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update the format

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This commit is contained in:
Hanzhang Ma
2024-05-15 15:06:43 +02:00
parent e04e01e943
commit 3740136d7c
5 changed files with 955 additions and 40 deletions
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18
EnergySystem.py
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@@ -21,6 +21,13 @@ class EnergySystem:
self.summer_week_soc = []
self.autumn_week_soc = []
self.winter_week_soc = []
self.factory_demand = []
self.buy_price_kWh = []
self.sell_price_kWh = []
self.pv_generated_kWh = []
self.grid_need_power_kW = []
self.time = []
self.ess_rest = 0
self.granularity = 4
self.season_step = self.granularity * 24 * 7 * 12
self.season_start= self.granularity * 24 * 7 * 2
@@ -37,8 +44,10 @@ class EnergySystem:
total_benefit = 0
total_netto_benefit = 0
total_gen = 0
net_grid = 0.
for index, row in data.iterrows():
time = row['time']
self.time.append(time)
# sunlight_intensity = row['sunlight']
pv_yield = row['PV yield[kW/kWp]']
factory_demand = row['demand']
@@ -58,6 +67,11 @@ class EnergySystem:
generated_pv_power = self.pv.capacity * pv_yield# 生成的功率，单位 kW
generated_pv_energy = generated_pv_power * time_interval * self.pv.loss # 生成的能量，单位 kWh
self.pv_generated_kWh.append(generated_pv_energy)
self.factory_demand.append(factory_demand)
self.buy_price_kWh.append(electricity_price)
self.sell_price_kWh.append(sell_price)
self.generated += generated_pv_energy
# pv生成的能量如果比工厂的需求要大
if generated_pv_energy >= factory_demand * time_interval:
@@ -75,6 +89,7 @@ class EnergySystem:
# 节省的能量 = 工厂需求的能量 * 时间段
# total_energy = factory_demand * time_interval
saved_energy = factory_demand * time_interval
self.grid_need_power_kW.append(0)
# pv比工厂的需求小
else:
# 从ess中需要的电量 = 工厂需要的电量 - pv中的电量
@@ -90,6 +105,7 @@ class EnergySystem:
self.ess.storage -= discharging_power
# 节省下来的能量 = pv的能量 + 放出来的能量
saved_energy = generated_pv_energy + discharging_power * self.ess.loss
self.grid_need_power_kW.append(0)
else:
# 如果存的电量不够
# 需要把ess中的所有电量释放出来
@@ -106,6 +122,7 @@ class EnergySystem:
self.ess.storage = 0
needed_from_grid = factory_demand * time_interval - saved_energy
net_grid = min(self.grid.capacity * time_interval, needed_from_grid) * self.grid.loss
self.grid_need_power_kW.append(needed_from_grid * 4)
# grid_energy += net_grid
# total_energy += net_grid
# print(total_energy)
@@ -124,6 +141,7 @@ class EnergySystem:
if index in range(week_start, week_end):
self.spring_week_gen.append(generated_pv_power)
self.spring_week_soc.append(self.ess.storage / self.ess.capacity)
self.ess_rest = self.ess.storage
# summer
# week_start += self.season_step
# week_end += self.season_step

4
config.json
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@@ -17,12 +17,12 @@
"pv_capacities":{
"begin": 0,
"end": 50000,
"groups": 11
"groups": 3
},
"ess_capacities":{
"begin": 0,
"end": 100000,
"groups": 11
"groups": 3
},
"time_interval":{
"numerator": 15,

4
config.py
View File

@@ -10,12 +10,12 @@ class pv_config:
def get_cost_per_year(self):
return self.capacity * self.cost_per_kW / self.lifetime
class ess_config:
def __init__(self, capacity, cost_per_kW, lifetime, loss, charge_power, discharge_power):
def __init__(self, capacity, cost_per_kW, lifetime, loss, charge_power, discharge_power, storage=0):
self.capacity = capacity
self.cost_per_kW = cost_per_kW
self.lifetime = lifetime
self.loss = loss
