{ "nbformat": 4, "nbformat_minor": 5, "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "name": "python", "version": "3" }, "colab": { "name": "SolarHearth_Power_Cost_Time.ipynb", "provenance": [] } }, "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# JN-SolarHearth · Power, Cost, and Time\n", "\n", "**Provenance:** generated 2026-08-10 by `build_jn_solarhearth.py` · companion to\n", "[solarhearth.pages.dev](https://solarhearth.pages.dev) · a concept study, not a product.\n", "\n", "**Discipline (the JN convention):** every figure below is **derived** from the single\n", "constants cell and asserted against a **dated baseline checkpoint** \u2014 never hardcoded\n", "in the logic. Change an assumption in `C`, re-run all: every number and chart moves,\n", "and the gates report exactly which results drifted from the 2026-08-10 checkpoint.\n", "Runs on Google Colab as-is (plotly is preinstalled); no pip installs needed.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## \u00a70 \u00b7 Assumptions\n", "\ud83d\udcdd **Assumption:** one dict `C` carries every parameter \u2014 solar resource, component\n", "prices, loads, the MOF sorption curve, the time ledger. **Plan:** all later cells\n", "read only `C` and each other's derived values. **Why:** a notebook that types its\n", "answers into the chart calls decays silently; this one can't.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# ===================== SINGLE SOURCE OF ASSUMPTIONS =====================\n", "# Change a value here, re-run all -> every figure and chart moves with it.\n", "# The BASELINE below is the 2026-08-10 checkpoint of derived results; a mismatch\n", "# means the constants changed and the gates will tell you exactly where.\n", "\n", "C = dict(\n", " # --- solar resource & power costs ---\n", " ghi_kwh_m2_day = 5.5, # design solar resource (E.Africa / MENA / S.Asia)\n", " pv_derate = 0.78, # dust, temperature, wiring\n", " pv_usd_per_w = 0.45, # installed small-scale\n", " batt_usd_kwh = 160.0, # LiFePO4, usable\n", " module_wp = 320, # one PV module\n", "\n", " # --- daily electrical loads (Wh) ---\n", " loads = {\n", " \"Induction cooking (2 meals)\": 2000,\n", " \"Lights, phones, comms, radio/fan\": 465,\n", " \"Flow pasteurizer, 20 L @ 12.3 Wh/L\": 246,\n", " \"UV-C polish, 20 L\": 4,\n", " \"Chlorinator + test kit + sensors\": 10,\n", " },\n", " batt_kwh = 2.0, # dusk meal 1.2 + overnight 0.5 + buffer\n", "\n", " # --- flywheel comparison ---\n", " fly_standby_loss_hr = 0.05, # optimistic for low-cost bearings\n", " fly_usd_kwh = 2000.0,\n", " fly_stored_dusk_kwh = 1.5,\n", "\n", " # --- one-time hardware ($) ---\n", " hw = {\n", " \"Induction hob 1.8 kW\": 65,\n", " \"Enclosure, tank, plumbing, controls\": 170,\n", " \"Phones/lights/comms/radio/fan kit\": 292,\n", " \"UV-C flow cell\": 60,\n", " \"Water test kit + incubator\": 45,\n", " \"Electrochlorination cell\": 90,\n", " \"Flow pasteurizer + counterflow HX\": 95,\n", " \"Arsenic cartridge (FeOOH, loaded)\": 50,\n", " \"Fluoride column (alumina/bone char)\": 60,\n", " },\n", " consumables_yr = (77, 163), # media + salt + 3%-capex maintenance, lo..hi\n", " life_years = 8,\n", "\n", " # --- cooking-only tiers (name, cook_kwh, batt_kwh, extra_wh, extra_$, bop_$, hobs) ---\n", " tiers = [\n", " (\"A. Sun-hours cooker (no battery)\", 2.0, 0.15, 0, 0, 110, 1),\n", " (\"B. Core cooker (evening meal)\", 2.0, 1.5, 0, 0, 140, 1),\n", " (\"C. Home hub (light add-ons)\", 2.0, 1.9, 465, 292, 170, 1),\n", " (\"D. Home hub + fridge\", 2.0, 2.6, 1465, 552, 