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Commit 984a952d authored by ZZH's avatar ZZH
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remove es 2023-6-2

parent 0bc47465
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unify_api/modules/common/procedures/pttl_max.py
View file @ 984a952d
from pot_libs.es_util.es_utils import EsUtil
from pot_libs.logger import log
from pot_libs.mysql_util.mysql_util import MysqlUtil
from unify_api.constants import POINT_15MIN_INDEX, INDEX
from unify_api.utils.es_query_body import EsQueryBody
from unify_api.utils.time_format import power_slots, range_to_type
from unify_api.utils.time_format import range_to_type
async def pttl_max(cid, start, end, point_id=None, inline_id=None):
# 根据进线,找point
if inline_id:
sql = "SELECT pid from `point` WHERE cid = %s " \
"and inlid_belongedto = %s and add_to_company = 1"
async with MysqlUtil() as conn:
point_info = await conn.fetchall(sql=sql,
args=(cid, inline_id))
point_list = [point.get("pid") for point in point_info]
terms = {"pid": point_list}
elif point_id == -1: # 选的全部
# 1.找出工厂所有pid，point表add_to_company字段为1
sql = "SELECT pid from `point` WHERE cid = %s " \
"and add_to_company = 1"
async with MysqlUtil() as conn:
point_info = await conn.fetchall(sql=sql, args=(cid,))
point_list = [point.get("pid") for point in point_info]
terms = {"pid": point_list}
else:
terms = {"pid": [point_id]}
# 1. 根据时间范围,取不同的index
date_type = range_to_type(start, end)
index = INDEX[date_type]
if date_type == "day":
date_key = "hour"
elif date_type == "month":
date_key = "day"
else:
date_key = "month"
# 2. 构造query_body
eqb = EsQueryBody(terms=terms, start=start, end=end,
date_key=date_key)
query = eqb.query()
query["aggs"] = {
"time_column": {
"date_histogram": {
"field": date_key,
"interval": date_key,
"time_zone": "+08:00",
"format": "yyyy-MM-dd HH:mm"
},
"aggs": {
"pttl_max": {
"sum": {
"field": "pttl_max"
}
}
}
}
}
log.info(index + f"====={query}")
async with EsUtil() as es:
es_re = await es.search_origin(body=query, index=index)
if not es_re["aggregations"]["time_column"]["buckets"]:
return "", ""
# 2.返回
es_re = es_re["aggregations"]["time_column"]["buckets"]
# 最大需量
max_val = 0
max_val_time = ""
for res in es_re:
mdp_max_value = res["pttl_max"]["value"]
if mdp_max_value and mdp_max_value > max_val:
max_val = mdp_max_value
max_val_time = res["key_as_string"]
# 根据时间范围, 返回不同时间格式
if max_val_time:
if date_type == "day":
max_val_time = max_val_time.split(" ")[1]
elif date_type == "month":
max_val_time = max_val_time.split("-", 1)[1].split(" ")[0]
else:
max_val_time = max_val_time[:7]
return max_val, max_val_time
async def pttl_max_new15(cid, start, end, point_id=None, inline_id=None):
async def load_pttl_max(cid, start, end, point_id=None, inline_id=None):
# 根据进线,找point
if inline_id:
sql = "SELECT pid from `point` WHERE cid = %s " \
......@@ -140,73 +60,7 @@ async def pttl_max_new15(cid, start, end, point_id=None, inline_id=None):
return max_val, max_val_time
async def pttl_max_15min(cid, start, end, point_id=None, inline_id=None):
"""负荷分布,最高负荷需要拿15min"""
# 根据进线,找point
if inline_id:
sql = "SELECT pid from `point` WHERE cid = %s " \
"and inlid_belongedto = %s"
async with MysqlUtil() as conn:
point_info = await conn.fetchall(sql=sql,
args=(cid, inline_id))
point_list = [point.get("pid") for point in point_info]
terms = {"pid": point_list}
elif point_id == -1: # 选的全部
# 1.找出工厂所有pid，point表add_to_company字段为1
sql = "SELECT pid from `point` WHERE cid = %s"
async with MysqlUtil() as conn:
point_info = await conn.fetchall(sql=sql, args=(cid,))
point_list = [point.get("pid") for point in point_info]
terms = {"pid": point_list}
