#!/usr/bin/env python3 """燃料と電池を「車両システム」として比べ直す計算モデル。 入力: data/assumptions.csv（LOW / BASE / HIGH、出典 ID 付き） 出力: results/*.csv, results/summary.json, results/figures/*.png 使い方: python3 model/vehicle_system_model.py # BASE で計算し results/ を更新 python3 model/vehicle_system_model.py --no-fig # 図を描かない 依存: Python 3.10+、matplotlib（図のみ）。numpy は使わない。 計算の境界: - 「単体」 : 燃料そのもの／電池パックそのもの（質量・体積・円/kWh） - 「車両」 : 国土交通省審査値（WLTC）の燃費・交流電力量消費率で測った車 1 台 - 「設備費」 : 一度払って繰り返し使うもの（電池パック・車両本体） - 「消費費」 : 走るたびに消えるもの（ガソリン・電気） 比べるときは、同じ境界・同じ分母・同じ期間に揃える。 """ from __future__ import annotations import argparse import csv import json from pathlib import Path ROOT = Path(__file__).resolve().parents[1] DATA = ROOT / "data" / "assumptions.csv" RESULTS = ROOT / "results" FIG = RESULTS / "figures" MJ_PER_KWH = 3.6 def load(case: str = "base") -> dict[str, float]: out: dict[str, float] = {} with DATA.open(encoding="utf-8") as f: for row in csv.DictReader(f): out[row["key"]] = float(row[case]) return out # ---------------------------------------------------------------- 単体の比較 def storage_medium(a: dict[str, float]) -> dict[str, float]: """燃料・電池『単体』の数字。ここだけ見ると電池は桁で負ける（それ自体は正しい）。""" hhv_l = a["gasoline_hhv_mj_per_l"] lhv_l = hhv_l * a["gasoline_lhv_factor"] rho = a["gasoline_density_kg_per_l"] lhv_kg = lhv_l / rho gas_kwh_per_kg = lhv_kg / MJ_PER_KWH gas_kwh_per_l = lhv_l / MJ_PER_KWH pack_kwh_per_kg = a["battery_pack_wh_per_kg"] / 1000.0 return { "gasoline_lhv_mj_per_l": round(lhv_l, 2), "gasoline_lhv_mj_per_kg": round(lhv_kg, 1), "gasoline_kwh_per_l": round(gas_kwh_per_l, 2), "gasoline_kwh_per_kg": round(gas_kwh_per_kg, 2), "battery_pack_kwh_per_kg": round(pack_kwh_per_kg, 3), "mass_density_ratio_gasoline_over_pack": round(gas_kwh_per_kg / pack_kwh_per_kg, 1), # 「円/kWh」を無造作に並べた場合の数字（記事で解体する対象） "gasoline_jpy_per_kwh_fuel": round(a["gasoline_retail_jpy_per_l"] / gas_kwh_per_l, 1), "battery_pack_jpy_per_kwh_capacity": round(a["battery_pack_usd_per_kwh"] * a["usd_jpy"], 0), } # ---------------------------------------------------------------- 車両の比較 def vehicles(a: dict[str, float], sm: dict[str, float]) -> dict[str, dict[str, float]]: """同じ軽規格・同じメーカーの 2 台（デイズ 2WD NA／サクラ）を WLTC 審査値で並べる。""" gas_kwh_per_l = sm["gasoline_kwh_per_l"] # デイズ d_l_per_km = 1.0 / a["dayz_fuel_economy_km_per_l"] d_energy_wh_per_km = d_l_per_km * gas_kwh_per_l * 1000.0 # 燃料の化学エネルギー（低位） d_range_km = a["dayz_tank_l"] * a["dayz_fuel_economy_km_per_l"] d_stored_kwh = a["dayz_tank_l"] * gas_kwh_per_l d_fuel_mass_kg = a["dayz_tank_l"] * a["gasoline_density_kg_per_l"] d_jpy_per_km = d_l_per_km * a["gasoline_retail_jpy_per_l"] d_jpy_per_km_no_subsidy = d_l_per_km * (a["gasoline_retail_jpy_per_l"] + a["gasoline_subsidy_jpy_per_l"]) # サクラ s_energy_wh_per_km = a["sakura_consumption_wh_per_km"] # 交流側（充電損失込み） s_jpy_per_km = s_energy_wh_per_km / 1000.0 * a["electricity_jpy_per_kwh"] s_pack_mass_est_kg = a["sakura_battery_kwh"] * 1000.0 / a["battery_pack_wh_per_kg"] # 推計（非公表） solar = a["solar_surplus_jpy_per_kwh"] def ev(prefix: str, battery_kwh: float, subsidy_key: str) -> dict[str, float]: wh_km = a[f"{prefix}_consumption_wh_per_km"] jpy_km = wh_km / 1000.0 * a["electricity_jpy_per_kwh"] return { "curb_mass_kg": a[f"{prefix}_curb_mass_kg"], "stored_energy_kwh": battery_kwh, "battery_pack_mass_estimate_kg": round(battery_kwh * 1000.0 / a["battery_pack_wh_per_kg"], 0), "range_km_wltc": a[f"{prefix}_range_km"], "energy_in_wh_per_km": round(wh_km, 0), "jpy_per_km": round(jpy_km, 2), "jpy_per_km_solar_surplus": round(wh_km / 1000.0 * solar, 2), "jpy_per_100km": round(jpy_km * 100, 0), "price_jpy": a[f"{prefix}_price_jpy"], "price_after_subsidy_jpy": a[f"{prefix}_price_jpy"] - a[subsidy_key], "subsidy_jpy": a[subsidy_key], "curb_mass_difference_vs_dayz_kg": a[f"{prefix}_curb_mass_kg"] - a["dayz_curb_mass_kg"], "range_dayz_over_this": round(d_range_km / a[f"{prefix}_range_km"], 2), "stored_energy_dayz_over_this": round(d_stored_kwh / battery_kwh, 1), "energy_in_per_km_dayz_over_this": round(d_energy_wh_per_km / wh_km, 2), "running_cost_dayz_over_this": round(d_jpy_per_km / jpy_km, 2), "running_cost_dayz_over_this_solar_surplus": round(d_jpy_per_km / (wh_km / 1000.0 * solar), 1), } return { "racco200": ev("racco200", a["racco200_battery_kwh"], "racco_subsidy_jpy"), "racco300": ev("racco300", a["racco300_battery_kwh"], "racco_subsidy_jpy"), "dayz": { "curb_mass_kg": a["dayz_curb_mass_kg"], "stored_energy_kwh_lhv": round(d_stored_kwh, 1), "fuel_mass_full_tank_kg": round(d_fuel_mass_kg, 1), "range_km_wltc": round(d_range_km, 0), "energy_in_wh_per_km": round(d_energy_wh_per_km, 0), "jpy_per_km": round(d_jpy_per_km, 2), "jpy_per_km_without_subsidy": round(d_jpy_per_km_no_subsidy, 2), "jpy_per_100km": round(d_jpy_per_km * 100, 0), "price_jpy": a["dayz_price_jpy"], }, "sakura": { "curb_mass_kg": a["sakura_curb_mass_kg"], "stored_energy_kwh": a["sakura_battery_kwh"], "battery_pack_mass_estimate_kg": round(s_pack_mass_est_kg, 0), "range_km_wltc": a["sakura_range_km"], "energy_in_wh_per_km": round(s_energy_wh_per_km, 0), "jpy_per_km": round(s_jpy_per_km, 2), "jpy_per_km_solar_surplus": round(s_energy_wh_per_km / 1000.0 * solar, 2), "jpy_per_100km": round(s_jpy_per_km * 100, 0), "price_jpy": a["sakura_price_jpy"], "price_after_subsidy_jpy": a["sakura_price_jpy"] - a["sakura_subsidy_jpy"], }, "ratios": { "stored_energy_dayz_over_sakura": round(d_stored_kwh / a["sakura_battery_kwh"], 1), "range_dayz_over_sakura": round(d_range_km / a["sakura_range_km"], 2), "curb_mass_sakura_over_dayz": round(a["sakura_curb_mass_kg"] / a["dayz_curb_mass_kg"], 2), "curb_mass_difference_kg": a["sakura_curb_mass_kg"] - a["dayz_curb_mass_kg"], "energy_in_per_km_dayz_over_sakura": round(d_energy_wh_per_km / s_energy_wh_per_km, 2), "running_cost_dayz_over_sakura": round(d_jpy_per_km / s_jpy_per_km, 2), "running_cost_dayz_over_sakura_solar_surplus": round(d_jpy_per_km / (s_energy_wh_per_km / 1000.0 * solar), 1), }, } # ---------------------------------------------------------------- 円/kWh の会計処理 def accounting(a: dict[str, float], sm: dict[str, float], v: dict[str, dict[str, float]]) -> dict[str, float]: """『電池の円/kWh』を設備費として寿命中の供給量で割り直す。""" pack_jpy = sm["battery_pack_jpy_per_kwh_capacity"] * a["sakura_battery_kwh"] km = a["sakura_battery_warranty_km"] kwh_delivered = km * a["sakura_consumption_wh_per_km"] / 1000.0 pack_jpy_per_kwh_delivered = pack_jpy / kwh_delivered pack_jpy_per_km = pack_jpy / km # 仕事（車輪）あたりに揃える概算: 単体の円/kWh を変換効率で割る gas_jpy_per_kwh_wheel = sm["gasoline_jpy_per_kwh_fuel"] / a["ice_ttw_efficiency"] ev_jpy_per_kwh_wheel = (a["electricity_jpy_per_kwh"] + pack_jpy_per_kwh_delivered) / a["bev_grid_to_wheel_efficiency"] solar = a["solar_surplus_jpy_per_kwh"] ev_solar_jpy_per_kwh_wheel = (solar + pack_jpy_per_kwh_delivered) / a["bev_grid_to_wheel_efficiency"] lfp_jpy_per_kwh_capacity = a["battery_pack_lfp_usd_per_kwh"] * a["usd_jpy"] racco = {} for key, bat_key, wh_key in (("racco200", "racco200_battery_kwh", "racco200_consumption_wh_per_km"), ("racco300", "racco300_battery_kwh", "racco300_consumption_wh_per_km")): r_km = a["racco_battery_warranty_km"] r_kwh_delivered = r_km * a[wh_key] / 1000.0 for label, unit_price in (("bev_avg", sm["battery_pack_jpy_per_kwh_capacity"]), ("lfp", lfp_jpy_per_kwh_capacity)): r_pack = unit_price * a[bat_key] racco[f"{key}_pack_cost_jpy_{label}"] = round(r_pack, 0) racco[f"{key}_pack_jpy_per_kwh_delivered_{label}"] = round(r_pack / r_kwh_delivered, 1) racco[f"{key}_pack_jpy_per_km_{label}"] = round(r_pack / r_km, 2) racco[f"{key}_electricity_plus_pack_jpy_per_kwh_at_wheel_{label}"] = round((a["electricity_jpy_per_kwh"] + r_pack / r_kwh_delivered) / a["bev_grid_to_wheel_efficiency"], 0) racco[f"{key}_kwh_delivered_over_warranty_km"] = round(r_kwh_delivered, 0) return { "lfp_pack_jpy_per_kwh_capacity": round(lfp_jpy_per_kwh_capacity, 0), "solar_surplus_jpy_per_kwh": solar, "solar_plus_pack_jpy_per_kwh_at_wheel_est": round(ev_solar_jpy_per_kwh_wheel, 0), "gasoline_over_solar_plus_pack_at_wheel": round(gas_jpy_per_kwh_wheel / ev_solar_jpy_per_kwh_wheel, 1), "sakura_pack_plus_solar_jpy_per_km": round(pack_jpy_per_km + a["sakura_consumption_wh_per_km"] / 1000.0 * solar, 2), "sakura_pack_plus_grid_jpy_per_km": round(pack_jpy_per_km + a["sakura_consumption_wh_per_km"] / 1000.0 * a["electricity_jpy_per_kwh"], 2), **racco, "battery_pack_cost_jpy_20kwh": round(pack_jpy, 0), "kwh_delivered_over_warranty_km": round(kwh_delivered, 0), "battery_pack_jpy_per_kwh_delivered": round(pack_jpy_per_kwh_delivered, 1), "battery_pack_jpy_per_km": round(pack_jpy_per_km, 2), "gasoline_jpy_per_kwh_fuel": sm["gasoline_jpy_per_kwh_fuel"], "gasoline_jpy_per_kwh_at_wheel_est": round(gas_jpy_per_kwh_wheel, 0), "electricity_plus_pack_jpy_per_kwh_at_wheel_est": round(ev_jpy_per_kwh_wheel, 