Energy-Data.io is a REST API. Send a GET request. Get degree days back as JSON or CSV.
\nWhat it calculates: Heating Degree Days, Cooling Degree Days, or both - daily, monthly, or yearly, for any location, from 1970 to present.
\nWhat you need to start:
\nAn active Energy-Data.io account (energy-data.io/register)
\nYour email address - this is your API credential (user_id)
Your monthly call allowance - check it at energy-data.io/dashboard before running large queries
\nWhat are degree days?
\nA degree day measures how far the daily temperature fell from your base temperature. If it is 10°C outside and your base temperature is 18°C, that is 8 HDD for the day. Accumulate those over a month or year and you have a measure of how hard the building worked.
\nBase temperature defaults vary by region: 18°C in most of Europe, 15.5°C in the UK, 65°F in the USA.
\nEvery request requires your registered email address as the user_id parameter. This identifies your account and tracks usage against your monthly call allowance.
?user_id=your.email@example.com
Your email must match the address on your Energy-Data.io account exactly. No separate API key is required.
\nIf you receive a 401 Unauthorized response, check for typos or confirm your account is active
Each plan includes a monthly allowance of API calls. The number of calls a request consumes depends on the calculation method:
\nMean method: 1 call per request, regardless of date range
\nMin/max method: 1 call per request
\nIntegration method: 1 call per 15 days (a 365-day query uses 25 calls)
\nPlans and call limits:
\nAPI Essential: up to 6,500 calls
\nAPI Advanced: up to 25,000 calls
\nAPI Enterprise: up to 45,000 calls
\nEnterprise Plus: custom volume - contact us
\nNeed more calls mid-month? Purchase a one-off top-up or upgrade your plan from your account settings. If you exceed your allowance, requests return a 429 error until your limit resets.
Latitude coordinate of the location
\n","type":"text/plain"},"key":"lat","value":"53.55108"},{"description":{"content":"Longitude coordinate of the location
\n","type":"text/plain"},"key":"lon","value":"9.99368"},{"description":{"content":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both).
\n","type":"text/plain"},"key":"kind","value":"hdd"},{"description":{"content":"Required for hdd or cdd only. Multiple values allowed, e.g. ...&kind=hdd&base_temp=14&base_temp=15
\n","type":"text/plain"},"key":"base_temp","value":"15"},{"description":{"content":"Calculation method. Accepted values: integration, mean, minmax
\n","type":"text/plain"},"key":"method","value":"mean"},{"description":{"content":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit).
\n","type":"text/plain"},"key":"unit","value":"metric"},{"description":{"content":"Start date in YYYY-MM-DD format.
\n","type":"text/plain"},"key":"start","value":"2025-01-01"},{"description":{"content":"End date in YYYY-MM-DD format (or use \"today\" for the current date).
\n","type":"text/plain"},"key":"end","value":"2025-01-02"},{"description":{"content":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly.
\n","type":"text/plain"},"key":"breakdown","value":"daily"},{"description":{"content":"[optional] Output format of the response. Accepts csv or json. Defaults to json.
\n","type":"text/plain"},"key":"format","value":"JSON"},{"description":{"content":"API key provided to the user
\n","type":"text/plain"},"key":"key","value":"{YOUR API KEY}"}],"variable":[]}},"response":[{"id":"a11a26a1-4c4d-40db-9ece-550c717f1931","name":"Get Degree Days","originalRequest":{"method":"GET","header":[],"url":{"raw":"https://api.energy-data.io/v2/?lat=53.55108&lon=9.99368&unit=metric&kind=hdd&base_temp=15&method=mean&start=2025-01-01&end=2025-01-31&breakdown=monthly&format=JSON&key={YOUR API KEY}","protocol":"https","host":["api","energy-data","io"],"path":["v2",""],"query":[{"key":"lat","value":"53.55108","description":"Latitude coordinate of the location"},{"key":"lon","value":"9.99368","description":"Longitude coordinate of the location"},{"key":"unit","value":"metric","description":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit)."