else:
terms = {"pid": [point_id]}
# 1. 根据时间范围,取不同的index
index = POINT_15MIN_INDEX
date_key = "quarter_time"
interval = "15m"
# 2. 构造query_body
eqb = EsQueryBody(terms=terms, start=start, end=end,
date_key=date_key)
query = eqb.query()
query["aggs"] = {
"time_column": {
"date_histogram": {
"field": date_key,
"interval": interval,
"time_zone": "+08:00",
"format": "yyyy-MM-dd HH:mm"
},
"aggs": {
"pttl_max": {
"sum": {
"field": "pttl_max"
}
}
}
}
}
log.info(index + f"====={query}")
async with EsUtil() as es:
es_re = await es.search_origin(body=query, index=index)
if not es_re["aggregations"]["time_column"]["buckets"]:
return "", ""
# 2.返回
es_re = es_re["aggregations"]["time_column"]["buckets"]
# 最大需量
max_val = 0
max_val_time = ""
for res in es_re:
mdp_max_value = res["pttl_max"]["value"]
if mdp_max_value and mdp_max_value > max_val:
max_val = mdp_max_value
max_val_time = res["key_as_string"]
# 根据时间范围, 返回不同时间格式
if max_val_time:
max_val_time = max_val_time[5:]
return max_val, max_val_time
async def pttl_max_15min_new15(cid, start, end, point_id=None, inline_id=None):
async def load_pttl_max_15min(cid, start, end, point_id=None, inline_id=None):
if inline_id:
sql = "SELECT pid from `point` WHERE cid = %s and inlid = %s"
async with MysqlUtil() as conn:
......
unify_api/modules/elec_charge/dao/syncretize_energy_es_dao.py
View file @ 984a952d
from pot_libs.es_util.es_utils import EsUtil
from pot_libs.mysql_util.mysql_util import MysqlUtil
from pot_libs.utils.pendulum_wrapper import my_pendulum
from unify_api.utils.time_format import get_start_end_by_tz_time_new
def convert_es_str(str1: object) -> object:
"""str date转换为str es日期格式"""
es_date = my_pendulum.from_format(str1, 'YYYY-MM-DD')
return str(es_date)
async def query_search_kwh_p(cid, start, end, interval):
query_body = {
"query": {
"bool": {
"filter": [
{
"term": {
"cid": cid
}
},
{
"range": {
"quarter_time": {
"gte": convert_es_str(start),
"lte": convert_es_str(end)
}
}
}
]
}
},
"aggs": {"quarter_time": {
"date_histogram": {
"field": "quarter_time",
"interval": interval,
"time_zone": "+08:00",
"format": "yyyy-MM-dd HH:mm:ss"
},
"aggs": {
"p": {
"stats": {
"field": "p"
}
},
"kwh": {
"stats": {
"field": "kwh"
}
}
}
}
},
"sort": [
{
"quarter_time": {
"order": "asc"
}
}
]
}
async with EsUtil() as es:
es_re = await es.search_origin(body=query_body,
index="poweriot_company_15min_power")
return es_re["aggregations"]["quarter_time"]["buckets"]
async def query_search_kwh_p_new15(cid, start, end):
async def load_compy_power(cid, start, end):
start, _ = get_start_end_by_tz_time_new(start)
_, end = get_start_end_by_tz_time_new(end)
sql = f"""
......@@ -75,53 +11,11 @@ async def query_search_kwh_p_new15(cid, start, end):
order by create_time asc
"""
async with MysqlUtil() as conn:
datas = await conn.fetchall(sql=sql,
args=(cid, start, end))
datas = await conn.fetchall(sql=sql, args=(cid, start, end))
return datas
async def query_spfv_price(cid, start, end):
query_body = {
"query": {
"bool": {
"filter": [
{
"term": {
"cid": cid
}
},
{
"range": {
"quarter_time": {
"gte": convert_es_str(start),
"lte": convert_es_str(end)
}
}
}
]
}
},
"aggs": {
"charge": {
"stats": {
"field": "charge"
}
},
"kwh": {
"stats": {
"field": "kwh"
}
}
}
}
async with EsUtil() as es:
es_re = await es.search_origin(body=query_body,
index="poweriot_company_15min_power")
return es_re["aggregations"]["charge"]["avg"], es_re["aggregations"]["kwh"]["avg"]
async def query_spfv_price_new15(cid, start, end):
async def load_spfv_price(cid, start, end):
start, _ = get_start_end_by_tz_time_new(start)
_, end = get_start_end_by_tz_time_new(end)
sql = f"""
......