170, 1),\n", " (\"E. Cluster kitchen (5 hh)\", 10.0, 6.0, 465, 292, 450, 3),\n", " ],\n", " hob_usd = 65,\n", "\n", " # --- MOF water-from-air ---\n", " mof_uptake_l_kg = {20: 0.22, 30: 0.32, 50: 0.42}, # per cycle, by night RH%\n", " desorb_mj_per_l = 3.1,\n", " heat_recovery = 0.40, # active mode\n", " fan_ctrl_kwh_l = 0.10,\n", " coll_eff = 0.55, # glazed solar-thermal box\n", " coll_usd_m2 = 85.0,\n", " mof_usd_kg_range = (30, 80),\n", " rh_range = (20, 30, 50),\n", " bop_household = 260.0, bop_cluster = 900.0,\n", " mof_life_years = 10, maint_frac_yr = 0.03,\n", " trucking_usd_m3 = (5, 30),\n", "\n", " # --- women's time ledger (hours/day, before -> with unit) ---\n", " ledger = {\n", " \"Fuel collection & purchase\": (1.5, 0.1),\n", " \"Fire building & tending\": (0.8, 0.2),\n", " \"Water queuing & carrying\": (1.5, 0.5),\n", " \"Laundry by hand\": (1.7, 0.3),\n", " },\n", " shadow_wage_usd_hr = (0.25, 0.60),\n", ")\n", "\n", "BASELINE = {\"load_wh\": 2725.0, \"pv_w\": 635.198, \"yield_wh\": 2745.6, \"fly_left_kwh\": 0.811, \"capex\": 1532.839, \"tier_core\": 655.0, \"tier_hub\": 1090.0, \"awh20a_lo\": 3531.0, \"awh20a_hi\": 5479.0, \"saved_yr_h\": 1606.0, \"val_lo\": 401.5, \"val_hi\": 963.6} # 2026-08-10 checkpoint -- regenerated, never hand-edited\n", "\n", "def gate(name, derived, tol=0.5):\n", " \"\"\"Compare a derived figure to its baseline; DIAGNOSE and halt on drift.\"\"\"\n", " base = BASELINE[name]\n", " if abs(derived - base) > tol:\n", " raise AssertionError(\n", " f\"GATE {name}: derived {derived} != baseline {base} \"\n", " f\"(checkpoint 2026-08-10). A constant changed -- if intentional, \"\n", " f\"re-run the generator to stamp a new baseline.\")\n", " return derived\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## \u00a71 \u00b7 Power\n", "\ud83d\udcdd **Assumption:** design solar resource 5.5 kWh/m\u00b2/day with a 0.78 derate; the load\n", "is the full unit (cooking + water treatment + accessories). **Plan:** derive the\n", "daily load, size the PV array in whole modules, check yield closure, and give the\n", "flywheel its fair hearing. **Why:** the array must be sized from the load, not the\n", "other way around \u2014 and the storage choice should be arithmetic, not fashion.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# ----------------------------- POWER -----------------------------\n", "wh_per_pvw = C[\"ghi_kwh_m2_day\"] * C[\"pv_derate\"] # Wh/day per W of PV\n", "load_wh = sum(C[\"loads\"].values())\n", "pv_w = load_wh / wh_per_pvw\n", "modules = -(-pv_w // C[\"module_wp\"]) # ceil\n", "yield_wh = modules * C[\"module_wp\"] * wh_per_pvw\n", "pv_cost = pv_w * C[\"pv_usd_per_w\"]\n", "batt_cost = C[\"batt_kwh\"] * C[\"batt_usd_kwh\"]\n", "\n", "# flywheel: overnight retention + cost ratio\n", "fly_left = C[\"fly_stored_dusk_kwh\"] * (1 - C[\"fly_standby_loss_hr\"]) ** 12\n", "fly_ratio = C[\"fly_usd_kwh\"] / C[\"batt_usd_kwh\"]\n", "\n", "print(f\"daily load {load_wh:>7.0f} Wh\")\n", "print(f\"PV required {pv_w:>7.0f} W -> {modules:.0f} x {C['module_wp']} Wp modules\")\n", "print(f\"array yield {yield_wh:>7.0f} Wh/day (closure vs load: {yield_wh/load_wh:5.1%})\")\n", "print(f\"battery {C['batt_kwh']} kWh (${batt_cost:.0f}); PV ${pv_cost:.0f}\")\n", "print(f\"flywheel at dawn {fly_left:.2f} kWh of {C['fly_stored_dusk_kwh']} \"\n", " f\"({fly_left/C['fly_stored_dusk_kwh']:.0%} kept), {fly_ratio:.0f}x battery $/kWh\")\n", "\n", "gate(\"load_wh\", load_wh); gate(\"pv_w\", pv_w); gate(\"yield_wh\", yield_wh)\n", "gate(\"fly_left_kwh\", fly_left, tol=0.01)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\ud83d\udcdd **Found:** the load sizes to two 320 Wp modules with ~1% closure margin, and the\n", "flywheel keeps roughly half its dusk charge by dawn at 12\u00d7 the battery's $/kWh \u2014\n", "the gate cells above HALT if any of this drifts from the checkpoint. **Verify:**\n", "`gate()` compares each derived figure to the dated baseline and diagnoses drift.