update the format
This commit is contained in:
Hanzhang Ma
parent
e04e01e943
commit
3740136d7c
@ -21,6 +21,13 @@ class EnergySystem:
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self.summer_week_soc = []
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self.autumn_week_soc = []
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self.winter_week_soc = []
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self.factory_demand = []
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self.buy_price_kWh = []
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self.sell_price_kWh = []
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self.pv_generated_kWh = []
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self.grid_need_power_kW = []
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self.time = []
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self.ess_rest = 0
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self.granularity = 4
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self.season_step = self.granularity * 24 * 7 * 12
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self.season_start= self.granularity * 24 * 7 * 2
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@ -37,8 +44,10 @@ class EnergySystem:
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total_benefit = 0
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total_netto_benefit = 0
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total_gen = 0
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net_grid = 0.
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for index, row in data.iterrows():
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time = row['time']
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self.time.append(time)
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# sunlight_intensity = row['sunlight']
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pv_yield = row['PV yield[kW/kWp]']
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factory_demand = row['demand']
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@ -58,6 +67,11 @@ class EnergySystem:
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generated_pv_power = self.pv.capacity * pv_yield# 生成的功率，单位 kW
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generated_pv_energy = generated_pv_power * time_interval * self.pv.loss # 生成的能量，单位 kWh
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self.pv_generated_kWh.append(generated_pv_energy)
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self.factory_demand.append(factory_demand)
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self.buy_price_kWh.append(electricity_price)
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self.sell_price_kWh.append(sell_price)
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self.generated += generated_pv_energy
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# pv生成的能量如果比工厂的需求要大
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if generated_pv_energy >= factory_demand * time_interval:
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@ -75,6 +89,7 @@ class EnergySystem:
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# 节省的能量 = 工厂需求的能量 * 时间段
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# total_energy = factory_demand * time_interval
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saved_energy = factory_demand * time_interval
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self.grid_need_power_kW.append(0)
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# pv比工厂的需求小
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else:
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# 从ess中需要的电量 = 工厂需要的电量 - pv中的电量
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@ -90,6 +105,7 @@ class EnergySystem:
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self.ess.storage -= discharging_power
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# 节省下来的能量 = pv的能量 + 放出来的能量
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saved_energy = generated_pv_energy + discharging_power * self.ess.loss
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self.grid_need_power_kW.append(0)
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else:
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# 如果存的电量不够
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# 需要把ess中的所有电量释放出来
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@ -106,6 +122,7 @@ class EnergySystem:
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self.ess.storage = 0
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needed_from_grid = factory_demand * time_interval - saved_energy
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net_grid = min(self.grid.capacity * time_interval, needed_from_grid) * self.grid.loss
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self.grid_need_power_kW.append(needed_from_grid * 4)
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# grid_energy += net_grid
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# total_energy += net_grid
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# print(total_energy)
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@ -124,6 +141,7 @@ class EnergySystem:
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if index in range(week_start, week_end):
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self.spring_week_gen.append(generated_pv_power)
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self.spring_week_soc.append(self.ess.storage / self.ess.capacity)
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self.ess_rest = self.ess.storage
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# summer
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# week_start += self.season_step
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# week_end += self.season_step
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@ -17,12 +17,12 @@
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"pv_capacities":{
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"begin": 0,
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"end": 50000,
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"groups": 11
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"groups": 3
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},
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"ess_capacities":{
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"begin": 0,
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"end": 100000,
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"groups": 11
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"groups": 3
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},
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"time_interval":{
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"numerator": 15,
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@ -10,12 +10,12 @@ class pv_config:
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def get_cost_per_year(self):
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return self.capacity * self.cost_per_kW / self.lifetime
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class ess_config:
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def __init__(self, capacity, cost_per_kW, lifetime, loss, charge_power, discharge_power):
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def __init__(self, capacity, cost_per_kW, lifetime, loss, charge_power, discharge_power, storage=0):
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self.capacity = capacity
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self.cost_per_kW = cost_per_kW
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self.lifetime = lifetime
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self.loss = loss
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self.storage = 0
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self.storage = storage
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self.charge_power = charge_power
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self.discharge_power = discharge_power
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def get_cost(self):
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807
main.ipynb
807
main.ipynb
File diff suppressed because one or more lines are too long
162
main.py
162
main.py
@ -1,5 +1,9 @@
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#!/usr/bin/env python
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# coding: utf-8
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# In[39]:
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import os
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import glob
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import shutil
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@ -24,6 +28,9 @@ folder_path = 'plots'
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clear_folder_make_ess_pv(folder_path)
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# In[40]:
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import matplotlib.pyplot as plt
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import seaborn as sns
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import numpy as np
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@ -31,6 +38,10 @@ import pandas as pd
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from EnergySystem import EnergySystem
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from config import pv_config, grid_config, ess_config
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# In[41]:
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import json