},{"key":"kind","value":"hdd","description":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both)."},{"key":"base_temp","value":"15","description":"Required for hdd or cdd only. Multiple values allowed, e.g. ...&kind=hdd&base_temp=14&base_temp=15"},{"key":"method","value":"mean","description":"Calculation method. Accepted values: integration, mean, minmax"},{"key":"start","value":"2025-01-01","description":"Start date in YYYY-MM-DD format."},{"key":"end","value":"2025-01-31","description":"End date in YYYY-MM-DD format (or use \"today\" for the current date)."},{"key":"breakdown","value":"monthly","description":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly."},{"key":"format","value":"JSON","description":"[optional] Output format of the response. Accepts csv or json. Defaults to json."},{"key":"key","value":"{YOUR API KEY}","description":"API key provided to the user"}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[{"key":"Server","value":"nginx/1.24.0 (Ubuntu)"},{"key":"Date","value":"Tue, 04 Mar 2025 05:03:34 GMT"},{"key":"Content-Type","value":"application/json"},{"key":"Content-Length","value":"3829"},{"key":"Connection","value":"keep-alive"},{"key":"Access-Control-Allow-Methods","value":"GET, POST, PUT, DELETE, OPTIONS"},{"key":"Access-Control-Allow-Headers","value":"Authorization, Content-Type, Accept"}],"cookie":[],"responseTime":null,"body":"{\n \"Type_of_Degree_Days\": \"Heating Degree Days\",\n \"Calculation_Method\": \"Daily Mean Temperature Method\",\n \"Base_temperature\": \"15\",\n \"Unit\": \"Celsius\",\n \"Coordinates\": {\n \"latitude\": \"53.55108\",\n \"longitude\": \"9.99368\"\n },\n \"Source\": \"https://energy-data.io/\",\n \"Degree_Days_Data\": [\n {\n \"date\": \"2025-01-01\",\n \"hdd\": 8\n },\n {\n \"date\": \"2025-01-02\",\n \"hdd\": 12.3\n }\n ],\n \"stations\": {\n \"EDHI\": {\n \"distance\": 11079,\n \"latitude\": 53.53,\n \"longitude\": 9.83,\n \"useCount\": 0,\n \"id\": \"EDHI\",\n \"name\": \"EDHI\",\n \"quality\": 50,\n },\n \"EDDH\": {\n \"distance\": 8795,\n \"latitude\": 53.63,\n \"longitude\": 10,\n \"useCount\": 0,\n \"id\": \"EDDH\",\n \"name\": \"EDDH\",\n \"quality\": 50\n },\n \"01981\": {\n \"distance\": 10430,\n \"latitude\": 53.478,\n \"longitude\": 9.896,\n \"useCount\": 0,\n \"id\": \"01981\",\n \"name\": \"Hamburg-Neuwiedenthal\",\n \"quality\": 100\n },\n \"00760\": {\n \"distance\": 21211,\n \"latitude\": 53.363,\n \"longitude\": 9.944,\n \"useCount\": 0,\n \"id\": \"00760\",\n \"name\": \"Rosengarten-Klecken\",\n \"quality\": 100\n },\n \"04857\": {\n \"distance\": 25395,\n \"latitude\": 53.553,\n \"longitude\": 9.61,\n \"useCount\": 0,\n \"id\": \"04857\",\n \"name\": \"Mittelnkirchen-Hohenfelde\",\n \"quality\": 99\n },\n \"10149099999\": {\n \"distance\": 10500,\n \"latitude\": 53.536,\n \"longitude\": 9.837,\n \"useCount\": 0,\n \"id\": \"10149099999\",\n \"name\": \"HAMBURG FINKENWERDER, GM\",\n \"quality\": 49\n },\n \"01975\": {\n \"distance\": 9149,\n \"latitude\": 53.633,\n \"longitude\": 9.988,\n \"useCount\": 0,\n \"id\": \"01975\",\n \"name\": \"Hamburg-Fuhlsbüttel\",\n \"quality\": 100\n }\n }\n}"}],"_postman_id":"a052f7d6-0ecb-48ff-9e05-4205fc48d1b0"},{"name":"Get Degree Days by Post Code","id":"d60bce6a-fa7b-4bd2-9948-0fb3f58095c5","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"https://api.energy-data.io/v2/?country=DE&zip=10115&kind=hdd&base_temp=15&unit=metric&method=mean&start=2025-01-01&end=2025-01-02&breakdown=daily&format=JSON&key={YOUR API KEY}","urlObject":{"protocol":"https","path":["v2",""],"host":["api","energy-data","io"],"query":[{"description":{"content":"ISO country code: DE, NL, GB, or UK
\n","type":"text/plain"},"key":"country","value":"DE"},{"description":{"content":"Postal/ZIP code
\n","type":"text/plain"},"key":"zip","value":"10115"},{"description":{"content":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both).
\n","type":"text/plain"},"key":"kind","value":"hdd"},{"description":{"content":"Required for hdd or cdd only. Multiple values allowed, e.g. ...&kind=hdd&base_temp=14&base_temp=15
\n","type":"text/plain"},"key":"base_temp","value":"15"},{"description":{"content":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit).