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# viz -- daily load budget + flywheel retention (derived, never typed literals)\n", "import plotly.graph_objects as go\n", "f = go.Figure(go.Bar(x=list(C[\"loads\"].values()), y=list(C[\"loads\"].keys()),\n", " orientation=\"h\", marker_color=\"#C97A10\"))\n", "f.update_layout(title=f\"Daily electrical load: {load_wh:,.0f} Wh -> {modules:.0f} x \"\n", " f\"{C['module_wp']} Wp modules\", height=280,\n", " margin=dict(l=10, r=10, t=40, b=10))\n", "f.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\u26a0 **What this chart could mislead about:** the bars are *electrical* energy only \u2014\n", "the pasteurizer's small bar rides on a large *thermal* flow made cheap by heat\n", "recovery, and cooking's dominance is the design's point, not an inefficiency.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## \u00a72 \u00b7 Cost\n", "\ud83d\udcdd **Assumption:** hardware prices are parametric estimates (PV $0.45/W, LiFePO4\n", "$160/kWh, commodity hob), not vendor quotes. **Plan:** build the full-unit BOM from\n", "`C`, reproduce the cooking-only tier ladder, then sweep the water-from-air module\n", "across its two dominant uncertainties (night humidity 20\u201350% RH, MOF $30\u201380/kg).\n", "**Why:** the ranges ARE the result \u2014 a single point number would overclaim.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# ----------------------------- COST: full-unit BOM -----------------------------\n", "bom_groups = {\n", " \"Power system\": {\"PV array\": pv_cost, \"LiFePO4 battery\": batt_cost},\n", " \"Core + modules + options\": dict(C[\"hw\"]),\n", "}\n", "capex = sum(v for g in bom_groups.values() for v in g.values())\n", "cons_lo, cons_hi = C[\"consumables_yr\"]\n", "yr_lo = capex / C[\"life_years\"] + cons_lo\n", "yr_hi = capex / C[\"life_years\"] + cons_hi\n", "\n", "print(f\"FULL UNIT CAPEX ${capex:,.0f}\")\n", "print(f\"all-in per year ${yr_lo:.0f}-{yr_hi:.0f} (${yr_lo/12:.0f}-{yr_hi/12:.0f}/mo; charcoal displaced $15-40/mo)\")\n", "gate(\"capex\", capex)\n", "\n", "# ----------------------------- COST: cooking-only tiers -----------------------------\n", "tier_rows = []\n", "for name, cook, batt, xwh, xcap, bop, hobs in C[\"tiers\"]:\n", " elec = cook + xwh / 1000\n", " tier_capex = (elec * 1000 / wh_per_pvw) * C[\"pv_usd_per_w\"] \\\n", " + batt * C[\"batt_usd_kwh\"] + C[\"hob_usd\"] * hobs + bop + xcap\n", " tier_rows.append((name, elec, round(tier_capex)))\n", " print(f\"{name:<36} {elec:>5.2f} kWh/d ${tier_capex:>6,.0f}\")\n", "gate(\"tier_core\", tier_rows[1][2]); gate(\"tier_hub\", tier_rows[2][2])\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# ----------------------------- COST: water-from-air sweep -----------------------------\n", "def awh_config(liters_day, rh, mof_usd_kg, mode, households=1):\n", " uptake, cycles = C[\"mof_uptake_l_kg\"][rh], (1 if mode == \"passive\" else 3)\n", " mof_kg = liters_day / (uptake * cycles)\n", " mof_cost = mof_kg * mof_usd_kg\n", " if mode == \"passive\":\n", " th_kwh = liters_day * C[\"desorb_mj_per_l\"] / 3.6\n", " coll_m2 = th_kwh / (C[\"ghi_kwh_m2_day\"] * C[\"coll_eff\"])\n", " coll_cost = coll_m2 * C[\"coll_usd_m2\"]\n", " water_e = liters_day * 0.05\n", " else:\n", " coll_cost = 0.0\n", " kwh_l = C[\"desorb_mj_per_l\"] * (1 - C[\"heat_recovery\"]) / 3.6 + C[\"fan_ctrl_kwh_l\"]\n", " water_e = liters_day * kwh_l\n", " cook_e = 2.0 * households\n", " total_e = water_e + cook_e\n", " pv_cost_c = (total_e * 1000 / wh_per_pvw) * C[\"pv_usd_per_w\"]\n", " batt_kwh = 1.2 * households + 0.3 + (water_e * 0.5 if mode == \"active\" else 0.1)\n", " bop = C[\"bop_cluster\"] if households > 1 else C[\"bop_household\"]\n", " cap = pv_cost_c + batt_kwh * C[\"batt_usd_kwh\"] + mof_cost + coll_cost + bop \\\n", " + C[\"hob_usd\"] * min(households, 4)\n", " lifetime_l = liters_day * 365 * C[\"mof_life_years\"]\n", " lifetime_cost = cap * (1 + C[\"maint_frac_yr\"] * C[\"mof_life_years\"]) + mof_cost\n", " return round(cap), round(lifetime_cost / lifetime_l * 1000)\n", "\n", "AWH = [(\"HH 6 L/d passive\", 6, \"passive\", 1), (\"HH 20 L/d passive\", 20, \"passive\", 1),\n", " (\"HH 20 L/d active\", 20, \"active\", 1), (\"Cluster 100 L/d\", 100, \"active\", 5)]\n", "awh_rows = {}\n", "for label, L, mode, hh in AWH:\n", " pts = [awh_config(L, rh, mc, mode, hh)\n", " for rh in C[\"rh_range\"] for mc in C[\"mof_usd_kg_range\"]]\n", " caps, usdm3 = [p[0] for p in pts], [p[1] for p in pts]\n", " awh_rows[label] = (min(caps), max(caps), min(usdm3), max(usdm3))\n", " print(f\"{label:<20} capex ${min(caps):>6,}-{max(caps):<7,} water ${min(usdm3):>3}-{max(usdm3)}/m3\")\n", "print(f\"{'Trucked benchmark':<20} water ${C['trucking_usd_m3'][0]}-{C['trucking_usd_m3'][1]}/m3\")\n", "gate(\"awh20a_lo\", awh_rows[\"HH 20 L/d active\"][0]); gate(\"awh20a_hi\", awh_rows[\"HH 20 L/d active\"][1])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\ud83d\udcdd **Found:** the full unit lands at the checkpointed capex with all-in running cost\n", "inside the charcoal band it displaces; water-from-air stays 2\u201310\u00d7 trucked-water\n", "cost across the whole sweep, which is why it ships as the module of last resort.\n", "**Verify:** gates on the BOM total, two tier anchors, and the 20 L/day active\n", "range ends.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# viz -- tier capex + water-from-air ranges\n", "import plotly.graph_objects as go\n", "f = go.Figure(go.Bar(x=[r[2] for r in tier_rows], y=[r[0] for r in tier_rows],\n", " orientation=\"h\", marker_color=\"#C97A10\"))\n", "f.update_layout(title=\"Cooking-only tiers, capex ($)\", height=280,\n", " margin=dict(l=10, r=10, t=40, b=10))\n", "f.show()\n", "\n", "labels = list(awh_rows)\n", "f2 = go.Figure(go.Bar(x=[awh_rows[k][1] - awh_rows[k][0] for k in labels],\n", " base=[awh_rows[k][0] for k in labels], y=labels,\n", " orientation=\"h\", marker_color=\"#0E7490\"))\n", "f2.update_layout(title=\"Water-from-air capex range across 20-50% RH x $30-80/kg MOF ($)\",\n", " height=260, margin=dict(l=10, r=10, t=40, b=10))\n", "f2.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\u26a0 **What these charts could mislead about:** tier bars are capex only (tier E serves\n", "5 households \u2014 per-household it is the *cheapest* tier); the water-from-air ranges\n", "span *uncertainty*, not choice \u2014 a deployment sits at one point of each bar, and\n", "the bar's width is exactly why the module is optional.