self.storage = 0
self.storage = storage
self.charge_power = charge_power
self.discharge_power = discharge_power
def get_cost(self):

807
main.ipynb
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File diff suppressed because one or more lines are too long

162
main.py
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@@ -1,5 +1,9 @@
#!/usr/bin/env python
# coding: utf-8
# In[39]:
import os
import glob
import shutil
@@ -24,6 +28,9 @@ folder_path = 'plots'
clear_folder_make_ess_pv(folder_path)
# In[40]:
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
@@ -31,6 +38,10 @@ import pandas as pd
from EnergySystem import EnergySystem
from config import pv_config, grid_config, ess_config
# In[41]:
import json
print("Version 0.0.5")
@@ -38,6 +49,9 @@ print("Version 0.0.5")
with open('config.json', 'r') as f:
js_data = json.load(f)
time_interval = js_data["time_interval"]["numerator"] / js_data["time_interval"]["denominator"]
print(time_interval)
@@ -102,7 +116,7 @@ ess_capacities = np.linspace(ess_begin, ess_end, ess_groups)
# overload_cnt = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
# In[ ]:
# In[42]:
hour_demand = []
@@ -118,6 +132,9 @@ plt.savefig('plots/demand.png')
plt.close()
# In[43]:
def draw_results(results, filename, title_benefit, annot_benefit=False, figure_size=(10, 10)):
df=results
df = df.astype(float)
@@ -154,7 +171,7 @@ def draw_results(results, filename, title_benefit, annot_benefit=False, figure_s
plt.savefig(filename)
# In[ ]:
# In[44]:
def draw_roi(costs, results, filename, title_roi, days=365, annot_roi=False, figure_size=(10, 10)):
@@ -202,6 +219,11 @@ def draw_roi(costs, results, filename, title_roi, days=365, annot_roi=False, fig
plt.xlabel('ESS Capacity (MWh)')
plt.ylabel('PV Capacity (MW)')
plt.savefig(filename)
plt.close()
# In[45]:
def draw_cost(costs, filename, title_cost, annot_cost=False, figure_size=(10, 10)):
df = costs
@@ -232,6 +254,10 @@ def draw_cost(costs, filename, title_cost, annot_cost=False, figure_size=(10, 10
plt.xlabel('ESS Capacity (MWh)')
plt.ylabel('PV Capacity (MW)')
plt.savefig(filename)
plt.close()
# In[46]:
def draw_overload(overload_cnt, filename, title_unmet, annot_unmet=False, figure_size=(10, 10), days=365, granularity=15):
@@ -280,12 +306,21 @@ def draw_overload(overload_cnt, filename, title_unmet, annot_unmet=False, figure
plt.xlabel('ESS Capacity (MWh)')
plt.ylabel('PV Capacity (MW)')
plt.savefig(filename)
plt.close()
# In[47]:
def cal_profit(es: EnergySystem, saved_money, days):
profit = saved_money - es.ess.get_cost_per_year() / 365 * days - es.pv.get_cost_per_year() / 365 * days
return profit
def generate_data(pv_capacity, pv_cost_per_kW, pv_lifetime, pv_loss, ess_capacity, ess_cost_per_kW, ess_lifetime, ess_loss, grid_capacity, grid_loss, sell_price, time_interval, data, days):
# In[48]:
def generate_data(pv_capacity, pv_cost_per_kW, pv_lifetime, pv_loss, ess_capacity, ess_cost_per_kW, ess_lifetime, ess_loss, grid_capacity, grid_loss, sell_price, time_interval, data, days, storage=0):
pv = pv_config(capacity=pv_capacity,
cost_per_kW=pv_cost_per_kW,
lifetime=pv_lifetime,
@@ -295,7 +330,8 @@ def generate_data(pv_capacity, pv_cost_per_kW, pv_lifetime, pv_loss, ess_capacit
lifetime=ess_lifetime,
loss=ess_loss,
charge_power=ess_capacity,
discharge_power=ess_capacity)
discharge_power=ess_capacity,
storage=storage)
grid = grid_config(capacity=grid_capacity,
grid_loss=grid_loss,
sell_price= sell_price)
