# -*- coding: utf-8 -*- """ fig_dgcup2022a.py —— 电工杯 2022 A 题范文配图（24 张 SVG） ================================================ 复用 gen_dgcup2022a 的确定性真源，生成三篇范文各 8 张图，共 24 张， 写入 assets/problems/dgcup2022a/figs/，命名 dgcup2022a-{paper}-fig{n}.svg。 用法：cd tools/ && python3 fig_dgcup2022a.py """ import os import gen_dgcup2022a as G from _svg import (_fig, _save, _bar, _grouped_bar, _line, _scatter, _pie, _heatmap, _stack, _network, _flow, _txt, C_ACC, C_RED, C_GREEN, C_AMB, C_PUR, C_CYAN, C_TEAL, C_PINK, C_GRID, C_MUT, PALETTE) HERE = os.path.dirname(os.path.abspath(__file__)) OUT = os.path.normpath(os.path.join(HERE, "..", "assets", "problems", "dgcup2022a", "figs")) os.makedirs(OUT, exist_ok=True) D = G.gen_dgcup2022a() load_arr = D["load_arr"] load_norm = D["load_norm"] wind_norm = D["wind_norm"] DT = G.DT hours = [k * DT for k in range(96)] CARBON = G.CARBON_PRICES def step_series(units_idx, la, wa): res = {i: [] for i in units_idx} wu, cu, lo = [], [], [] for load, w in zip(la, wa): Ps, w_used, curt, loss = G.dispatch_no_storage(units_idx, load, w) for i in units_idx: res[i].append(Ps[i]) wu.append(w_used) cu.append(curt) lo.append(loss) return res, wu, cu, lo # ===================== 范文一：基础建模与无储能分析 ===================== def p1_f1(): s = [("负荷(标幺)", C_ACC, [(hours[k], load_norm[k]) for k in range(96)]), ("风电(标幺)", C_GREEN, [(hours[k], wind_norm[k]) for k in range(96)])] return _line("图1 典型日负荷与风电归一化出力曲线", s, xlabel="时刻 h", ylabel="标幺值") def p1_f2(): q = D["q1_plan"] s = [("机组1", C_ACC, [(hours[k], q[1][k]) for k in range(96)]), ("机组2", C_RED, [(hours[k], q[2][k]) for k in range(96)]), ("机组3", C_GREEN, [(hours[k], q[3][k]) for k in range(96)])] return _line("图2 问题一无风电时三机组日发电计划 MW", s, xlabel="时刻 h", ylabel="出力 MW") def p1_f3(): q = D["q1"][60] return _pie("图3 问题一发电成本构成(碳价60元/t)", ["火电煤耗", "运行维护", "碳捕集"], [q["coal"], q["om"], q["carbon"]]) def p1_f4(): res, wu, cu, lo = step_series([1, 2], load_arr, [v * 300 for v in wind_norm]) layers = [("机组1", C_ACC, res[1]), ("机组2", C_RED, res[2]), ("风电消纳", C_GREEN, wu), ("弃风", C_AMB, cu)] return _stack("图4 问题二功率平衡(风电300MW替代机组3)", hours, layers, ymax=1000) def p1_f5(): _, _, cu, _ = step_series([1, 2], load_arr, [v * 300 for v in wind_norm]) s = [("弃风功率 MW", C_AMB, [(hours[k], cu[k]) for k in range(96)])] return _line("图5 问题二逐时弃风功率 MW", s, xlabel="时刻 h", ylabel="弃风 MW") def p1_f6(): res, wu, cu, lo = step_series([1, 3], load_arr, [v * 600 for v in wind_norm]) layers = [("机组1", C_ACC, res[1]), ("机组3", C_GREEN, res[3]), ("风电消纳", C_TEAL, wu), ("弃风", C_AMB, cu), ("失负荷", C_RED, lo)] return _stack("图6 问题三功率平衡(风电600MW替代机组2)", hours, layers, ymax=1000) def p1_f7(): q2, q3 = D["q2"], D["q3"] groups = ["问题二(300MW)", "问题三(600MW)"] cats = ["弃风电量", "失负荷电量"] vals = [[q2["curt_kwh"], q2["loss_kwh"]], [q3["curt_kwh"], q3["loss_kwh"]]] return _grouped_bar("图7 问题二/三 弃风与失负荷电量对比 kWh", groups, cats, vals, fmt="%.0f") def p1_f8(): vals = [D["q1"][0]["unit_supply"], D["q2"]["unit_supply"], D["q3"]["unit_supply"]] return _bar("图8 问题一/二/三 单位供电成本(碳价0) 元/kWh", ["问题一(无风)", "问题二(300MW)", "问题三(600MW)"], vals, colors=[C_ACC, C_GREEN, C_TEAL], fmt="%.4f") # ===================== 范文二：碳捕集、储能配置与单位成本 ===================== def p2_f1(): q4 = D["q4"] groups = ["问题二场景", "问题三场景"] cats = ["0", "60", "80", "100"] vals = [[q4["Q2"][c] for c in CARBON], [q4["Q3"][c] for c in CARBON]] return _grouped_bar("图1 四档碳价下单位供电成本 元/kWh", groups, cats, vals, fmt="%.4f") def p2_f2(): w2 = [v * 300 for v in wind_norm] vals = [] for cp in CARBON: tot, _, _, _, _ = G.scenario_cost([1, 2], load_arr, w2, cp) vals.append(tot["carbon"]) return _bar("图2 问题二碳捕集成本随碳价变化 元", [str(c) for c in CARBON], vals, colors=[C_PUR] * 4, fmt="%.0f") def p2_f3(): _, _, _, lo = step_series([1], load_arr, [v * 900 for v in wind_norm]) s = [("失负荷功率 MW", C_RED, [(hours[k], lo[k]) for k in range(96)])] return _line("图3 问题五无储能时逐时失负荷 MW", s, xlabel="时刻 h", ylabel="失负荷 MW") def p2_f4(): q5 = D["q5"] s = [("可充电功率 MW", C_GREEN, [(hours[k], q5["S"][k]) for k in range(96)]), ("需放电功率 MW", C_RED, [(hours[k], q5["D"][k]) for k in range(96)])] return _line("图4 问题五储能充放电功率计划 MW", s, xlabel="时刻 h", ylabel="功率 MW") def p2_f5(): q5 = D["q5"] return _bar("图5 问题五最小储能配置", ["储能容量(MWh)", "储能功率(MW)"], [q5["sto_capacity"], q5["sto_power"]], colors=[C_ACC, C_PUR], fmt="%.1f") def p2_f6(): vals = [D["q5"]["unit_supply_no_sto"], D["q5"]["unit_supply"]] return _bar("图6 问题五含储能前后单位供电成本 元/kWh", ["无储能(碳价60)", "含储能(碳价60)"], vals, colors=[C_RED, C_GREEN], fmt="%.4f") def p2_f7(): q4 = D["q4"] s = [("问题二场景", C_GREEN, [(c, q4["Q2"][c]) for c in CARBON]), ("问题三场景", C_RED, [(c, q4["Q3"][c]) for c in CARBON])] return _line("图7 单位供电成本随碳价变化 元/kWh", s, xlabel="碳价 元/t", ylabel="元/kWh") def p2_f8(): w5 = [v * 900 for v in wind_norm] tot, _, _, _, _ = G.scenario_cost([1], load_arr, w5, 60) stor = D["q5"]["sto_daily"] labels = ["火电煤耗", "运行维护", "碳捕集", "风电运维", "弃风损失", "储能成本"] vals = [tot["coal"], tot["om"], tot["carbon"], tot["wind"], tot["curt"], stor] return _bar("图8 问题五含储能成本构成 元/天", labels, vals, colors=[C_ACC, C_CYAN, C_PUR, C_GREEN, C_AMB, C_PINK], fmt="%.0f") # ===================== 范文三：灵敏度、Q6/Q7 与方案设计 ===================== def p3_f1(): ser = D["q6"]["series"] s = [("单位供电成本", C_ACC, [(r["inst"], r["unit_supply"]) for r in ser])] return _line("图1 单位供电成本随风电装机变化 元/kWh", s, xlabel="风电装机 MW", ylabel="元/kWh") def p3_f2(): ser = D["q6"]["series"] s = [("弃风电量 kWh", C_AMB, [(r["pen"], r["curt_kwh"]) for r in ser]), ("失负荷电量 kWh", C_RED, [(r["pen"], r["loss_kwh"]) for r in ser])] return _line("图2 弃风与失负荷随渗透率变化", s, xlabel="风电渗透率", ylabel="电量 kWh") def p3_f3(): q5 = D["q5"] mults = [0.5, 1.0, 2.0, 3.0] tp = sum(q5["S"]) * DT * 1000 + sum(q5["D"]) * DT * 1000 base = q5["total_with_sto"] - q5["sto_daily"] us = [] for m in mults: inv = (G.STO_PC * m) * q5["sto_power"] * 1000 + (G.STO_EC * m) * q5["sto_capacity"] * 1000 dinv = inv / (G.STO_LIFE * 365) dom = tp * G.STO_OM us.append((base + dinv + dom) / D["load_kwh_day"]) s = [("单位供电成本", C_ACC, [(m, us[i]) for i, m in enumerate(mults)])] return _line("图3 单位供电成本对储能成本的敏感性", s, xlabel="储能成本倍数", ylabel="元/kWh") def p3_f4(): rows = [0, # placeholder replaced below ] insts = [0, 300, 600, 900, 1200] M = [] for inst in insts: if inst == 0: uidx = [1, 2, 3] elif inst <= 300: uidx = [1, 2] elif inst <= 600: uidx = [1, 3] else: uidx = [1] wa = [v * inst for v in wind_norm] row = [] for cp in CARBON: tot, _, _, _, _ = G.scenario_cost(uidx, load_arr, wa, cp) row.append(tot["unit_supply"]) M.append(row) return _heatmap("图4 风电装机×碳价 单位供电成本热力图 元/kWh", [str(i) for i in insts], [str(c) for c in CARBON], M, fmt="%.3f") def p3_f5(): load15 = D["q7"]["load_arr"] wind15 = D["q7"]["wind_arr"] idx = list(range(0, 1440, 4)) s = [("负荷 MW", C_ACC, [(k * DT, load15[k]) for k in idx]), ("风电 MW", C_GREEN, [(k * DT, wind15[k]) for k in idx])] return _line("图5 问题七十五日负荷与风电 MW", s, xlabel="时刻 h", ylabel="功率 MW") def p3_f6(): load15 = D["q7"]["load_arr"] wind15 = D["q7"]["wind_arr"] end = 72 net = [load15[k] - wind15[k] for k in range(end)] s = [("负荷", C_ACC, [(k * DT, load15[k]) for k in range(end)]), ("风电", C_GREEN, [(k * DT, wind15[k]) for k in range(end)]), ("净负荷(负荷-风电)", C_RED, [(k * DT, net[k]) for k in range(end)])] return _line("图6 问题七前3日净负荷(替代机组2、3) MW", s, xlabel="时刻 h", ylabel="功率 MW") def p3_f7(): load15 = D["q7"]["load_arr"] wind15 = D["q7"]["wind_arr"] _, _, _, lo = step_series([1], load15, wind15) idx = list(range(0, 1440, 4)) s = [("失负荷 MW", C_RED, [(k * DT, lo[k]) for k in idx])] return _line("图7 问题七逐时失负荷(十五日) MW", s, xlabel="时刻 h", ylabel="失负荷 MW") def p3_f8(): load15 = D["q7"]["load_arr"] wind15 = D["q7"]["wind_arr"] def us_scenario(uidx, with_sto): tot, _, _, _, _ = G.scenario_cost(uidx, load15, wind15, 60) cost = tot["total"] if with_sto: st = G.storage_size(uidx, load15, wind15) tp = sum(st["S"]) * DT * 1000 + sum(st["D"]) * DT * 1000 sc = G.storage_daily_cost(st["power_MW"], st["capacity_MWh"], tp) cost = cost - tot["loss"] + sc["daily_total"] # 储能消除失负荷 lk = sum(load15) * DT * 1000 return cost / lk vals = [us_scenario([1], False), us_scenario([1], True), us_scenario([1, 2], True), us_scenario([1, 2, 3], True)] return _bar("图8 问题七不同方案单位供电成本 元/kWh", ["无措施", "仅储能", "储能+恢复机组2", "储能+恢复机组2,3"], vals, colors=[C_RED, C_GREEN, C_CYAN, C_ACC], fmt="%.4f") # ===================== 任务表 ===================== JOBS = [p1_f1, p1_f2, p1_f3, p1_f4, p1_f5, p1_f6, p1_f7, p1_f8, p2_f1, p2_f2, p2_f3, p2_f4, p2_f5, p2_f6, p2_f7, p2_f8, p3_f1, p3_f2, p3_f3, p3_f4, p3_f5, p3_f6, p3_f7, p3_f8] def save(name, svg): _save(os.path.join(OUT, name), svg) def main(): n_bad = 0 for i, job in enumerate(JOBS): paper = (i // 8) + 1 fig = (i % 8) + 1 name = "dgcup2022a-%d-fig%d.svg" % (paper, fig) try: svg = job() if svg and "