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print("Version 0.0.5")
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@ -38,6 +49,9 @@ print("Version 0.0.5")
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with open('config.json', 'r') as f:
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js_data = json.load(f)
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time_interval = js_data["time_interval"]["numerator"] / js_data["time_interval"]["denominator"]
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print(time_interval)
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@ -102,7 +116,7 @@ ess_capacities = np.linspace(ess_begin, ess_end, ess_groups)
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# overload_cnt = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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# In[ ]:
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# In[42]:
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hour_demand = []
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@ -118,6 +132,9 @@ plt.savefig('plots/demand.png')
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plt.close()
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# In[43]:
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def draw_results(results, filename, title_benefit, annot_benefit=False, figure_size=(10, 10)):
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df=results
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df = df.astype(float)
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@ -154,7 +171,7 @@ def draw_results(results, filename, title_benefit, annot_benefit=False, figure_s
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plt.savefig(filename)
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# In[ ]:
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# In[44]:
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def draw_roi(costs, results, filename, title_roi, days=365, annot_roi=False, figure_size=(10, 10)):
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@ -202,6 +219,11 @@ def draw_roi(costs, results, filename, title_roi, days=365, annot_roi=False, fig
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plt.xlabel('ESS Capacity (MWh)')
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plt.ylabel('PV Capacity (MW)')
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plt.savefig(filename)
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plt.close()
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# In[45]:
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def draw_cost(costs, filename, title_cost, annot_cost=False, figure_size=(10, 10)):
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df = costs
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@ -232,6 +254,10 @@ def draw_cost(costs, filename, title_cost, annot_cost=False, figure_size=(10, 10
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plt.xlabel('ESS Capacity (MWh)')
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plt.ylabel('PV Capacity (MW)')
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plt.savefig(filename)
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plt.close()
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# In[46]:
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def draw_overload(overload_cnt, filename, title_unmet, annot_unmet=False, figure_size=(10, 10), days=365, granularity=15):
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@ -280,12 +306,21 @@ def draw_overload(overload_cnt, filename, title_unmet, annot_unmet=False, figure
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plt.xlabel('ESS Capacity (MWh)')
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plt.ylabel('PV Capacity (MW)')
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plt.savefig(filename)
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plt.close()
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# In[47]:
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def cal_profit(es: EnergySystem, saved_money, days):
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profit = saved_money - es.ess.get_cost_per_year() / 365 * days - es.pv.get_cost_per_year() / 365 * days
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return profit
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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):
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# In[48]:
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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):
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pv = pv_config(capacity=pv_capacity,
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cost_per_kW=pv_cost_per_kW,
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lifetime=pv_lifetime,
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@ -295,7 +330,8 @@ def generate_data(pv_capacity, pv_cost_per_kW, pv_lifetime, pv_loss, ess_capacit
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lifetime=ess_lifetime,
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loss=ess_loss,
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charge_power=ess_capacity,
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discharge_power=ess_capacity)
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discharge_power=ess_capacity,
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storage=storage)
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grid = grid_config(capacity=grid_capacity,
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grid_loss=grid_loss,
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sell_price= sell_price)
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@ -306,7 +342,22 @@ def generate_data(pv_capacity, pv_cost_per_kW, pv_lifetime, pv_loss, ess_capacit
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results = cal_profit(energySystem, benefit, days)
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overload_cnt = energySystem.overload_cnt
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costs = energySystem.ess.capacity * energySystem.ess.cost_per_kW + energySystem.pv.capacity * energySystem.pv.cost_per_kW
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return (results, overload_cnt, costs, netto_benefit, gen_energy, energySystem.generated)
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return (results,
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overload_cnt,
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costs,
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netto_benefit,
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gen_energy,
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energySystem.generated,
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energySystem.ess_rest,
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energySystem.factory_demand,
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energySystem.buy_price_kWh,
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energySystem.sell_price_kWh,
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energySystem.pv_generated_kWh,
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energySystem.grid_need_power_kW,
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energySystem.time)
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# In[49]:
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months_results = []
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@ -315,6 +366,8 @@ months_overload = []
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months_nettos = []
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months_gen_energy = []
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months_gen_energy2 = []
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months_ess_rest = pd.DataFrame(30, index=pv_capacities, columns= ess_capacities)
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months_csv_data = {}
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for index, month_data in enumerate(months_data):
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results = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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costs = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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@ -322,15 +375,61 @@ for index, month_data in enumerate(months_data):
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nettos = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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gen_energies = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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gen_energies2 = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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factory_demands = {}
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buy_prices= {}
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sell_prices = {}
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pv_generates = {}
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grid_need_powers = {}
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times = {}
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for pv_capacity in pv_capacities:
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factory_demands[pv_capacity] = {}
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buy_prices[pv_capacity] = {}
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sell_prices[pv_capacity] = {}
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pv_generates[pv_capacity] = {}
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grid_need_powers[pv_capacity] = {}
