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Goal intervals in dynamic multicriteria problems

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Goal intervals in dynamic multicriteria problems The case of MOHO Juha M ntysaari Decision problem of space heating consumers Under time varying electricity tariff ... – PowerPoint PPT presentation

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Title: Goal intervals in dynamic multicriteria problems


1
Goal intervals in dynamic multicriteria problems
  • The case of MOHO

Juha Mäntysaari
2
Decision problem of space heating consumers
  • Under time varying electricity tariff space
    heating consumers can save in heating costs by
  • Storing heat in to the house during low tariff
    hours
  • Trading living comfort to costs savings
  • A dynamic decision problem

3
Space heating problem
  • Space heating consumers try to
  • MIN Heating costs
  • MAX Living comfort
  • subject to
  • Dynamic price of the electricity
  • Dynamics of house
  • Other (physical) constraints

4
Dynamics of the house
Q(t)Q(t-1)Dtq(t-1)-d(t-1) where d(t)
aDt(T(t) - Tout(t)) Q(t) T(t)/C, (b
1/C) Þ T(t) T(t-1) bDtq(t-1) -abDt(T(t-1) -
Tout(t-1)) Units Q kWh, a kW/C, C
kWh/C
5
Example houses
House 2
House 1
6
Information summary
7
Goal models
1. Hard constraint (pipe is hard)
2. Soft constraints (pipe is soft)Interval goal
programming
3. Hard constraint with a goal inside(pipe with
a goal)
8
Hard constraints
9
Soft constraints
10
Hard constraints with a goal
11
Goal models (summary)
1. Hard constraints
2. Soft constraints
3. Hard constraints with a goal
12
MultiObjective Household heating Optimization
(MOHO)
13
Idea of MOHO
  • Minimize heating costs using hard lower and upper
    bounds for indoor temperature
  • The case of hard constraints
  • Ask How many percents would you like to
    decrease the heating costs from the current
    level?
  • Solve again trying to achieve the desired
    decrease in cost by relaxing the indoor
    temperature upper bound
  • The e-constraints method (upper bound must be
    active in order to succeed)

14
Example House 2 (1/4)
Minimized heating costs
15
Example House 2 (2/4)
Decreased costs by 5
16
Example House 2 (3/4)
Decreased again by 5
17
Example House 2 (4/4)
And again by 5
18
Summary
  • Model and parameters of the house identified
  • Depending on the definition of the living
    comfort different multicriteria models can be
    used
  • Benefits of the simplified approach
  • Only bounds of the indoor temperature asked
  • Comparison and tradeoff only with heating costs
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