0), "naive_ratio_pack_over_gasoline_jpy_per_kwh": round( sm["battery_pack_jpy_per_kwh_capacity"] / sm["gasoline_jpy_per_kwh_fuel"], 0 ), } # ---------------------------------------------------------------- 保有総費用（距離×年数の感度） def tco_grid(a: dict[str, float], v: dict[str, dict[str, float]]) -> list[dict[str, float]]: rows = [] for years in (5, 8, 13): for km_per_year in (5000, 10000, 20000): km = years * km_per_year d = v["dayz"]["price_jpy"] + v["dayz"]["jpy_per_km"] * km s = v["sakura"]["price_after_subsidy_jpy"] + v["sakura"]["jpy_per_km"] * km s_nosub = v["sakura"]["price_jpy"] + v["sakura"]["jpy_per_km"] * km rows.append( { "years": years, "km_per_year": km_per_year, "total_km": km, "dayz_vehicle_plus_fuel_jpy": round(d, 0), "sakura_vehicle_after_subsidy_plus_electricity_jpy": round(s, 0), "sakura_vehicle_no_subsidy_plus_electricity_jpy": round(s_nosub, 0), "difference_sakura_minus_dayz_jpy": round(s - d, 0), "difference_no_subsidy_jpy": round(s_nosub - d, 0), } ) return rows def breakeven_km(v: dict[str, dict[str, float]]) -> dict[str, float]: def _be(car: str, solar: bool = False) -> dict[str, float]: dp = v[car]["price_after_subsidy_jpy"] - v["dayz"]["price_jpy"] dp_nosub = v[car]["price_jpy"] - v["dayz"]["price_jpy"] ev_cost = v[car]["jpy_per_km_solar_surplus"] if solar else v[car]["jpy_per_km"] dr = v["dayz"]["jpy_per_km"] - ev_cost return { "price_gap_after_subsidy_jpy": dp, "price_gap_no_subsidy_jpy": dp_nosub, "running_cost_gap_jpy_per_km": round(dr, 2), "breakeven_km_after_subsidy": round(dp / dr, 0) if dr > 0 else float("inf"), "breakeven_km_no_subsidy": round(dp_nosub / dr, 0) if dr > 0 else float("inf"), } out = _be("sakura") out["sakura_solar_surplus"] = _be("sakura", solar=True) out["racco200"] = _be("racco200") out["racco200_solar_surplus"] = _be("racco200", solar=True) out["racco300"] = _be("racco300") out["racco300_solar_surplus"] = _be("racco300", solar=True) return out # ---------------------------------------------------------------- ガソリン価格のシナリオ def gasoline_price_scenarios(a: dict[str, float], v: dict[str, dict[str, float]]) -> list[dict[str, float]]: """ガソリン価格だけを動かしたとき、円/km・倍率・価格差が並ぶ距離がどう動くか。EV 側は固定。""" rows = [] l_per_km = 1.0 / a["dayz_fuel_economy_km_per_l"] gas_kwh_per_l = storage_medium(a)["gasoline_kwh_per_l"] for label, price in ( ("2026-10 全国平均（補助金込み）", a["gasoline_retail_jpy_per_l"]), ("補助金なし（170.2＋42.8）", a["gasoline_retail_jpy_per_l"] + a["gasoline_subsidy_jpy_per_l"]), ("仮に 220 円", 220.0), ("仮に 250 円", 250.0), ): d_km = l_per_km * price row = {"scenario": label, "gasoline_jpy_per_l": price, "dayz_jpy_per_km": round(d_km, 2), "gasoline_jpy_per_kwh_fuel": round(price / gas_kwh_per_l, 1), "gasoline_jpy_per_kwh_at_wheel_est": round(price / gas_kwh_per_l / a["ice_ttw_efficiency"], 0)} for car in ("sakura", "racco200", "racco300"): grid = v[car]["jpy_per_km"] solar = v[car]["jpy_per_km_solar_surplus"] row[f"{car}_ratio_grid"] = round(d_km / grid, 2) row[f"{car}_ratio_solar_surplus"] = round(d_km / solar, 1) gap = v[car]["price_after_subsidy_jpy"] - v["dayz"]["price_jpy"] gap_nosub = v[car]["price_jpy"] - v["dayz"]["price_jpy"] row[f"{car}_breakeven_km_after_subsidy"] = round(gap / (d_km - grid), 0) row[f"{car}_breakeven_km_no_subsidy"] = round(gap_nosub / (d_km - grid), 0) row[f"{car}_breakeven_km_solar_surplus"] = round(gap / (d_km - solar), 0) rows.append(row) return rows # ---------------------------------------------------------------- 感度（一変数） def sensitivity(base: dict[str, float]) -> list[dict[str, float]]: rows = [] keys = [ "gasoline_retail_jpy_per_l", "electricity_jpy_per_kwh", "dayz_fuel_economy_km_per_l", "sakura_consumption_wh_per_km", "battery_pack_usd_per_kwh", "usd_jpy", "ice_ttw_efficiency", "bev_grid_to_wheel_efficiency", ] low, high = load("low"), load("high") for k in keys: for case, src in (("low", low), ("high", high)): a = dict(base) a[k] = src[k] sm = storage_medium(a) v = vehicles(a, sm) acc = accounting(a, sm, v) rows.append( { "key": k, "case": case, "value": src[k], "dayz_jpy_per_km": v["dayz"]["jpy_per_km"], "sakura_jpy_per_km": v["sakura"]["jpy_per_km"], "running_cost_ratio": v["ratios"]["running_cost_dayz_over_sakura"], "gasoline_jpy_per_kwh_fuel": sm["gasoline_jpy_per_kwh_fuel"], "battery_pack_jpy_per_kwh_delivered": acc["battery_pack_jpy_per_kwh_delivered"], } ) return rows # ---------------------------------------------------------------- 図 def make_figures(sm, v, acc) -> list[str]: try: import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt from matplotlib import font_manager except Exception: # pragma: no cover return [] for cand in ("Hiragino Sans", "Hiragino Kaku Gothic ProN", "Noto Sans CJK JP", "IPAexGothic"): if any(cand in f.name for f in font_manager.fontManager.ttflist): plt.rcParams["font.family"] = cand break plt.rcParams["axes.unicode_minus"] = False FIG.mkdir(parents=True, exist_ok=True) written = [] # 図1: 単体 → 車両 で倍率がどう変わるか labels = [ "質量あたり\n貯蔵エネルギー\n(燃料 vs パック)", "車載の貯蔵エネルギー\n(27 L vs 20 kWh)", "一充電/満タン\n航続 (WLTC)", "1 km あたり\n投入エネルギー", "1 km あたり\n走行費", ] vals = [ sm["mass_density_ratio_gasoline_over_pack"], v["ratios"]["stored_energy_dayz_over_sakura"], v["ratios"]["range_dayz_over_sakura"], v["ratios"]["energy_in_per_km_dayz_over_sakura"], v["ratios"]["running_cost_dayz_over_sakura"], ] fig, ax = plt.subplots(figsize=(9.2, 5.2), dpi=150) bars = ax.bar(labels, vals, color=["#8a8f98", "#8a8f98", "#2f7a4d", "#2f7a4d", "#c98a2b"]) ax.set_yscale("log") ax.set_ylim(0.7, max(vals) * 2.2) ax.set_ylabel("ガソリン側 ÷ 電池側（倍、対数軸）") ax.axhline(1.0, color="#333", lw=0.8, ls="--") for b, val in zip(bars, vals): ax.text(b.get_x() + b.get_width() / 2, val * 1.08, f"{val:g}倍", ha="center", va="bottom", fontsize=10) ax.set_title("図1　「単体」から「車両」へ境界を広げると、倍率はどう変わるか（デイズ 2WD NA／サクラ、WLTC 審査値）", fontsize=10.5) ax.text( 0.0, -0.30, "左 2 本は燃料・電池そのものの数字（ガソリンが大きい＝正しい）。