REPS: simulating which retrofit policy actually reaches Indonesia's Type 36 homes
A browser-based policy simulator that scores subsidies, green finance, mandates, and behavioural nudges on adoption, cost-effectiveness, and equity — built on the engineering results from my net-zero Type 36 thesis.
My net-zero Type 36 thesis showed that a low-cost "Cooling Survival Kit" can cut simulated electricity use by ~57%. The next question — the one policymakers actually ask — is which instrument gets households to adopt it?
REPS (Residential Retrofit Policy Simulator) is a transparent, browser-based prototype I built to explore that question. It couples the engineering savings from my Energy3D work to a discrete-choice (logit) model of household adoption, then lets you pull policy levers and watch the trade-offs unfold.
What you can do with it
Open the interactive simulator → and try:
- Consumer subsidies — how much of the retrofit cost the government covers
- Green financing — subsidised loans that remove upfront liquidity constraints
- Construction mandates — requiring the kit on new builds
- Behavioural nudges — campaigns that offset adoption friction
Sliders also expose the assumptions that matter: present-biased discount rates, rebound effects (savings taken as comfort rather than cash), rationed-comfort welfare for poorer deciles, and adoption friction — the behavioural barriers behind the energy-efficiency gap.
What it outputs
For any policy mix, REPS aggregates over 10 income deciles (illustrative Indonesian urban ranges, or your own CSV import):
- Adoption rate and households retrofitted
- Electricity and CO₂ savings
- Fiscal cost, cost per ton CO₂, and cost per household
- Equity charts — who adopts and who benefits (the poor gain most in comfort, the rich in cash)
- A four-instrument comparison table — mandate vs subsidy vs green finance vs nudge — with no single winner on every criterion
The model, honestly
Per household, yearly net benefit is:
NB = cash saving + value of recovered comfort − annualised cost of the retrofit
Adoption follows a logit on a benefit-vs-affordability index, penalised by friction and liquidity constraints, boosted by nudges, and forced on new builds under a mandate. Parameters come from my thesis (57% saving, ~IDR 8M retrofit cost), PLN tariffs, and IEA/ESDM grid emission factors.
Caveats I'll state up front: the logit scale is assumed, not econometrically estimated; income deciles are representative, not survey data; comfort valuation is a parameter, not measured. Everything is adjustable so the sensitivity is visible. This is a decision-support prototype — the doctoral step would be estimating preferences from revealed-choice data.
Why it matters
Indonesia's "One Million Houses" program locks millions of households into thermally poor envelopes. My thesis showed the engineering case for a cheap retrofit; REPS shows the policy design case — which lever reaches the most households, at what fiscal cost, and whether the poorest deciles are left behind.
Try the simulator → · Read the net-zero Type 36 summary → · Full paper on ResearchGate →