@@ -306,7 +342,22 @@ def generate_data(pv_capacity, pv_cost_per_kW, pv_lifetime, pv_loss, ess_capacit
results = cal_profit(energySystem, benefit, days)
overload_cnt = energySystem.overload_cnt
costs = energySystem.ess.capacity * energySystem.ess.cost_per_kW + energySystem.pv.capacity * energySystem.pv.cost_per_kW
return (results, overload_cnt, costs, netto_benefit, gen_energy, energySystem.generated)
return (results,
overload_cnt,
costs,
netto_benefit,
gen_energy,
energySystem.generated,
energySystem.ess_rest,
energySystem.factory_demand,
energySystem.buy_price_kWh,
energySystem.sell_price_kWh,
energySystem.pv_generated_kWh,
energySystem.grid_need_power_kW,
energySystem.time)
# In[49]:
months_results = []
@@ -315,6 +366,8 @@ months_overload = []
months_nettos = []
months_gen_energy = []
months_gen_energy2 = []
months_ess_rest = pd.DataFrame(30, index=pv_capacities, columns= ess_capacities)
months_csv_data = {}
for index, month_data in enumerate(months_data):
results = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
costs = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
@@ -322,15 +375,61 @@ for index, month_data in enumerate(months_data):
nettos = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
gen_energies = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
gen_energies2 = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
factory_demands = {}
buy_prices= {}
sell_prices = {}
pv_generates = {}
grid_need_powers = {}
times = {}
for pv_capacity in pv_capacities:
factory_demands[pv_capacity] = {}
buy_prices[pv_capacity] = {}
sell_prices[pv_capacity] = {}
pv_generates[pv_capacity] = {}
grid_need_powers[pv_capacity] = {}
times[pv_capacity] = {}
for ess_capacity in ess_capacities:
(result, overload, cost, netto, gen_energy, gen_energy2) = generate_data(pv_capacity=pv_capacity,pv_cost_per_kW=pv_cost_per_kW, pv_lifetime=pv_lifetime, pv_loss=pv_loss, ess_capacity=ess_capacity, ess_cost_per_kW=ess_cost_per_kW, ess_lifetime=ess_lifetime, ess_loss=ess_loss, grid_capacity=grid_capacity, grid_loss=grid_loss, sell_price=sell_price, time_interval=time_interval, data=month_data, days=months_days[index])
(result,
overload,
cost,
netto,
gen_energy,
gen_energy2,
ess_rest,
factory_demand,
buy_price,
sell_price,
pv_generate,
grid_need_power,
time) = generate_data(pv_capacity=pv_capacity,
pv_cost_per_kW=pv_cost_per_kW,
pv_lifetime=pv_lifetime,
pv_loss=pv_loss,
ess_capacity=ess_capacity,
ess_cost_per_kW=ess_cost_per_kW,
ess_lifetime=ess_lifetime,
ess_loss=ess_loss,
grid_capacity=grid_capacity,
grid_loss=grid_loss,
sell_price=sell_price,
time_interval=time_interval,
data=month_data,
days=months_days[index],
storage=months_ess_rest.loc[pv_capacity, ess_capacity])
results.loc[pv_capacity,ess_capacity] = result
overload_cnt.loc[pv_capacity,ess_capacity] = overload
costs.loc[pv_capacity,ess_capacity] = cost
nettos.loc[pv_capacity,ess_capacity] = netto
gen_energies.loc[pv_capacity, ess_capacity] = gen_energy
gen_energies2.loc[pv_capacity, ess_capacity] = gen_energy2
months_ess_rest.loc[pv_capacity, ess_capacity] = ess_rest
factory_demands[pv_capacity][ess_capacity] = factory_demand
buy_prices[pv_capacity][ess_capacity] = buy_price
sell_prices[pv_capacity][ess_capacity] = sell_price
pv_generates[pv_capacity][ess_capacity] = pv_generate
grid_need_powers[pv_capacity][ess_capacity] = grid_need_power
times[pv_capacity][ess_capacity] = time