右 3 本は同じ軽規格の実車で測った数字。\n" "1 km あたり投入エネルギーはガソリン車が約 3 倍多く、走行費はガソリン車が約 1.9 倍（170.2 円/L・31 円/kWh）。", transform=ax.transAxes, fontsize=8.5, va="top", ) fig.tight_layout() p = FIG / "fig01_boundary_ratios.png" fig.savefig(p, bbox_inches="tight") plt.close(fig) written.append(p.name) # 図2: 同じ「円/kWh」でも中身が違う fig, ax = plt.subplots(figsize=(9.2, 4.6), dpi=150) cats = ["ガソリン\n（消費費・燃料 1 kWh）", "電池パック\n（設備費・容量 1 kWh）", "電池パック\n（設備費 ÷ 保証走行で供給する kWh）", "電気\n（消費費・1 kWh）"] y = [ sm["gasoline_jpy_per_kwh_fuel"], sm["battery_pack_jpy_per_kwh_capacity"], acc["battery_pack_jpy_per_kwh_delivered"], load()["electricity_jpy_per_kwh"], ] cols = ["#c98a2b", "#8a8f98", "#2f7a4d", "#2f7a4d"] bars = ax.bar(cats, y, color=cols) ax.set_yscale("log") ax.set_ylim(5, max(y) * 2.5) ax.set_ylabel("円/kWh（対数軸）") for b, val in zip(bars, y): ax.text(b.get_x() + b.get_width() / 2, val * 1.1, f"{val:,.0f} 円", ha="center", va="bottom", fontsize=10) ax.set_title("図2　同じ「円/kWh」でも、消費費と設備費は別の勘定（2026-10 時点の値）", fontsize=10.5) ax.text( 0.0, -0.22, "電池の 1 kWh は「容量」の取得費で、保証期間（8 年 16 万 km）に繰り返し充放電して供給する。供給 1 kWh あたりに直すと十数円。\n" "ガソリンの 1 kWh は燃やせば消える。並べてよいのは右 2 本の和（電気＋設備の供給あたり費用）と左端であり、しかも効率補正が要る。", transform=ax.transAxes, fontsize=8.5, va="top", ) fig.tight_layout() p = FIG / "fig02_jpy_per_kwh_accounting.png" fig.savefig(p, bbox_inches="tight") plt.close(fig) written.append(p.name) # 図3: 保有総費用（車両＋エネルギー）の距離依存 fig, ax = plt.subplots(figsize=(9.2, 5.0), dpi=150) kms = list(range(0, 160001, 5000)) d = [v["dayz"]["price_jpy"] + v["dayz"]["jpy_per_km"] * k for k in kms] s = [v["sakura"]["price_after_subsidy_jpy"] + v["sakura"]["jpy_per_km"] * k for k in kms] s2 = [v["sakura"]["price_jpy"] + v["sakura"]["jpy_per_km"] * k for k in kms] ax.plot(kms, [x / 1e4 for x in d], color="#c98a2b", lw=2.2, label="デイズ X 2WD：車両価格＋ガソリン代") ax.plot(kms, [x / 1e4 for x in s], color="#2f7a4d", lw=2.2, label="サクラ S：車両価格（補助金 58 万円後）＋電気代") ax.plot(kms, [x / 1e4 for x in s2], color="#2f7a4d", lw=1.4, ls="--", label="サクラ S：補助金なし＋電気代") be = breakeven_km(v) if be["breakeven_km_after_subsidy"] != float("inf") and be["breakeven_km_after_subsidy"] < 160000: ax.axvline(be["breakeven_km_after_subsidy"], color="#555", lw=0.8, ls=":") ax.text(be["breakeven_km_after_subsidy"], ax.get_ylim()[1] * 0.98, f"分岐 {be['breakeven_km_after_subsidy']:,.0f} km", rotation=90, va="top", ha="right", fontsize=8.5) ax.set_xlabel("累計走行距離（km）") ax.set_ylabel("車両価格＋エネルギー費の累計（万円）") ax.set_title("図3　「車両＋エネルギー費」の累計（税・保険・整備・残価は含まない。前提は assumptions.csv）", fontsize=10.5) ax.grid(alpha=0.3) ax.legend(fontsize=8.5, loc="upper left") fig.tight_layout() p = FIG / "fig03_vehicle_plus_energy_cumulative.png" fig.savefig(p, bbox_inches="tight") plt.close(fig) written.append(p.name) # 図4: 1 km あたりのエネルギー費。