\n","type":"text/plain"},"key":"unit","value":"metric"},{"description":{"content":"Calculation method. Accepted values: integration, mean, minmax
\n","type":"text/plain"},"key":"method","value":"mean"},{"description":{"content":"Start date in YYYY-MM-DD format.
\n","type":"text/plain"},"key":"start","value":"2025-01-01"},{"description":{"content":"End date in YYYY-MM-DD format (or use \"today\" for the current date).
\n","type":"text/plain"},"key":"end","value":"2025-01-02"},{"description":{"content":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly.
\n","type":"text/plain"},"key":"breakdown","value":"daily"},{"description":{"content":"[optional] Output format of the response. Accepts csv or json. Defaults to json.
\n","type":"text/plain"},"key":"format","value":"JSON"},{"description":{"content":"API key provided to the user
\n","type":"text/plain"},"key":"key","value":"{YOUR API KEY}"}],"variable":[]}},"response":[],"_postman_id":"d60bce6a-fa7b-4bd2-9948-0fb3f58095c5"},{"name":"Get Degree Days For Multiple Base Temperatures","id":"5ebf0391-b174-441b-b36d-d50575a4f78b","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"https://api.energy-data.io/v2/?lat=-20.268868&lon=57.376972&unit=metric&kind=cdd&base_temp=19&base_temp=21&base_temp=23&method=mean&start=2025-01-01&end=2025-01-02&breakdown=daily&format=JSON&key={YOUR API KEY}","urlObject":{"protocol":"https","path":["v2",""],"host":["api","energy-data","io"],"query":[{"description":{"content":"Latitude coordinate of the location
\n","type":"text/plain"},"key":"lat","value":"-20.268868"},{"description":{"content":"Longitude coordinate of the location
\n","type":"text/plain"},"key":"lon","value":"57.376972"},{"description":{"content":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit).
\n","type":"text/plain"},"key":"unit","value":"metric"},{"description":{"content":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both).
\n","type":"text/plain"},"key":"kind","value":"cdd"},{"description":{"content":"Required for hdd or cdd only. Multiple values allowed, e.g. ...&kind=hdd&base_temp=14&base_temp=15
\n","type":"text/plain"},"key":"base_temp","value":"19"},{"key":"base_temp","value":"21"},{"key":"base_temp","value":"23"},{"description":{"content":"Calculation method. Accepted values: integration, mean, minmax
\n","type":"text/plain"},"key":"method","value":"mean"},{"description":{"content":"Start date in YYYY-MM-DD format.
\n","type":"text/plain"},"key":"start","value":"2025-01-01"},{"description":{"content":"End date in YYYY-MM-DD format (or use \"today\" for the current date).
\n","type":"text/plain"},"key":"end","value":"2025-01-02"},{"description":{"content":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly.
\n","type":"text/plain"},"key":"breakdown","value":"daily"},{"description":{"content":"[optional] Output format of the response. Accepts csv or json. Defaults to json.
\n","type":"text/plain"},"key":"format","value":"JSON"},{"description":{"content":"API key provided to the user
\n","type":"text/plain"},"key":"key","value":"{YOUR API KEY}"}],"variable":[]}},"response":[{"id":"69155383-3406-473b-a8a3-af29ca4219ff","name":"200 OK Response","originalRequest":{"method":"GET","header":[],"url":{"raw":"https://api.energy-data.io/v2/?lat=-20.268868&lon=57.376972&unit=metric&kind=cdd&base_temp=19&base_temp=21&base_temp=23&method=mean&start=2025-01-01&end=2025-01-02&breakdown=daily&format=JSON&key={YOUR API KEY}","protocol":"https","host":["api","energy-data","io"],"path":["v2",""],"query":[{"key":"lat","value":"-20.268868","description":"Latitude coordinate of the location"},{"key":"lon","value":"57.376972","description":"Longitude coordinate of the location"},{"key":"unit","value":"metric","description":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit)."},{"key":"kind","value":"cdd","description":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both)."},{"key":"base_temp","value":"19","description":"Required for hdd or cdd only. Multiple values allowed, e.g. ...&kind=hdd&base_temp=14&base_temp=15"},{"key":"base_temp","value":"21"},{"key":"base_temp","value":"23"},{"key":"method","value":"mean","description":"Calculation method. Accepted values: integration, mean, minmax"},{"key":"start","value":"2025-01-01","description":"Start date in YYYY-MM-DD format."},{"key":"end","value":"2025-01-02","description":"End date in YYYY-MM-DD format (or use \"today\" for the current date)."