months_csv_data[index] = {"factory_demand": factory_demands, "buy_price": buy_prices, "sell_price": sell_prices, "pv_generate": pv_generates, "grid_need_power": grid_need_powers, "time": times}
months_results.append(results)
months_costs.append(costs)
months_overload.append(overload_cnt)
@@ -349,7 +448,6 @@ for index, month_data in enumerate(months_data):
figure_size=figure_size,
days=months_days[index],
granularity=granularity)
annual_result = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
annual_costs = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
annual_overload = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
@@ -358,7 +456,6 @@ annual_gen = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
annual_gen2 = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
# get the yearly results
for pv_capacity in pv_capacities:
for ess_capacity in ess_capacities:
@@ -399,11 +496,53 @@ draw_overload(overload_cnt=annual_overload,
figure_size=figure_size)
# In[50]:
def collapse_months_csv_data(months_csv_data, column_name,pv_capacies, ess_capacities):
data = {}
for pv_capacity in pv_capacities:
data[pv_capacity] = {}
for ess_capacity in ess_capacities:
annual_data = []
for index, month_data in enumerate(months_data):
annual_data.extend(months_csv_data[index][column_name][pv_capacity][ess_capacity])
# months_csv_data[index][column_name][pv_capacity][ess_capacity] = months_csv_data[index][column_name][pv_capacity][ess_capacity].tolist()
data[pv_capacity][ess_capacity] = annual_data
return data
# In[51]:
annual_pv_gen = collapse_months_csv_data(months_csv_data, "pv_generate", pv_capacities, ess_capacities)
annual_time = collapse_months_csv_data(months_csv_data, "time", pv_capacities, ess_capacities)
annual_buy_price = collapse_months_csv_data(months_csv_data, "buy_price",pv_capacities, ess_capacities)
annual_sell_price = collapse_months_csv_data(months_csv_data, "sell_price", pv_capacities, ess_capacities)
annual_factory_demand = collapse_months_csv_data(months_csv_data, "factory_demand", pv_capacities, ess_capacities)
annual_grid_need_power = collapse_months_csv_data(months_csv_data, "grid_need_power", pv_capacities, ess_capacities)
for pv_capacity in pv_capacities:
for ess_capacity in ess_capacities:
with open(f'data/annual_data-pv-{pv_capacity}-ess-{ess_capacity}.csv', 'w') as f:
f.write("time,pv_generate,factory_demand,buy_price,sell_price,grid_need_power\n")
for i in range(len(annual_time[pv_capacity][ess_capacity])):
f.write(f"{annual_time[pv_capacity][ess_capacity][i]}, {int(annual_pv_gen[pv_capacity][ess_capacity][i])}, {int(annual_factory_demand[pv_capacity][ess_capacity][i])}, {int(annual_buy_price[pv_capacity][ess_capacity][i]*1000)}, {int(annual_sell_price[pv_capacity][ess_capacity][i]*1000)}, {int(annual_grid_need_power[pv_capacity][ess_capacity][i])}\n")
# In[52]:
def save_data(data, filename):
data.to_csv(filename+'.csv')
data.to_json(filename + '.json')
# In[53]:
if not os.path.isdir('data'):
os.makedirs('data')
@@ -411,8 +550,15 @@ save_data(annual_result, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess
save_data(annual_costs, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-costs')
save_data(annual_overload, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-overload_cnt')
# In[54]:
draw_results(annual_result, 'plots/test.png', 'test', False)
# In[55]:
draw_roi(annual_costs, annual_nettos, 'plots/annual_roi.png', title_roi, 365, annot_benefit, figure_size)