Estimating energy consumption in Australia using a spatial microsimulation model Presentation to ANZRSAI Conference, 2014 Robert Tanton 15 November2014

Authors Robert Tanton, NATSEM, Institute for Governance and Policy Analysis, University of Canberra Yogi Vidyattama, NATSEM, Institute for Governance and Policy Analysis, University of Canberra

Structure The Problem ● Planning for population growth ● Future use of energy Spatial Microsimulation How to use spatial microsimulation to estimate energy expenditure Advantages and Disadvantages of this approach Conclusions

The Problem Population growth with constraints ● Demographic models based on births, deaths and migration ● No constraints –Land –Food –Energy –Water How inform future planning?

Example of the ACT Land-Locked Area to the South ● national park Areas can’t expand ● Hills and ridges ● Commonwealth land ● Lakes

Example of the ACT Using a cohort-component method, ACT population predicted to grow from 390,000 people (2014) to 682,000 people (2054) How much energy will these people need? Will we have the capacity to supply it? What will we need to do to service this increased population (more solar, wind, etc)? How will energy saving appliances contribute?

Spatial Microsimulation Small area estimation technique that derives a synthetic dataset for each small area Synthetic dataset for small area based on real data from survey or completely synthetic ● Use survey data with reweighting or selection ● Use completely synthetic if don’t have survey with information required Provides unit record data for all small areas Use this for cross-tabulations, projections, imputing more data, etc

8 Reweighting to small areas turning the national household weights in the SIH and file into … … household weights for small-areas

How apply to energy? Create synthetic people/households for each small area as a base (2014) Grow areas using cohort component method (Births/Deaths/Migration) ● Assign births to families –If assigned to a house that is too small, move them ● Assign deaths randomly based on Age ● Allocate in-migration to either old or new households based on Incomes, Work, etc ● Move people ‘down sizing’ when number of people exceeds number of rooms ● Allocate people of certain age group to new households (moving out) ● Allocate separations to new households

How estimate energy consumption? Impute household energy use using current variables ● Household size ● Number of bedrooms ● Flat/House ● Construction type?

Remember We have some detail on every resident and house in an area – can be as complex as we want

Quick Application Use spatial microsimulation to estimate energy expenditure Benchmarks: BenchmarkClassifications Total number of people in the household >=6 Dwelling StructureSeparate House; Semi-Detached house 1 storey; Semi-detached house 2 stories; Flat with 1 or 2 storeys; Flat with 3 storeys; Flat with 4 or more storeys; Flat attached to a house; Caravan, cabin, improvised home, flat attached to shop Number of bedrooms in householdNone >=6

Data 2011 Census benchmarks ● Only ACT areas 2009/10 ABS Household Expenditure Survey (HES) ● Only included records from the ACT

Validation

Results – Expenditure on Energy, Houses only

Results – Expenditure on Energy, Flats 1 or 2 Storey

Advantages Flexibility ● Look at energy consumption for different household types Scenario modelling – ‘What If’ ● Technological change ● Renewable energy

Disadvantages Data intensive ● Survey, Census, Benchmarks ● Creating 25 Million people across Australia? –Start with ACT Complexity ● Explaining to users? Modelling interactions?

Conclusions Spatial Microsimulation can provide spatial base data for a model of sustainability and could be used to estimate energy use in small areas given characteristics of the population The final model would be complex but would provide realistic scenario modelling for planners