},{"key":"breakdown","value":"daily","description":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly."},{"key":"format","value":"JSON","description":"[optional] Output format of the response. Accepts csv or json. Defaults to json."},{"key":"key","value":"{YOUR API KEY}","description":"API key provided to the user"}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[{"key":"Server","value":"nginx/1.24.0 (Ubuntu)"},{"key":"Date","value":"Tue, 04 Mar 2025 05:07:52 GMT"},{"key":"Content-Type","value":"application/json"},{"key":"Content-Length","value":"1566"},{"key":"Connection","value":"keep-alive"},{"key":"Access-Control-Allow-Methods","value":"GET, POST, PUT, DELETE, OPTIONS"},{"key":"Access-Control-Allow-Headers","value":"Authorization, Content-Type, Accept"}],"cookie":[],"responseTime":null,"body":"{\n \"Type_of_Degree_Days\": \"Cooling Degree Days\",\n \"Calculation_Method\": \"Daily Mean Temperature Method\",\n \"baseTemperature\": [\n \"19\",\n \"21\",\n \"23\"\n ],\n \"Unit\": \"Celsius\",\n \"Coordinates\": {\n \"latitude\": \"-20.268868\",\n \"longitude\": \"57.376972\"\n },\n \"Source\": \"https://energy-data.io/\",\n \"Degree_Days_Data\": [\n {\n \"date\": \"2025-01-01\",\n \"cdd(19)\": 7.5,\n \"cdd(21)\": 5.5,\n \"cdd(23)\": 3.5\n },\n {\n \"date\": \"2025-01-02\",\n \"cdd(19)\": 7.2,\n \"cdd(21)\": 5.2,\n \"cdd(23)\": 3.2\n }\n ],\n \"stations\": {\n \"61990099999\": {\n \"distance\": 36698,\n \"latitude\": -20.43,\n \"longitude\": 57.684,\n \"useCount\": 0,\n \"id\": \"61990099999\",\n \"name\": \"SIR SEEWOOSAGUR RAMGOOLAM INTERNATIONAL, MP\",\n \"quality\": 99\n },\n \"61995099999\": {\n \"distance\": 9989,\n \"latitude\": -20.3,\n \"longitude\": 57.467,\n \"useCount\": 0,\n \"id\": \"61995099999\",\n \"name\": \"VACOAS MAURITIUS, MP\",\n \"quality\": 64\n }\n }\n}"}],"_postman_id":"5ebf0391-b174-441b-b36d-d50575a4f78b"},{"name":"Get Heating and Cooling Degree Days","id":"085f3635-d895-4225-9ee7-c1ce74423a13","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"https://api.energy-data.io/v2/?lat=40.712776&lon=-74.005974&kind=bth&unit=imperial&base_temp_cdd=75&base_temp_hdd=60&method=mean&start=2024-01-01&end=2024-12-31&breakdown=monthly&format=JSON&key={YOUR API KEY}","description":"bth (Both Heating and Cooling Degree Days)Parameters: base_temp_hdd and base_temp_cdd
Description:
\nWhen kind is set to bth, the API expects two dedicated base temperature parameters.
base_temp_hdd: Base temperature used for heating degree days calculations.
base_temp_cdd: Base temperature used for cooling degree days calculations.
...&kind=bth&base_temp_hdd=18&base_temp_cdd=22
When using these parameters, ensure that:
\nFor hdd or cdd, if you provide multiple values via the base_temp parameter, all values will be considered.
For bth, both base_temp_hdd and base_temp_cdd must be provided. If the optional generic parameter base_temp is used in this scenario, only the first value will be applied to both heating and cooling calculations.
This flexibility in specifying base temperatures allows you to compare calculations based on different thresholds or to compute distinct values for heating and cooling when needed.
\n","urlObject":{"protocol":"https","path":["v2",""],"host":["api","energy-data","io"],"query":[{"description":{"content":"Latitude coordinate of the location
\n","type":"text/plain"},"key":"lat","value":"40.712776"},{"description":{"content":"Longitude coordinate of the location
\n","type":"text/plain"},"key":"lon","value":"-74.005974"},{"description":{"content":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both).
\n","type":"text/plain"},"key":"kind","value":"bth"},{"description":{"content":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit).
\n","type":"text/plain"},"key":"unit","value":"imperial"},{"description":{"content":"Required for bth only
\n","type":"text/plain"},"key":"base_temp_cdd","value":"75"},{"description":{"content":"Required for bth only
\n","type":"text/plain"},"key":"base_temp_hdd","value":"60"},{"description":{"content":"Calculation method. Accepted values: integration, mean, minmax
\n","type":"text/plain"},"key":"method","value":"mean"},{"description":{"content":"Start date in YYYY-MM-DD format
\n","type":"text/plain"},"key":"start","value":"2024-01-01"},{"description":{"content":"End date in YYYY-MM-DD format (or use \"today\" for the current date)
\n","type":"text/plain"},"key":"end","value":"2024-12-31"},{"description":{"content":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly.