系統電力で充電した場合と、卒FIT の余剰太陽光（売れば 8 円/kWh）で充電した場合 a = load() fig, ax = plt.subplots(figsize=(9.2, 4.8), dpi=150) names = ["デイズ X 2WD\n170.2 円/L", "デイズ\n補助金なし\n213 円/L", "サクラ S\n系統\n31 円/kWh", "RACCO 200\n系統\n31 円/kWh", "RACCO 300Plus\n系統\n31 円/kWh", "サクラ S\n余剰太陽光\n8 円/kWh", "RACCO 200\n余剰太陽光\n8 円/kWh"] yv = [ v["dayz"]["jpy_per_km"], v["dayz"]["jpy_per_km_without_subsidy"], v["sakura"]["jpy_per_km"], v["racco200"]["jpy_per_km"], v["racco300"]["jpy_per_km"], v["sakura"]["jpy_per_km_solar_surplus"], v["racco200"]["jpy_per_km_solar_surplus"], ] colors = ["#c98a2b", "#e0b36a", "#2f7a4d", "#2f7a4d", "#2f7a4d", "#7fb77e", "#7fb77e"] bars = ax.bar(names, yv, color=colors) for b, val in zip(bars, yv): ax.text(b.get_x() + b.get_width() / 2, val + 0.12, f"{val:.2f} 円", ha="center", va="bottom", fontsize=9.5) ax.set_ylabel("1 km あたりの燃料・電気代（円）") ax.set_ylim(0, max(yv) * 1.25) ax.tick_params(axis="x", labelsize=8.5) ax.set_title("図4　1 km あたりのエネルギー費。充電する電気の値段で、EV 側の数字は 3.8 円から 1 円まで動く", fontsize=10.5) ax.text( 0.0, -0.34, f"余剰太陽光の 8 円/kWh は、FIT 買取期間を終えた住宅用太陽光の余剰を売電した場合の単価（大手 10 社の基本買取 7〜9 円）。\n" "自家消費で車に充電すると、その電気の機会費用は売電単価になる。昼間に車が自宅にあること、または蓄電池を介することが前提。", transform=ax.transAxes, fontsize=8.5, va="top", ) fig.tight_layout() p = FIG / "fig04_jpy_per_km_by_charging_source.png" fig.savefig(p, bbox_inches="tight") plt.close(fig) written.append(p.name) return written # ---------------------------------------------------------------- main def write_csv(path: Path, rows: list[dict]) -> None: if not rows: return with path.open("w", encoding="utf-8", newline="") as f: w = csv.DictWriter(f, fieldnames=list(rows[0].keys())) w.writeheader() w.writerows(rows) def main() -> None: ap = argparse.ArgumentParser() ap.add_argument("--no-fig", action="store_true") args = ap.parse_args() a = load("base") sm = storage_medium(a) v = vehicles(a, sm) acc = accounting(a, sm, v) be = breakeven_km(v) tco = tco_grid(a, v) sens = sensitivity(a) gas = gasoline_price_scenarios(a, v) RESULTS.mkdir(parents=True, exist_ok=True) write_csv(RESULTS / "storage_medium.csv", [{"metric": k, "value": val} for k, val in sm.items()]) rows = [] for car in ("dayz", "sakura", "racco200", "racco300"): for k, val in v[car].items(): rows.append({"vehicle": car, "metric": k, "value": val}) for k, val in v["ratios"].items(): rows.append({"vehicle": "ratio", "metric": k, "value": val}) write_csv(RESULTS / "vehicle_comparison.csv", rows) write_csv(RESULTS / "accounting_jpy_per_kwh.csv", [{"metric": k, "value": val} for k, val in acc.items()]) write_csv(RESULTS / "tco_grid.csv", tco) write_csv(RESULTS / "sensitivity.csv", sens) write_csv(RESULTS / "gasoline_price_scenarios.csv", gas) figs = [] if args.no_fig else make_figures(sm, v, acc) summary = { "generated_from": "data/assumptions.csv (BASE)", "storage_medium": sm, "vehicles": v, "accounting": acc, "breakeven": be, "gasoline_price_scenarios": gas, "figures": figs, } (RESULTS / "summary.json").write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(summary, ensure_ascii=False, indent=2)) if __name__ == "__main__": main()