def _plot_energy_profile_hr(self, area: Area, subdir: str):
"""
Plots history of energy trades plotted for each market_slot
"""
area_stats = self.endpoint_buffer.area_market_stocks_stats.state[
area.name]
barmode = "relative"
xtitle = 'Time'
ytitle = 'Energy [kWh]'
market_name = area.name
title = f'High Resolution Energy Trade Profile of {market_name}'
plot_dir = os.path.join(self.plot_dir, subdir, "energy_profile_hr")
mkdir_from_str(plot_dir)
for market_slot, data in area_stats.items():
plot_data = self.add_plotly_graph_dataset(data, market_slot)
if len(plot_data) > 0:
market_slot_str = market_slot.format(DATE_TIME_FORMAT)
output_file = \
os.path.join(plot_dir, f'energy_profile_hr_'
f'{market_name}_{market_slot_str}.html')
time_range = [
market_slot - GlobalConfig.tick_length, market_slot +
GlobalConfig.slot_length + GlobalConfig.tick_length
]
PlotlyGraph.plot_bar_graph(barmode,
title,
xtitle,
ytitle,
plot_data,
output_file,
time_range=time_range)
def _plot_ess_soc_history(self, storage_list: list, subdir: str,
root_name: str):
"""
Plots ess soc for each knot in the hierarchy
"""
storage_key = 'charge [%]'
data = list()
barmode = "relative"
title = 'ESS SOC ({})'.format(root_name)
xtitle = 'Time'
ytitle = 'Charge [%]'
for si in storage_list:
graph_obj = PlotlyGraph(self.file_stats_endpoint.plot_stats[si],
storage_key)
graph_obj.graph_value()
data_obj = go.Scatter(x=list(graph_obj.umHours.keys()),
y=list(graph_obj.umHours.values()),
name=si)
data.append(data_obj)
if len(data) == 0:
return
plot_dir = os.path.join(self.plot_dir, subdir)
mkdir_from_str(plot_dir)
output_file = os.path.join(plot_dir,
'ess_soc_history_{}.html'.format(root_name))
PlotlyGraph.plot_bar_graph(barmode, title, xtitle, ytitle, data,
output_file)
def __init__(self, root_area: Area, path: str, subdir: str,
file_stats_endpoint, endpoint_buffer):
self.area = root_area
self.endpoint_buffer = endpoint_buffer
self.file_stats_endpoint = file_stats_endpoint
self.raw_data_subdir = None
try:
if path is not None:
path = os.path.abspath(path)
if ConstSettings.IAASettings.AlternativePricing.COMPARE_PRICING_SCHEMES is True:
subdir = os.path.join(
subdir, alternative_pricing_subdirs[
ConstSettings.IAASettings.AlternativePricing.