\n","type":"text/plain"},"key":"breakdown","value":"monthly"},{"description":{"content":"[optional] Output format of the response. Accepts csv or json. Defaults to json.
\n","type":"text/plain"},"key":"format","value":"JSON"},{"description":{"content":"API key provided to the user
\n","type":"text/plain"},"key":"key","value":"{YOUR API KEY}"}],"variable":[]}},"response":[{"id":"cd076a6c-9350-4993-a696-b006ec2389d2","name":"Get Heating and Cooling Degree Days","originalRequest":{"method":"GET","header":[],"url":{"raw":"https://api.energy-data.io/v2/?lat=40.712776&lon=-74.005974&kind=bth&unit=imperial&base_temp_cdd=75&base_temp_hdd=60&method=mean&start=2024-01-01&end=2024-12-31&breakdown=monthly&format=JSON&key={Your API Key}","protocol":"https","host":["api","energy-data","io"],"path":["v2",""],"query":[{"key":"lat","value":"40.712776","description":"Latitude coordinate of the location"},{"key":"lon","value":"-74.005974","description":"Longitude coordinate of the location"},{"key":"kind","value":"bth","description":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both)."},{"key":"unit","value":"imperial","description":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit)."},{"key":"base_temp_cdd","value":"75","description":"Required for bth only"},{"key":"base_temp_hdd","value":"60","description":"Required for bth only"},{"key":"method","value":"mean","description":"Calculation method. Accepted values: integration, mean, minmax"},{"key":"start","value":"2024-01-01","description":"Start date in YYYY-MM-DD format"},{"key":"end","value":"2024-12-31","description":"End date in YYYY-MM-DD format (or use \"today\" for the current date)"},{"key":"breakdown","value":"monthly","description":"[optional] Frequency of data aggregation. Accepts daily, monthly, or yearly. Defaults to monthly."},{"key":"format","value":"JSON","description":"[optional] Output format of the response. Accepts csv or json. Defaults to json."},{"key":"key","value":"{Your API Key}","description":"API key provided to the user"}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[{"key":"Server","value":"nginx/1.24.0 (Ubuntu)"},{"key":"Date","value":"Tue, 04 Mar 2025 06:21:18 GMT"},{"key":"Content-Type","value":"application/json"},{"key":"Content-Length","value":"3993"},{"key":"Connection","value":"keep-alive"},{"key":"Access-Control-Allow-Methods","value":"GET, POST, PUT, DELETE, OPTIONS"},{"key":"Access-Control-Allow-Headers","value":"Authorization, Content-Type, Accept"}],"cookie":[],"responseTime":null,"body":"{\n \"Type_of_Degree_Days\": \"Heating and Cooling Degree Days\",\n \"Calculation_Method\": \"Daily Mean Temperature Method\",\n \"Base_temperature_heating\": [\n \"60\"\n ],\n \"Base_temperature_cooling\": [\n \"75\"\n ],\n \"Unit\": \"Fahrenheit\",\n \"Coordinates\": {\n \"latitude\": \"40.712776\",\n \"longitude\": \"-74.005974\"\n },\n \"Source\": \"https://energy-data.io/\",\n \"Degree_Days_Data\": [\n {\n \"date\": \"2024-01\",\n \"hdd(60)\": 711.2,\n \"cdd(75)\": 0\n },\n {\n \"date\": \"2024-02\",\n \"hdd(60)\": 586.3,\n \"cdd(75)\": 0\n },\n {\n \"date\": \"2024-03\",\n \"hdd(60)\": 