed electricity production

• Less transport losses
• Higher efficiency of production at home
• Use of renewable sources
• CO2 reduction
• Relief of loads of electricity grid
• Production capacity limited
• Demand/supply matching

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Electricity production at home
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Heat production at home
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MicroCHP

• Micro Combined Heat and Power
• Input gas
• Output electricity and heat
• Electricity consumed at home or delivered to the
  grid
• Heat consumed at home (no concrete plans to share
  heat within a neighbourhood)

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Heat demand in a house

• Central heating, tap water
• Immediate supply by household device (unless you
  live in Enschede Zuid)
• Heat buffer necessary for scheduling

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Electricity demand in a house

• Fridge, tv, coffee machine,
• Supply is no issue (unless you live in
  Haaksbergen)
• Electricity pricing
• Electricity buffer possible, but not necessary

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If you live in Haaksbergen
microCHP
radiator

grid
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Problem setting

• Use a microCHP in house
• Apply this onto many houses
• Electricity supplier offers global control of the
  appliances

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Research goal

• Study the consequences of introducing a fleet of
  microCHPs
• Controllability/scalability
• Optimization heuristics

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Controllability/scalability

• Global Scheduler
• Local Scheduler (Embedded Computer)
• Hierarchical structure
• Hard Constraints
• Household comfort
• Limited communication
• Real time decision making

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Optimization heuristics

• Several objectives
• Minimize total electricity costs
• Minimize total energy costs
• Maximize total electricity revenue
• Minimize transportational losses
• Minimize peak loads at transformers
• Make use of electricity market (APX)
• Make use of electricity and heat profiles

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APX prices
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Scheduling

• Offline use all available information
• Online receive a job and schedule immediately
  (example earliest possible)

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Our scheduling problem

• Jobs switched on microCHP appliances
• Jobs have undetermined length!
• Online problem repetitive jobs

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ILP formulation

• Decision variable
• Accountancy equations

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ILP formulation

• Objective minimize/maximize something
• Heatstore below LL switch on
• Heatstore above UL switch off

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ILP formulation

• Need to run minimum runtime MR
• Stay switched off for minimum time MO
• Fleet capacity restrictions

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Scheduling problem

• Optimal values (AIMMS)

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Scheduling problem

• When is it good to use longer jobs?
• Divide jobs into classes
• Heatstore information
• Runtime information
• Consumption prediction
• Make decisions that balance classes!
• Make switch off decisions!

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Questions

• ?