Plot summary; take account of snapshot weightings correctly
This commit is contained in:
Tom Brown
Jonas Hörsch
parent
f3a12e7aee
commit
540985164f
128
config.yaml
128
config.yaml
@ -180,6 +180,13 @@ plotting:
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linewidth_factor: 3.e+3 # 1.e+3 #3.e+3
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costs_max: 800
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costs_threshold: 1
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energy_max: 15000.
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energy_min: -10000.
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energy_threshold: 50.
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vre_techs: ["onwind", "offwind", "solar", "ror"]
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conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
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@ -193,60 +200,73 @@ plotting:
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"central CHP electric", "central gas boiler"]
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heat_generators: ["gas boiler", "central gas boiler", "solar thermal collector", "central solar thermal collector"]
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tech_colors:
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onwind: "xkcd:azure"
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offwind: "blue"
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hydro: "g"
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ror: "lightgreen"
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PHS: "g"
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hydro+PHS: "g"
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solar: "yellow"
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OCGT: "brown"
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OCGT marginal: "sandybrown"
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OCGT-heat: "orange"
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central gas boiler: "orange"
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gas boiler: "orange"
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gas boilers: "orange"
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gas boiler marginal: "orange"
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gas: "brown"
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lines: "k"
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AC line: "k"
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AC-AC: "k"
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transmission lines: "k"
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H2: "m"
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hydrogen storage: "m"
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battery: "slategray"
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battery storage: "slategray"
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CAES: "lightgray"
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nuclear: "r"
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nuclear marginal: "r"
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coal: "k"
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coal marginal: "k"
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lignite: "grey"
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lignite marginal: "grey"
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CCGT: "orange"
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CCGT marginal: "orange"
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diesel: "darkred"
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diesel marginal: "darkred"
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heat pumps: "green"
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heat pump: "green"
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central heat pump: "green"
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resistive heater: "pink"
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central resistive heater: "pink"
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Sabatier: "turquoise"
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water tanks: "w"
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CHP: "r"
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CHP heat: "r"
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CHP electric: "r"
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central CHP heat: "r"
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central CHP electric: "r"
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Pumped storage: "g"
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Ambient: "k"
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AC load: "b"
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Heat load: "r"
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Li ion load: "grey"
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heat: "r"
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Li ion: "grey"
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district heating: "#CC4E5C"
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"onwind" : "b"
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"onshore wind" : "b"
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'offwind' : "c"
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'offshore wind' : "c"
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"hydro" : "#3B5323"
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"hydro reservoir" : "#3B5323"
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"ror" : "#78AB46"
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"run of river" : "#78AB46"
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'hydroelectricity' : '#006400'
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'solar' : "y"
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'solar PV' : "y"
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'solar thermal' : 'coral'
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"OCGT" : "wheat"
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"OCGT marginal" : "sandybrown"
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"OCGT-heat" : "orange"
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"gas boiler" : "orange"
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"gas boilers" : "orange"
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"gas boiler marginal" : "orange"
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"gas" : "brown"
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"natural gas" : "brown"
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"lines" : "k"
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"transmission lines" : "k"
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"H2" : "m"
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"hydrogen storage" : "m"
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"battery" : "slategray"
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"battery storage" : "slategray"
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"Nuclear" : "r"
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"Nuclear marginal" : "r"
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"Coal" : "k"
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"Coal marginal" : "k"
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"Lignite" : "grey"
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"Lignite marginal" : "grey"
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"CCGT" : "orange"
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"CCGT marginal" : "orange"
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"heat pumps" : "#76EE00"
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"heat pump" : "#76EE00"
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"air heat pump" : "#76EE00"
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"ground heat pump" : "#40AA00"
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"resistive heater" : "pink"
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"Sabatier" : "#FF1493"
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"methanation" : "#FF1493"
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"helmeth" : "#7D0552"
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"helmeth" : "#7D0552"
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"DAC" : "#E74C3C"
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"nuclear" : "#303030"
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"water tanks" : "#BBBBBB"
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"hot water storage" : "#BBBBBB"
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"hot water charging" : "#BBBBBB"
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"hot water discharging" : "#999999"
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"CHP" : "r"
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"CHP heat" : "r"
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"CHP electric" : "r"
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"PHS" : "g"
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"Ambient" : "k"
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"Electric load" : "b"
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"Heat load" : "r"
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"Transport load" : "grey"
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"heat" : "r"
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"Li ion" : "grey"
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"district heating" : "#CC4E5C"
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"retrofitting" : "purple"
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"building retrofitting" : "purple"
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"BEV charger" : "grey"
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"V2G" : "grey"
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"transport" : "grey"
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"electricity" : "k"
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"transport fuel cell" : "#AAAAAA"
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nice_names:
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# OCGT: "Gas"
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# OCGT marginal: "Gas (marginal)"
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@ -50,15 +50,15 @@ def calculate_costs(n,label,costs):
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costs.loc[idx[c.list_name,"capital",list(capital_costs_grouped.index)],label] = capital_costs_grouped.values
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if c.name == "Link":
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p = c.pnl.p0.sum()
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p = c.pnl.p0.multiply(n.snapshot_weightings,axis=0).sum()
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elif c.name == "Line":
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continue
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elif c.name == "StorageUnit":
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p_all = c.pnl.p.copy()
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p_all = c.pnl.p.multiply(n.snapshot_weightings,axis=0)
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p_all[p_all < 0.] = 0.