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## \u00a73 \u00b7 Time\n", "\ud83d\udcdd **Assumption:** the ledger's hours are mid-range planning figures from a wide\n", "field literature (fuel collection, fire tending, water hauling, hand laundry);\n", "shadow wages $0.25\u20130.60/h for informal-sector labor. **Plan:** total the ledger,\n", "annualize, monetize, and compare against the unit's all-in yearly cost from \u00a72.\n", "**Why:** the claim \"the unit pays for itself in returned time alone\" must survive\n", "its own arithmetic at the *low* wage bound, or it doesn't get made.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# ----------------------------- TIME: the women's-time ledger -----------------------------\n", "before = sum(b for b, a in C[\"ledger\"].values())\n", "after = sum(a for b, a in C[\"ledger\"].values())\n", "saved_day = before - after\n", "saved_yr = saved_day * 365\n", "w_lo, w_hi = C[\"shadow_wage_usd_hr\"]\n", "val_lo, val_hi = saved_yr * w_lo, saved_yr * w_hi\n", "\n", "for task, (b, a) in C[\"ledger\"].items():\n", " print(f\"{task:<30} {b:>4.1f} -> {a:.1f} h/day\")\n", "print(f\"{'TOTAL':<30} {before:>4.1f} -> {after:.1f} (saves {saved_day:.1f} h/day, {saved_yr:,.0f} h/yr)\")\n", "print(f\"labor value at ${w_lo}-{w_hi}/h: ${val_lo:,.0f}-{val_hi:,.0f}/yr\")\n", "print(f\"unit all-in cost: ${yr_lo:.0f}-{yr_hi:.0f}/yr\")\n", "print(f\"-> the unit repays itself in returned time alone\" if val_lo > yr_hi else \"-> check parameters\")\n", "\n", "gate(\"saved_yr_h\", saved_yr, tol=1); gate(\"val_lo\", val_lo, tol=1); gate(\"val_hi\", val_hi, tol=1)\n", "assert val_lo > yr_hi, \"time value should exceed all-in cost at the low wage bound\"\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\ud83d\udcdd **Found:** ~4.4 hours returned daily \u2248 1,600 h/yr \u2014 a full-time job's worth of\n", "labor capacity \u2014 worth more per year at the lowest shadow wage than the unit costs\n", "all-in. The final `assert` enforces that ordering; if a price rise or a ledger\n", "correction ever breaks it, this notebook fails loudly rather than letting the\n", "claim stand. **Verify:** gates on saved hours and both value bounds.\n" ] }, { "cell_type": "code", "metadata": {}, "execution_count": null, "outputs": [], "source": [ "# viz -- the time ledger, before vs with the unit\n", "import plotly.graph_objects as go\n", "tasks = list(C[\"ledger\"])\n", "f = go.Figure([\n", " go.Bar(name=\"today\", x=[C[\"ledger\"][t][0] for t in tasks], y=tasks,\n", " orientation=\"h\", marker_color=\"#B4B2A9\"),\n", " go.Bar(name=\"with unit\", x=[C[\"ledger\"][t][1] for t in tasks], y=tasks,\n", " orientation=\"h\", marker_color=\"#0E7490\"),\n", "])\n", "f.update_layout(barmode=\"group\", height=300, title=\n", " f\"A woman's day: {before:.1f} h -> {after:.1f} h ({saved_yr:,.0f} h/yr returned)\",\n", " margin=dict(l=10, r=10, t=40, b=10))\n", "f.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\u26a0 **What this chart could mislead about:** these are planning estimates, not\n", "measurements \u2014 individual settlements vary substantially, and caregiving hours\n", "returned by less diarrheal illness are real but deliberately *not counted*.\n", "A deployment should run its own time-use baseline (it belongs in the pilot\n", "protocol) and let measured data replace this ledger.\n", "\n", "---\n", "*Models this notebook mirrors: [awh_model.py](https://solarhearth.pages.dev/models/awh_model.py) \u00b7\n", "[cook_only_model.py](https://solarhearth.pages.dev/models/cook_only_model.py) \u00b7\n", "[purification_model.py](https://solarhearth.pages.dev/models/purification_model.py) \u00b7\n", "[full_unit_pricing.py](https://solarhearth.pages.dev/models/full_unit_pricing.py)*\n" ] } ] }