PRICING_SCHEME])
self.rootdir = pathlib.Path(
path or str(pathlib.Path.home()) + "/d3a-simulation")
self.directory = pathlib.Path(self.rootdir, subdir)
self.zip_filename = pathlib.Path(self.rootdir, subdir + "_results")
mkdir_from_str(str(self.directory))
if d3a.constants.RETAIN_PAST_MARKET_STRATEGIES_STATE:
self.raw_data_subdir = pathlib.Path(self.directory, "raw_data")
if not self.raw_data_subdir.exists():
self.raw_data_subdir.mkdir(exist_ok=True, parents=True)
except Exception as ex:
_log.error("Could not open directory for csv exports: %s" %
str(ex))
return
def _plot_energy_profile(self, subdir: str, market_name: str,
energy_profile):
"""
Plots history of energy trades
"""
data = list()
barmode = "relative"
xtitle = 'Time'
ytitle = 'Energy [kWh]'
key = 'energy'
title = 'Energy Trade Profile of {}'.format(market_name)
data.extend(
self._plot_energy_graph(energy_profile, market_name,
"sold_energy_lists", "-seller", key,
ENERGY_SELLER_SIGN_PLOTS))
data.extend(
self._plot_energy_graph(energy_profile, market_name,
"bought_energy_lists", "-buyer", key,
ENERGY_BUYER_SIGN_PLOTS))
if len(data) == 0:
return
if all([len(da.y) == 0 for da in data]):
return
plot_dir = os.path.join(self.plot_dir, subdir)
mkdir_from_str(plot_dir)
output_file = os.path.join(
plot_dir, 'energy_profile_{}.html'.format(market_name))
PlotlyGraph.plot_bar_graph(barmode, title, xtitle, ytitle, data,
output_file)
def plot_all_unmatched_loads(self):
"""
Plot unmatched loads of all loads in the configuration into one plot
"""
unmatched_key = 'deficit [kWh]'
data = list()
root_name = self.area.slug
title = 'Unmatched Loads for all devices in {}'.format(root_name)
xtitle = 'Time'
ytitle = 'Energy (kWh)'
barmode = 'stack'
load_list = [
child_key for child_key in self.export_data.plot_stats.keys()
if unmatched_key in self.export_data.plot_stats[child_key].keys()
]
for li in load_list:
graph_obj = PlotlyGraph(self.export_data.plot_stats[li],
unmatched_key)
if sum(graph_obj.dataset[unmatched_key]) < 1e-10:
continue
graph_obj.graph_value()
data_obj = go.Bar(x=list(graph_obj.umHours.keys()),
y=list(graph_obj.umHours.values()),
name=li)
data.append(data_obj)
if len(data) == 0:
return
plot_dir = os.path.join(self.plot_dir)
mkdir_from_str(plot_dir)
output_file = os.path.join(plot_dir,
'unmatched_loads_{}.html'.format(root_name))
PlotlyGraph.plot_bar_graph(barmode, title, xtitle, ytitle, data,
output_file)
def export_json_data(self, directory: dir):
json_dir = os.path.join(directory, "aggregated_results")
mkdir_from_str(json_dir)
settings_file = os.path.join(json_dir, "const_settings.json")
with open(settings_file, 'w') as outfile:
json.dump(constsettings_to_dict(), outfile, indent=2)
for key, value in self.endpoint_buffer.generate_json_report().items():
json_file = os.path.join(json_dir, key + ".json")
with open(json_file, 'w') as outfile:
json.dump(value, outfile, indent=2)
def plot_stock_info_per_area_per_market_slot(self, area, plot_dir):
"""
Wrapper for _plot_stock_info_per_area_per_market_slot.
"""
new_sub_dir = os.path.join(plot_dir, area.slug)
mkdir_from_str(new_sub_dir)
self._plot_stock_info_per_area_per_market_slot(area, new_sub_dir)
for child in area.children:
if not child.children:
continue
self.plot_stock_info_per_area_per_market_slot(child, new_sub_dir)
def _plot_supply_demand_curve(self, subdir: str, area: Area):
if area.slug not in self.file_stats_endpoint.clearing:
return
for market_slot, clearing in self.file_stats_endpoint.clearing[
area.slug].items():
data = list()
xmax = 0
for time_slot, supply_curve in \