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p = p_all.sum()
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else:
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p = c.pnl.p.sum()
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p = c.pnl.p.multiply(n.snapshot_weightings,axis=0).sum()
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marginal_costs = p*c.df.marginal_cost
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@ -97,9 +97,9 @@ def calculate_energy(n,label,energy):
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for c in n.iterate_components(n.one_port_components|n.branch_components):
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if c.name in n.one_port_components:
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c_energies = c.pnl.p.sum().multiply(c.df.sign).groupby(c.df.carrier).sum()
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c_energies = c.pnl.p.multiply(n.snapshot_weightings,axis=0).sum().multiply(c.df.sign).groupby(c.df.carrier).sum()
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else:
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c_energies = (-c.pnl.p1.sum() - c.pnl.p0.sum()).groupby(c.df.carrier).sum()
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c_energies = (-c.pnl.p1.multiply(n.snapshot_weightings,axis=0).sum() - c.pnl.p0.multiply(n.snapshot_weightings,axis=0).sum()).groupby(c.df.carrier).sum()
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energy = energy.reindex(energy.index|pd.MultiIndex.from_product([[c.list_name],c_energies.index]))
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185
scripts/plot_summary.py
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185
scripts/plot_summary.py
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@ -0,0 +1,185 @@
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import pandas as pd
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#allow plotting without Xwindows
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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#consolidate and rename
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def rename_techs(label):
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if label[:8] == "central ":
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label = label[8:]
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if label[:6] == "urban ":
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label = label[6:]
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if "retrofitting" in label:
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label = "building retrofitting"
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if "H2" in label:
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label = "hydrogen storage"
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if "CHP" in label:
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label = "CHP"
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if "water tank" in label:
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label = "water tanks"
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if label=="water tanks":
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label = "hot water storage"
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if "gas" in label and label != "gas boiler":
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label = "natural gas"
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if "solar thermal" in label:
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label = "solar thermal"
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if label == "solar":
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label = "solar PV"
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if label == "heat pump":
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label = "air heat pump"
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if label == "Sabatier":
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label = "methanation"
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if label == "offwind":
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label = "offshore wind"
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if label == "onwind":
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label = "onshore wind"
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if label == "ror":
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label = "hydroelectricity"
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if label == "hydro":
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label = "hydroelectricity"
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if label == "PHS":
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label = "hydroelectricity"
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if label == "co2 Store":
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label = "DAC"
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if "battery" in label:
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label = "battery storage"
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return label
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preferred_order = pd.Index(["transmission lines","hydroelectricity","hydro reservoir","run of river","pumped hydro storage","onshore wind","offshore wind","solar PV","solar thermal","building retrofitting","ground heat pump","air heat pump","resistive heater","CHP","OCGT","gas boiler","gas","natural gas","methanation","hydrogen storage","battery storage","hot water storage"])
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def plot_costs():
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cost_df = pd.read_csv(snakemake.input.costs,index_col=list(range(3)),header=[0,1,2])
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df = cost_df.groupby(cost_df.index.get_level_values(2)).sum()
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#convert to billions
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df = df/1e9
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df = df.groupby(df.index.map(rename_techs)).sum()
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to_drop = df.index[df.max(axis=1) < snakemake.config['plotting']['costs_threshold']]
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print("dropping")
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print(df.loc[to_drop])
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df = df.drop(to_drop)
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print(df.sum())
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new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
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new_columns = df.sum().sort_values().index
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fig, ax = plt.subplots()
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fig.set_size_inches((12,8))
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df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[snakemake.config['plotting']['tech_colors'][i] for i in new_index])
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handles,labels = ax.get_legend_handles_labels()
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handles.reverse()
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labels.reverse()
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ax.set_ylim([0,snakemake.config['plotting']['costs_max']])
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ax.set_ylabel("System Cost [EUR billion per year]")
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ax.set_xlabel("")
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ax.grid(axis="y")
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ax.legend(handles,labels,ncol=4,loc="upper left")
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fig.tight_layout()
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fig.savefig(snakemake.output.costs,transparent=True)
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def plot_energy():
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energy_df = pd.read_csv(snakemake.input.energy,index_col=list(range(2)),header=[0,1,2])
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df = energy_df.groupby(energy_df.index.get_level_values(1)).sum()
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#convert MWh to TWh
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df = df/1e6
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df = df.groupby(df.index.map(rename_techs)).sum()
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to_drop = df.index[df.abs().max(axis=1) < snakemake.config['plotting']['energy_threshold']]
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print("dropping")
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print(df.loc[to_drop])
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df = df.drop(to_drop)
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print(df.sum())
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new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
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new_columns = df.columns.sort_values()
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fig, ax = plt.subplots()
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fig.set_size_inches((12,8))
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df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[snakemake.config['plotting']['tech_colors'][i] for i in new_index])
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handles,labels = ax.get_legend_handles_labels()
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handles.reverse()
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labels.reverse()
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ax.set_ylim([snakemake.config['plotting']['energy_min'],snakemake.config['plotting']['energy_max']])
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ax.set_ylabel("Energy [TWh/a]")
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ax.set_xlabel("")
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ax.grid(axis="y")
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ax.legend(handles,labels,ncol=4,loc="upper left")
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fig.tight_layout()
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fig.savefig(snakemake.output.energy,transparent=True)
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if __name__ == "__main__":
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# Detect running outside of snakemake and mock snakemake for testing
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if 'snakemake' not in globals():
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from vresutils import Dict
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import yaml
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snakemake = Dict()
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with open('config.yaml') as f:
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snakemake.config = yaml.load(f)
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snakemake.input = Dict()
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snakemake.output = Dict()
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name = "37-lv"
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for item in ["costs","energy"]:
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snakemake.input[item] = snakemake.config['summary_dir'] + '/{name}/csvs/{item}.csv'.format(name=name,item=item)
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snakemake.output[item] = snakemake.config['summary_dir'] + '/{name}/graphs/{item}.pdf'.format(name=name,item=item)
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plot_costs()
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plot_energy()
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