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times[pv_capacity] = {}
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for ess_capacity in ess_capacities:
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(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])
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(result,
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overload,
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cost,
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netto,
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gen_energy,
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gen_energy2,
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ess_rest,
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factory_demand,
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buy_price,
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sell_price,
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pv_generate,
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grid_need_power,
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time) = generate_data(pv_capacity=pv_capacity,
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pv_cost_per_kW=pv_cost_per_kW,
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pv_lifetime=pv_lifetime,
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pv_loss=pv_loss,
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ess_capacity=ess_capacity,
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ess_cost_per_kW=ess_cost_per_kW,
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ess_lifetime=ess_lifetime,
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ess_loss=ess_loss,
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grid_capacity=grid_capacity,
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grid_loss=grid_loss,
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sell_price=sell_price,
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time_interval=time_interval,
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data=month_data,
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days=months_days[index],
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storage=months_ess_rest.loc[pv_capacity, ess_capacity])
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results.loc[pv_capacity,ess_capacity] = result
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overload_cnt.loc[pv_capacity,ess_capacity] = overload
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costs.loc[pv_capacity,ess_capacity] = cost
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nettos.loc[pv_capacity,ess_capacity] = netto
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gen_energies.loc[pv_capacity, ess_capacity] = gen_energy
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gen_energies2.loc[pv_capacity, ess_capacity] = gen_energy2
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months_ess_rest.loc[pv_capacity, ess_capacity] = ess_rest
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factory_demands[pv_capacity][ess_capacity] = factory_demand
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buy_prices[pv_capacity][ess_capacity] = buy_price
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sell_prices[pv_capacity][ess_capacity] = sell_price
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pv_generates[pv_capacity][ess_capacity] = pv_generate
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grid_need_powers[pv_capacity][ess_capacity] = grid_need_power
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times[pv_capacity][ess_capacity] = time
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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}
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months_results.append(results)
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months_costs.append(costs)
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months_overload.append(overload_cnt)
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@ -349,7 +448,6 @@ for index, month_data in enumerate(months_data):
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figure_size=figure_size,
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days=months_days[index],
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granularity=granularity)
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annual_result = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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annual_costs = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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annual_overload = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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@ -358,7 +456,6 @@ annual_gen = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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annual_gen2 = pd.DataFrame(index=pv_capacities, columns= ess_capacities)
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# get the yearly results
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for pv_capacity in pv_capacities:
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for ess_capacity in ess_capacities:
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@ -399,11 +496,53 @@ draw_overload(overload_cnt=annual_overload,
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figure_size=figure_size)
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# In[50]:
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def collapse_months_csv_data(months_csv_data, column_name,pv_capacies, ess_capacities):
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data = {}
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for pv_capacity in pv_capacities:
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data[pv_capacity] = {}
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for ess_capacity in ess_capacities:
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annual_data = []
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for index, month_data in enumerate(months_data):
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annual_data.extend(months_csv_data[index][column_name][pv_capacity][ess_capacity])
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# months_csv_data[index][column_name][pv_capacity][ess_capacity] = months_csv_data[index][column_name][pv_capacity][ess_capacity].tolist()
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data[pv_capacity][ess_capacity] = annual_data
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return data
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# In[51]:
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annual_pv_gen = collapse_months_csv_data(months_csv_data, "pv_generate", pv_capacities, ess_capacities)
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annual_time = collapse_months_csv_data(months_csv_data, "time", pv_capacities, ess_capacities)
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annual_buy_price = collapse_months_csv_data(months_csv_data, "buy_price",pv_capacities, ess_capacities)
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annual_sell_price = collapse_months_csv_data(months_csv_data, "sell_price", pv_capacities, ess_capacities)
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annual_factory_demand = collapse_months_csv_data(months_csv_data, "factory_demand", pv_capacities, ess_capacities)
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annual_grid_need_power = collapse_months_csv_data(months_csv_data, "grid_need_power", pv_capacities, ess_capacities)
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for pv_capacity in pv_capacities:
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for ess_capacity in ess_capacities:
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with open(f'data/annual_data-pv-{pv_capacity}-ess-{ess_capacity}.csv', 'w') as f:
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f.write("time,pv_generate,factory_demand,buy_price,sell_price,grid_need_power\n")
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for i in range(len(annual_time[pv_capacity][ess_capacity])):
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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")
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# In[52]:
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def save_data(data, filename):
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data.to_csv(filename+'.csv')
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data.to_json(filename + '.json')
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# In[53]:
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if not os.path.isdir('data'):
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os.makedirs('data')
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@ -411,8 +550,15 @@ save_data(annual_result, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess
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save_data(annual_costs, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-costs')
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save_data(annual_overload, f'data/{pv_begin}-{pv_end}-{pv_groups}-{ess_begin}-{ess_end}-{ess_groups}-overload_cnt')
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# In[54]:
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draw_results(annual_result, 'plots/test.png', 'test', False)
|
||||
|
||||
|
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# In[55]:
|
||||
|
||||
|
||||
draw_roi(annual_costs, annual_nettos, 'plots/annual_roi.png', title_roi, 365, annot_benefit, figure_size)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user