self.file_stats_endpoint.cumulative_offers[area.slug][market_slot].items():
data.append(
self.render_supply_demand_curve(supply_curve, time_slot,
True))
for time_slot, demand_curve in \
self.file_stats_endpoint.cumulative_bids[area.slug][market_slot].items():
data.append(
self.render_supply_demand_curve(demand_curve, time_slot,
False))
if len(data) == 0:
continue
for time_slot, clearing_point in clearing.items():
# clearing_point[0] --> Clearing-Rate
# clearing_point[1] --> Clearing-Energy
if len(clearing_point) != 0:
data_obj = go.Scatter(
x=[0, clearing_point[1]],
y=[clearing_point[0], clearing_point[0]],
mode='lines+markers',
line=dict(width=5),
name=time_slot.format(DATE_TIME_FORMAT) +
' Clearing-Rate')
data.append(data_obj)
data_obj = go.Scatter(
x=[clearing_point[1], clearing_point[1]],
y=[0, clearing_point[0]],
mode='lines+markers',
line=dict(width=5),
name=time_slot.format(DATE_TIME_FORMAT) +
' Clearing-Energy')
data.append(data_obj)
xmax = max(xmax, clearing_point[1]) * 3
plot_dir = os.path.join(self.plot_dir, subdir, 'mcp')
mkdir_from_str(plot_dir)
output_file = os.path.join(plot_dir,
f'supply_demand_{market_slot}.html')
PlotlyGraph.plot_line_graph('supply_demand_curve', 'Energy (kWh)',
'Rate (ct./kWh)', data, output_file,
xmax)
def _plot_ess_energy_trace(self, energy: dict, subdir: str,
root_name: str):
"""
Plots ess energy trace for each knot in the hierarchy
"""
data = list()
barmode = "stack"
title = 'ESS ENERGY SHARE ({})'.format(root_name)
xtitle = 'Time'
ytitle = 'Energy [kWh]'
temp = {
ESSEnergyOrigin.UNKNOWN:
{slot: 0.
for slot in generate_market_slot_list()},
ESSEnergyOrigin.LOCAL:
{slot: 0.
for slot in generate_market_slot_list()},
ESSEnergyOrigin.EXTERNAL:
{slot: 0.
for slot in generate_market_slot_list()}
}
for time, energy_info in energy.items():
temp[ESSEnergyOrigin.EXTERNAL][time] = energy_info[
ESSEnergyOrigin.EXTERNAL]
temp[ESSEnergyOrigin.LOCAL][time] = energy_info[
ESSEnergyOrigin.LOCAL]
temp[ESSEnergyOrigin.UNKNOWN][time] = energy_info[
ESSEnergyOrigin.UNKNOWN]
for energy_type in [
ESSEnergyOrigin.EXTERNAL, ESSEnergyOrigin.LOCAL,
ESSEnergyOrigin.UNKNOWN
]:
data_obj = go.Bar(x=list(temp[energy_type].keys()),
y=list(temp[energy_type].values()),
name=f"{energy_type}")
data.append(data_obj)
if len(data) == 0:
return
plot_dir = os.path.join(self.plot_dir, subdir)
mkdir_from_str(plot_dir)
output_file = os.path.join(
plot_dir, 'ess_energy_share_{}.html'.format(root_name))
PlotlyGraph.plot_bar_graph(barmode, title, xtitle, ytitle, data,
output_file)
def _plot_energy_profile(self, subdir: str, market_name: str):
"""
Plots history of energy trades
"""
data = list()
barmode = "relative"
xtitle = 'Time'
ytitle = 'Energy [kWh]'
key = 'energy'
title = 'Energy Trade Profile of {}'.format(market_name)
data.extend(
self._plot_energy_graph(
self.endpoint_buffer.trade_profile.traded_energy_profile,
market_name, "sold_energy_lists", "-seller", key,
ENERGY_SELLER_SIGN_PLOTS))
data.extend(
self._plot_energy_graph(
self.endpoint_buffer.trade_profile.traded_energy_profile,
market_name, "bought_energy_lists", "-buyer", key,
ENERGY_BUYER_SIGN_PLOTS))
if ConstSettings.BalancingSettings.ENABLE_BALANCING_MARKET:
if "sold_energy_lists" in \
self.endpoint_buffer.trade_profile.balancing_traded_energy[market_name]:
data.extend(
self._plot_energy_graph(
self.endpoint_buffer.trade_profile.
balancing_traded_energy, market_name,
"sold_energy_lists", "-balancing-seller", key,
ENERGY_SELLER_SIGN_PLOTS))
data.extend(
self._plot_energy_graph(
self.endpoint_buffer.trade_profile.