393.1,\n \"cdd(75)\": 0\n },\n {\n \"date\": \"2024-04\",\n \"hdd(60)\": 204.7,\n \"cdd(75)\": 0\n },\n {\n \"date\": \"2024-05\",\n \"hdd(60)\": 43,\n \"cdd(75)\": 1.7\n },\n {\n \"date\": \"2024-06\",\n \"hdd(60)\": 0,\n \"cdd(75)\": 58.8\n },\n {\n \"date\": \"2024-07\",\n \"hdd(60)\": 0,\n \"cdd(75)\": 135.6\n },\n {\n \"date\": \"2024-08\",\n \"hdd(60)\": 0,\n \"cdd(75)\": 62.5\n },\n {\n \"date\": \"2024-09\",\n \"hdd(60)\": 0,\n \"cdd(75)\": 1.9\n },\n {\n \"date\": \"2024-10\",\n \"hdd(60)\": 62.7,\n \"cdd(75)\": 0\n },\n {\n \"date\": \"2024-11\",\n \"hdd(60)\": 273.3,\n \"cdd(75)\": 0\n },\n {\n \"date\": \"2024-12\",\n \"hdd(60)\": 666,\n \"cdd(75)\": 0\n }\n ],\n \"stations\": {\n \"72505394728\": {\n \"distance\": 7995,\n \"latitude\": 40.779,\n \"longitude\": -73.969,\n \"useCount\": 0,\n \"id\": \"72505394728\",\n \"name\": \"NY CITY CENTRAL PARK, NY US\",\n \"quality\": 100\n },\n \"KEWR\": {\n \"distance\": 13915,\n \"latitude\": 40.7,\n \"longitude\": -74.17,\n \"useCount\": 0,\n \"id\": \"KEWR\",\n \"name\": \"KEWR\",\n \"quality\": 100\n },\n \"KLGA\": {\n \"distance\": 10976,\n \"latitude\": 40.77,\n \"longitude\": -73.9,\n \"useCount\": 0,\n \"id\": \"KLGA\",\n \"name\": \"KLGA\",\n \"quality\": 100\n },\n \"72502014734\": {\n \"distance\": 14199,\n \"latitude\": 40.683,\n \"longitude\": -74.169,\n \"useCount\": 0,\n \"id\": \"72502014734\",\n \"name\": \"NEWARK LIBERTY INTERNATIONAL AIRPORT, NJ US\",\n \"quality\": 100\n },\n \"F8726\": {\n \"distance\": 5089,\n \"latitude\": 40.671,\n \"longitude\": -73.981,\n \"useCount\": 0,\n \"id\": \"F8726\",\n \"name\": \"FW8726 Brooklyn NY US\",\n \"quality\": 0\n },\n \"KNYC\": {\n \"distance\": 6736,\n \"latitude\": 40.77,\n \"longitude\": -73.98,\n \"useCount\": 0,\n \"id\": \"KNYC\",\n \"name\": \"KNYC\",\n \"quality\": 100\n },\n \"72503014732\": {\n \"distance\": 12936,\n \"latitude\": 40.779,\n \"longitude\": -73.88,\n \"useCount\": 0,\n \"id\": \"72503014732\",\n \"name\": \"LAGUARDIA AIRPORT, NY US\",\n \"quality\": 100\n }\n }\n}"}],"_postman_id":"085f3635-d895-4225-9ee7-c1ce74423a13"}],"id":"4655fb92-0c48-462c-aaf6-94e9703aa0c3","description":"Calculate heating degree days (HDD), cooling degree days (CDD), or both for any location.
\nThis endpoint returns degree days data based on the provided coordinates, date range, and calculation method. It supports both JSON and CSV formats and handles aggregation by daily, monthly, or yearly breakdowns.
\nGET /v2/\n\nChoose one of two methods to specify location:
\nFor locations worldwide:
\nnotionvc: 41749c12-b427-4cbe-8572-54dcf2f10fea EndFragment
\nPerfect for addresses in Germany, Netherlands, or United Kingdom:
\nSupported Countries:
\n🇩🇪 Germany (DE) - All German ZIP codes
\n🇳🇱 Netherlands (NL) - All Dutch postal codes
\n🇬🇧 United Kingdom (GB or UK) - All UK postcodes
\nZIP Code Formats:
\nGermany: 5 digits (e.g., 10115, 01067)
Netherlands: 4 digits + 2 letters, with or without space (e.g., 1012AB or 1012 AB)
UK: Variable format, with or without space (e.g., SW1A1AA or SW1A 1AA)
💡 Tip: Spaces in UK/NL postcodes are automatically handled - use either format!