unify_api/modules/elec_charge/service/syncretize_energy_services.py
View file @ 984a952d
......@@ -7,10 +7,10 @@ import pandas as pd
from pot_libs.logger import log
from pot_libs.common.components.responses import success_res
from unify_api.modules.elec_charge.dao.syncretize_energy_es_dao import \
query_search_kwh_p_new15, query_spfv_price_new15
load_compy_power, load_spfv_price
from unify_api.modules.elec_charge.dao.syncretize_energy_dao import \
get_annual_sunshine_hours, get_p, insert_price_policy_data_dao, \
inset_algorithm_power_factor_dao, get_elec_price_dao,\
inset_algorithm_power_factor_dao, get_elec_price_dao, \
get_algorithm_power_factor_dao, get_max_demand_by_inlid
from unify_api.modules.elec_charge.components.syncretize_energy_cps import \
PvEvaluateComputeResp, Optimizecurve, ElectrovalenceResp, \
......@@ -33,7 +33,7 @@ async def pv_evaluate_service(cid, start, end):
start_list = start.split("-")
end_list = end.split("-")
pendulum_start = pendulum.date(int(start_list[0]),
int(start_list[1]), 1)
int(start_list[1]), 1)
pendulum_end = pendulum.date(int(end_list[0]), int(end_list[1]), 1)
day_num = pendulum_end.days_in_month
except:
......@@ -43,10 +43,9 @@ async def pv_evaluate_service(cid, start, end):
elif (pendulum_end - pendulum_start).in_months() > 12:
return success_res(code=4008, msg="日期最多选择12个月")
else:
# kwh_datas = await query_search_kwh_p_new15(cid, f"{start}-01",
# f"{end}-{day_num}", "1h")
p_datas = await query_search_kwh_p_new15(cid, f"{start}-01",
f"{end}-{day_num}")
p_datas = await load_compy_power(cid, f"{start}-01",
f"{end}-{day_num}")
if not p_datas:
return PvEvaluateTwoResp(kwh_slot=[], p_slot=[], p=[], kwh=[],
electrovalence={}, sum_kwh_p="",
......@@ -66,11 +65,10 @@ async def pv_evaluate_service(cid, start, end):
kwh_slots[flag].append(num)
num = data["kwh"]
flag = create_time[11:13]
# for data in p_datas:
# if data["p"]:
# p_slots[create_time[11:16]].append(data["p"])
for key, value in kwh_slots.items():
kwh_slots[key] = round(sum(value)/len(value), 2) if value else ""
kwh_slots[key] = round(sum(value) / len(value), 2) if value else ""
# 获取峰时段
elec_price = await get_elec_price_dao(cid)
if not elec_price:
......@@ -88,7 +86,8 @@ async def pv_evaluate_service(cid, start, end):
p_slot=[slot for slot in p_slots],
electrovalence=elecs,
sum_kwh_p=round(sum_kwh_p, 2),
p=[round(sum(p)/len(p), 2) if p else "" for p in p_slots.values()],
p=[round(sum(p) / len(p), 2) if p else "" for p in
p_slots.values()],
kwh=list(kwh_slots.values()))
......@@ -108,7 +107,8 @@ async def pv_evaluate_compute_service(download=None, url=None, **body):
total_capacity = float(body.get("install_space")) * \
float(body.get("area_conversion_ratio"))
# 工厂容量 =屋顶面积*折算系数*单位面积容量
invest_capacity = total_capacity * body.get("capacity_per_meter")/1000
invest_capacity = total_capacity * body.get(
"capacity_per_meter") / 1000
if not invest_capacity:
return success_res(code=4008, msg="场地面积/面积折算系数/单位面积容量不能为0")
except:
......@@ -136,9 +136,9 @@ async def pv_evaluate_compute_service(download=None, url=None, **body):
{"quarter_time": list(p_slots.keys()), "pv_curve": df_pv_curve},
columns=["quarter_time", "pv_curve"])
# 获取电量和负荷15分钟数据
datas = await query_search_kwh_p_new15(body.get("cid"),
f"{body.get('start')}-01",
f"{body.get('end')}-{day_num}")
datas = await load_compy_power(body.get("cid"),
f"{body.get('start')}-01",
f"{body.get('end')}-{day_num}")
if not datas:
return success_res(code=4008, msg="未找到数据")