balancing_traded_energy, market_name,
"bought_energy_lists", "-balancing-buyer", key,
ENERGY_BUYER_SIGN_PLOTS))
if len(data) == 0:
return
if all([len(da.y) == 0 for da in data]):
return
plot_dir = os.path.join(self.plot_dir, subdir)
mkdir_from_str(plot_dir)
output_file = os.path.join(
plot_dir, 'energy_profile_{}.html'.format(market_name))
PlotlyGraph.plot_bar_graph(barmode, title, xtitle, ytitle, data,
output_file)
def _plot_device_stats(self, address_list: list, device_strategy):
"""
Plots device graphs
"""
# Dont use the root area name for address list:
device_address_list = address_list[1::]
device_name = device_address_list[-1].replace(" ", "_")
device_stats = self.endpoint_buffer.results_handler.all_raw_results[
"device_statistics"]
device_dict = get_from_dict(device_stats, device_address_list)
# converting address_list into plot_dir by slugifying the members
plot_dir = os.path.join(
self.plot_dir,
"/".join([slugify(node).lower() for node in address_list][0:-1]))
mkdir_from_str(plot_dir)
output_file = os.path.join(
plot_dir, 'device_profile_{}.html'.format(device_name))
PlotlyGraph.plot_device_profile(device_dict, device_name, output_file,
device_strategy)
def _plot_avg_trade_price(self, area_list: list, subdir: str):
"""
Plots average trade for the specified level of the hierarchy
"""
data = list()
barmode = 'stack'
xtitle = "Time"
ytitle = "Rate [ct./kWh]"
key = 'avg trade rate [ct./kWh]'
title = 'Average Trade Price {}'.format(area_list[0])
for area_name in area_list:
data.append(
self._plot_avg_trade_graph(self.file_stats_endpoint.plot_stats,
area_name, key, area_name))
if ConstSettings.BalancingSettings.ENABLE_BALANCING_MARKET and \
self.file_stats_endpoint.plot_balancing_stats[area_name.lower()] is not None:
area_name_balancing = area_name.lower(
) + "-demand-balancing-trades"
data.append(
self._plot_avg_trade_graph(
self.file_stats_endpoint.plot_balancing_stats,
area_name, 'avg demand balancing trade rate [ct./kWh]',
area_name_balancing))
area_name_balancing = area_name.lower(
) + "-supply-balancing-trades"
data.append(
self._plot_avg_trade_graph(
self.file_stats_endpoint.plot_balancing_stats,
area_name, 'avg supply balancing trade rate [ct./kWh]',
area_name_balancing))
if all([len(da.y) == 0 for da in data]):
return
plot_dir = os.path.join(self.plot_dir, subdir)
mkdir_from_str(plot_dir)
output_file = os.path.join(
plot_dir, 'average_trade_price_{}.html'.format(area_list[0]))
PlotlyGraph.plot_bar_graph(barmode, title, xtitle, ytitle, data,
output_file)
def __init__(self, root_area: Area, path: str, subdir: str,
file_stats_endpoint, endpoint_buffer):
self.area = root_area
self.endpoint_buffer = endpoint_buffer
self.file_stats_endpoint = file_stats_endpoint
try:
if path is not None:
path = os.path.abspath(path)
if ConstSettings.IAASettings.AlternativePricing.COMPARE_PRICING_SCHEMES is True:
subdir = os.path.join(
subdir, alternative_pricing_subdirs[
ConstSettings.IAASettings.AlternativePricing.
PRICING_SCHEME])
self.rootdir = pathlib.Path(
path or str(pathlib.Path.home()) + "/d3a-simulation")
self.directory = pathlib.Path(self.rootdir, subdir)
self.zip_filename = pathlib.Path(self.rootdir, subdir + "_results")
mkdir_from_str(str(self.directory))
except Exception as ex:
_log.error("Could not open directory for csv exports: %s" %
str(ex))
return