\nDate Rules:
\nFormat must be YYYY-MM-DD
Historical data from 1970 onwards
\nMaximum range: 3 years (1 year recommended per request)
\nhdd - Heating Degree Days
Measures heating energy needed
\nUse for winter/cold climate analysis
\ncdd - Cooling Degree Days
Measures cooling energy needed
\nUse for summer/warm climate analysis
\nbth - Both
Calculate HDD and CDD in one request
\nRequires both base_temp_hdd and base_temp_cdd
mean ⭐ Recommended
Uses daily average temperature
\n1 API call per request (regardless of date range)
\nFast and accurate for most use cases
\nFormula: DD = max(0, base_temp - daily_avg_temp)
integration 🎯 Most Accurate
Uses hourly temperature data
\n1 API call per 15 days (rounded up)
\nExample: 31 days = 3 API calls, 365 days = 25 API calls
\nBest for critical calculations
\nminmax
Uses daily min/max temperatures
\n1 API call per request
\nGood balance between accuracy and cost
\nThe temperature threshold for your calculation:
\nCommon Values (Metric):
\nHeating: 15, 18, 20 (°C)
Cooling: 18, 21, 24 (°C)
Common Values (Imperial):
\nHeating: 59, 65, 68 (°F)
Cooling: 65, 70, 75 (°F)
💡 Multiple Base Temperatures:
You can request multiple base temperatures in one API call:
base_temp=15&base_temp=18&base_temp=20\n\nThis returns three columns: hdd(15.0), hdd(18.0), hdd(20.0)
metric - Celsius (°C) and meters
imperial - Fahrenheit (°F) and miles
daily - One row per day (default)
monthly - One row per month
yearly - One row per year
json - JSON response (default)
csv - CSV file download
notionvc: d4ab6cb3-8719-4c6c-b54d-42fbcfd7381e EndFragment
\n","_postman_id":"4655fb92-0c48-462c-aaf6-94e9703aa0c3"},{"name":"Manage Datasets/ Projects","item":[{"name":"Upload a Raw Dataset (Usage Only)","id":"a6eee950-a32c-4997-9ff1-1cee241957fb","protocolProfileBehavior":{"disableBodyPruning":true,"disabledSystemHeaders":{"accept":true,"user-agent":true,"accept-encoding":true,"connection":true}},"request":{"method":"POST","header":[],"body":{"mode":"raw","raw":"{\r\n \"metadata\": {\r\n \"project_name\": \"Example\",\r\n \"parameters\": {\r\n \"usage_unit\": \"kWh\"\r\n }\r\n },\r\n \"usage_data\": [\r\n {\r\n \"period_id\": \"1\",\r\n \"begin_period\": \"2025-01-01\",\r\n \"end_period\": \"2025-01-01\",\r\n \"usage\": 123\r\n },\r\n {\r\n \"period_id\": \"2\",\r\n \"begin_period\": \"2025-01-02\",\r\n \"end_period\": \"2025-01-02\",\r\n \"usage\": 456\r\n },\r\n {\r\n \"period_id\": \"3\",\r\n \"begin_period\": \"2025-01-03\",\r\n \"end_period\": \"2025-01-03\",\r\n \"usage\": 234\r\n },\r\n {\r\n \"period_id\": \"4\",\r\n \"begin_period\": \"2025-01-04\",\r\n \"end_period\": \"2025-01-04\",\r\n \"usage\": 345\r\n },\r\n {\r\n \"period_id\": \"5\",\r\n \"begin_period\": \"2025-01-05\",\r\n \"end_period\": \"2025-01-05\",\r\n \"usage\": 678\r\n },\r\n {\r\n \"period_id\": \"6\",\r\n \"begin_period\": \"2025-01-06\",\r\n \"end_period\": \"2025-01-06\",\r\n \"usage\": 567\r\n },\r\n {\r\n \"period_id\": \"7\",\r\n \"begin_period\": \"2025-01-07\",\r\n \"end_period\": \"2025-01-07\",\r\n \"usage\": 345\r\n },\r\n {\r\n \"period_id\": \"8\",\r\n \"begin_period\": \"2025-01-08\",\r\n \"end_period\": \"2025-01-08\",\r\n \"usage\": 789\r\n },\r\n {\r\n \"period_id\": \"9\",\r\n \"begin_period\": \"2025-01-09\",\r\n \"end_period\": \"2025-01-09\",\r\n \"usage\": 654\r\n },\r\n {\r\n \"period_id\": \"10\",\r\n \"begin_period\": \"2025-01-10\",\r\n \"end_period\": \"2025-01-10\",\r\n \"usage\": 432\r\n }\r\n ]\r\n}","options":{"raw":{"language":"json"}}},"url":"https://data.energy-data.io/api/upload/rawdata?key={Your API Key}","description":"Generated from cURL: curl -X POST http://:5000/api/upload/rawdata
-H \"Content-Type: application/json\"
-d '{\n \"dataset_id\": \"dataset001\",\n \"user_id\": \"user123\"\n }'
Generated from cURL: curl --location --request PUT 'https://data.energy-data.io/api/update_dataset/6fef5383-59ec-4ebe-9896-0c82d2d8b4bf?key=degree-calculator-members'
--header 'Content-Type: application/json'
--data-raw '{\n \"metadata\": {\n \"project_name\": \"New Project Name\",\n \"parameters\": {\n \"unit\": \"kWh\",\n \"predictors\": [\n {\"name\": \"temp\", \"constraint\": \"c+\"}\n ]\n }\n },\n \"usage_data\": [\n {\n \"period_id\": \"1\",\n \"begin_period\": \"2025-01-01\",\n \"end_period\": \"2025-01-02\",\n \"usage\": 10.5\n },\n {\n \"period_id\": \"2\",\n \"begin_period\": \"2025-01-02\",\n \"end_period\": \"2025-01-03\",\n \"usage\": 9.2\n }\n ]\n}'
BaseURLhttps://data.energy-data.io
Endpoint: POST /api/upload/
Description: Upload a dataset (rawdata, normalization, or regression).