for data in datas:
......@@ -146,21 +146,21 @@ async def pv_evaluate_compute_service(download=None, url=None, **body):
if data["p"]:
p_slots[create_time[11:19]].append(data["p"])
for index, value in p_slots.items():
p_slots[index] = sum(value)/len(value) if value else None
p_slots[index] = sum(value) / len(value) if value else None
# 负荷曲线df_load
df_load = pd.DataFrame(
{"quarter_time": list(p_slots.keys()),
"load_curve": list(p_slots.values())},
columns=["quarter_time", "load_curve"])
df_load = pd.DataFrame({"quarter_time": list(p_slots.keys()),
"load_curve": list(p_slots.values())},
columns=["quarter_time", "load_curve"])
# 获取这段时间平均价格
charge_price, kwh_price = await query_spfv_price_new15(body.get("cid"),
f"{body.get('start')}-01",
f"{body.get('end')}-{day_num}")
spfv_price = charge_price/kwh_price if charge_price and kwh_price else 0
charge_price, kwh_price = await load_spfv_price(body.get("cid"),
f"{body.get('start')}-01",
f"{body.get('end')}-{day_num}")
spfv_price = charge_price / kwh_price if charge_price and kwh_price else 0
pv_system = {
"user_type": "工商业", # 建筑类型
"install_space": body.get("install_space"), # 屋顶面积m2
"area_conversion_ratio": body.get("area_conversion_ratio"), # 面积折算系数
"area_conversion_ratio": body.get("area_conversion_ratio"),
# 面积折算系数
"capacity_per_meter": body.get("capacity_per_meter"), # 单位面积容量
"self_use_ratio": body.get("self_use_ratio"), # 自发自用比例
"efficiency": body.get("efficiency"), # 发电效率
......@@ -183,7 +183,9 @@ async def pv_evaluate_compute_service(download=None, url=None, **body):
obj = PvEvaluateTool(pv_system, price, invest_capacity, df_load, df_pv)
obj.output()
# 测算表
evaluate_table = (obj.evaluate_table.where(obj.evaluate_table.notnull(), None)).round(2)
evaluate_table = (
obj.evaluate_table.where(obj.evaluate_table.notnull(),
None)).round(2)
# 下载
if download:
company = await select_cname_by_cid(body.get("cid"))
......@@ -253,8 +255,8 @@ async def ess_evaluate_service(cid, start, end, work_day):
elec_list = [i for i in re.findall("p*", elec["quarters"]) if i]
rule = 2 if len(elec_list) > 1 else 1
p_datas = await query_search_kwh_p_new15(cid, f"{start}-01",
f"{end}-{day_num}")
p_datas = await load_compy_power(cid, f"{start}-01",
f"{end}-{day_num}")
if not p_datas:
return PvEvaluateTwoResp(kwh_slot=[], p_slot=[], p=[], kwh=[],
electrovalence={}, sum_kwh_p="",
......@@ -331,7 +333,8 @@ async def ess_evaluate_service(cid, start, end, work_day):
electrovalence=elecs,
sum_kwh_p=round(sum_kwh_p, 2),
sum_kwh_s=sum_kwh_s,
p=[round(sum(p)/len(p), 2) if p else "" for p in p_slots.values()],
p=[round(sum(p) / len(p), 2) if p else "" for p in
p_slots.values()],
kwh=list(kwh_slots.values()))
......@@ -377,9 +380,9 @@ async def ess_evaluate_compute_service(download=None, url=None, **body):
max_demand_pmax += demand[1]
max_demand_var = {"flag": max_demand_flag, "pmax": max_demand_pmax}
# 获取电量和负荷15分钟数据
datas = await query_search_kwh_p_new15(body.get("cid"),
f"{body.get('start')}-01",
f"{body.get('end')}-{day_num}")
datas = await load_compy_power(body.get("cid"),
f"{body.get('start')}-01",
f"{body.get('end')}-{day_num}")
if not datas:
return success_res(code=4008, msg="未找到数据")
p_slots = {"%02d:%02d:00" % (i, j): [] for i in range(24) for j in
......@@ -388,7 +391,8 @@ async def ess_evaluate_compute_service(download=None, url=None, **body):
# 1全部 2工作日 3非工作日
if body.get("work_day") == "2":
create_time = data["create_time"].strftime("%Y-%m-%d %H:%M:%S")
if ChineseCalendar(create_time[:10]).is_workday() and data["p"]:
if ChineseCalendar(create_time[:10]).is_workday() and data[
"p"]:
p_slots[create_time[11:19]].append(
data["p"])
elif body.get("work_day") == "3":
......@@ -400,7 +404,7 @@ async def ess_evaluate_compute_service(download=None, url=None, **body):
if data["p"]:
p_slots[create_time[11:19]].append(data["p"])
for index, value in p_slots.items():
p_slots[index] = sum(value)/len(value) if value else None
p_slots[index] = sum(value) / len(value) if value else None
# 负荷典型用电曲线 df_curve
df_curve = pd.DataFrame(
{"quarter_time": list(p_slots.keys()),
......@@ -409,11 +413,11 @@ async def ess_evaluate_compute_service(download=None, url=None, **body):
df_curve.loc[:, "quarter_time"] = pd.to_datetime(
df_curve.loc[:, "quarter_time"])
if elec_prices.get("price_s") and section_time_range.get("s"):
peak_valley_price = elec_prices["price_s"]-elec_prices["price_v"]
peak_flat_price = elec_prices["price_s"]-elec_prices["price_f"]
peak_valley_price = elec_prices["price_s"] - elec_prices["price_v"]
peak_flat_price = elec_prices["price_s"] - elec_prices["price_f"]
else:
peak_valley_price = elec_prices["price_p"]-elec_prices["price_v"]
peak_flat_price = elec_prices["price_p"]-elec_prices["price_f"]
peak_valley_price = elec_prices["price_p"] - elec_prices["price_v"]
peak_flat_price = elec_prices["price_p"] - elec_prices["price_f"]
log.info(f"cid:{body.get('cid')}, 峰谷价差:{peak_valley_price}, "
f"峰平价差:{peak_flat_price}")
price = {
......@@ -445,7 +449,8 @@ async def ess_evaluate_compute_service(download=None, url=None, **body):
"DOD": body.get("DOD"), # 放电深度
"decay_rate": body.get("decay_rate"), # 衰减率
# 年运维费用占静态投资额比例
"maintenance_ratio_per_year": body.get("maintenance_ratio_per_year"),
"maintenance_ratio_per_year": body.get(
"maintenance_ratio_per_year"),
"year_use_days": body.get("year_use_days"), # 一年可利用时间
"evaluate_year": evaluate_year, # 评估年限
"subsidy_year": body.get("subsidy_year"), # 补贴年限
......@@ -465,7 +470,8 @@ async def ess_evaluate_compute_service(download=None, url=None, **body):
table_name = f"{company['shortname']}_{body.get('start')}" \
f"_{body.get('end')}储能测算表"
return await dataframe_excl_download(evaluate_table, table_name)
curve = (obj.opt_curve.where(obj.opt_curve.notnull(), None)).round(2).reset_index()
curve = (obj.opt_curve.where(obj.opt_curve.notnull(), None)).round(
2).reset_index()
opt_curve = OptCurve(
slot=curve["quarter_time"].values.tolist(),
load_curve=curve["load_curve"].values.tolist(),
......@@ -512,7 +518,8 @@ async def electrovalence_setting_service(cid, price_md, price_tc, std_cos,
start = slot[0].split(":")
end = slot[1].split(":")
if int(end[0]) < int(start[0]) or \
(int(end[0]) == int(start[0]) and int(end[1]) <= int(start[1])):
(int(end[0]) == int(start[0]) and int(end[1]) <= int(
start[1])):
return success_res(code=400, msg="结束时间需要大于开始时间")
fina = int(end[0]) + 1 if end[1] != "00" else int(end[0])
for index, num in enumerate(range(int(start[0]), fina)):
......@@ -636,4 +643,4 @@ def get_section_time_slot(elecs):
end_h += 1
for i in range(start_h, end_h):
d[name].append("%02d:00" % i)
return d
\ No newline at end of file
return d
unify_api/modules/elec_charge/views/elec_statistics.py
View file @ 984a952d
......@@ -2,8 +2,7 @@ from unify_api.modules.elec_charge.common.utils import \
power_charge, max_min_time, power_charge_new15
from pot_libs.sanic_api import summary
from pot_libs.utils.pendulum_wrapper import my_pendulum
from unify_api.modules.common.procedures.pttl_max import pttl_max, \
pttl_max_new15
from unify_api.modules.common.procedures.pttl_max import load_pttl_max
from unify_api.modules.elec_charge.components.elec_statistics_cps import \
PcStatiReq, PcStatiResp, MaxpReq, MaxpResp, PcmResp
from unify_api.utils.common_utils import round_2
......@@ -31,7 +30,7 @@ async def post_max_p(req, body: MaxpReq) -> MaxpResp:
point_id = body.point_id
start = body.start
end = body.end
max_val, max_val_time = await pttl_max_new15(cid, start, end, point_id=point_id)
max_val, max_val_time = await load_pttl_max(cid, start, end, point_id=point_id)
return MaxpResp(maxp=max_val, date_time=max_val_time)
......@@ -121,7 +120,7 @@ async def power_charge_min_max_service_new15(cid, pid, start, end, date_type):
min_kwh = {"value": "", "time": ""}
max_charge = {"value": "", "time": ""}
min_charge = {"value": "", "time": ""}
max_val, max_val_time = await pttl_max_new15(cid, start, end, point_id=pid)
max_val, max_val_time = await load_pttl_max(cid, start, end, point_id=pid)
max_p["value"] = round_2(max_val)
max_p["time"] = max_val_time
# 2. 如果是日统计,则需要增加今日/昨日负荷曲线, 15min一个点
......
unify_api/modules/home_page/procedures/count_info_pds.py
View file @ 984a952d
......@@ -20,9 +20,7 @@ from unify_api.modules.common.dao.common_dao import monitor_point_join
from unify_api.modules.common.procedures.common_utils import get_electric_index
from unify_api.modules.common.procedures.points import proxy_points, \
get_points_num
from unify_api.modules.common.procedures.pttl_max import pttl_max, \
pttl_max_new15
from unify_api.modules.electric.views.electric import METERDATA_CURRENT_KEY
from unify_api.modules.common.procedures.pttl_max import load_pttl_max
from unify_api.modules.home_page.components.count_info_cps import (
MaxResidualCurrent,
ElectricInfo,
......@@ -308,7 +306,7 @@ async def power_count_info(cid):
start_time = (now - timedelta(30)).strftime("%Y-%m-%d 00:00:00")
end_time = now.strftime("%Y-%m-%d %H:%M:%S")
max_30d_load, _time = await pttl_max_new15(cid, start_time, end_time, -1)
max_30d_load, _time = await load_pttl_max(cid, start_time, end_time, -1)
cur_load = await real_time_load(cid)
return round_2(cur_load), round_2(max_30d_load)
......
unify_api/modules/load_analysis/views/load_distribution.py
View file @ 984a952d
......@@ -3,8 +3,7 @@ import re
from unify_api.utils.common_utils import round_2
from pot_libs.mysql_util import mysql_util
from pot_libs.sanic_api import summary
from unify_api.modules.common.procedures.pttl_max import pttl_max, \
pttl_max_15min, pttl_max_15min_new15
from unify_api.modules.common.procedures.pttl_max import load_pttl_max_15min
from unify_api.modules.load_analysis.components.load_distribution_cps import \
DistributionReq, DistributionResp, LrBins, MaxpResp
......@@ -53,11 +52,9 @@ async def post_load_distribution(req,
# 峰谷差
peak_valley = result["peak_valley"]
# 最高负荷
# max_val, max_val_time = await pttl_max_15min(cid=cid, start=start,
# end=end, inline_id=inline_id)
max_val, max_val_time = await pttl_max_15min_new15(cid=cid, start=start,
end=end,
inline_id=inline_id)
max_val, max_val_time = await load_pttl_max_15min(cid=cid, start=start,
end=end,
inline_id=inline_id)
max_p = MaxpResp(maxp=round_2(max_val), date_time=max_val_time)
return DistributionResp(base_load=base_load, mean_load_rate=mean_load_rate,
peak_valley=peak_valley, max_load=max_p,
......
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