Query Parameters:
\ndataset_id (required): Unique ID for the dataset.
user_id (required): ID of the user uploading the dataset.
raw_dataset_id (required for normalization and regression): ID of the raw dataset this dataset depends on.
Body: JSON containing the dataset contents.
\nResponse:
\n200 OK: Dataset uploaded successfully.
400 Bad Request: Missing parameters or invalid JSON.
500 Internal Server Error: File save failure.
Endpoint: GET /api/datasets/
Description: Retrieve all datasets for a user, grouped by raw_dataset_id and their dependencies (normalization and regression).
Path Parameter:
\nuser_id (required): ID of the user.Endpoint: DELETE /api/delete_dataset
Description: Delete a specific dataset by user_id and dataset_id.
Query Parameters:
\ndataset_id (required): ID of the dataset to delete.
user_id (required): ID of the user.
Response:
\n200 OK: Dataset successfully deleted.
404 Not Found: Dataset not found.
500 Internal Server Error: File deletion failure.
Latitude coordinate of the location
\n","type":"text/plain"},"key":"lat","value":"60.1927487436804"},{"description":{"content":"Longitude coordinate of the location
\n","type":"text/plain"},"key":"lon","value":"11.0695615332356"},{"description":{"content":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit)
\n","type":"text/plain"},"key":"unit","value":"metric"},{"description":{"content":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both)
\n","type":"text/plain"},"key":"kind","value":"hdd"},{"description":{"content":"Required for hdd or cdd only.
\n","type":"text/plain"},"key":"base_temp","value":"15"},{"disabled":true,"description":{"content":"Required for bth only
\n","type":"text/plain"},"key":"base_temp_cdd","value":"22"},{"disabled":true,"description":{"content":"Required for bth only
\n","type":"text/plain"},"key":"base_temp_hdd","value":"15"},{"disabled":true,"description":{"content":"The constant baseload (representing non-weather-related energy usage)
\n","type":"text/plain"},"key":"baseload","value":"3000"},{"disabled":true,"key":"hdd_coefficient","value":"1.1"},{"disabled":true,"key":"cdd_coefficient","value":"1.5"},{"key":"dataset_id","value":"36a6aa8f-aa4c-4d84-aaf9-3e9cd574143c"},{"description":{"content":"API key provided to the user
\n","type":"text/plain"},"key":"key","value":"{Your API Key}"},{"disabled":true,"description":{"content":"[optional] Calculation method. Accepted values: integration, mean, minmax. Default \"mean\"
\n","type":"text/plain"},"key":"method","value":"mean"}],"variable":[]}},"response":[{"id":"e0de15ee-f45c-4939-bde5-f311e83f24e5","name":"200 OK","originalRequest":{"method":"GET","header":[],"url":{"raw":"https://api.energy-data.io/normalize/?lat=60.1927487436804&lon=11.0695615332356&unit=metric&kind=hdd&base_temp=15&dataset_id=36a6aa8f-aa4c-4d84-aaf9-3e9cd574143c&key={Your API Key}","protocol":"https","host":["api","energy-data","io"],"path":["normalize",""],"query":[{"key":"lat","value":"60.1927487436804","description":"Latitude coordinate of the location"},{"key":"lon","value":"11.0695615332356","description":"Longitude coordinate of the location"},{"key":"unit","value":"metric","description":"Unit system. Accepted values: metric (Celsius) or imperial (Fahrenheit)"},{"key":"kind","value":"hdd","description":"Type of degree days to calculate. Accepts hdd (Heating), cdd (Cooling), or bth (Both)"},{"key":"base_temp","value":"15","description":"Required for hdd or cdd only."},{"key":"base_temp_cdd","value":"22","description":"Required for bth only","disabled":true},{"key":"base_temp_hdd","value":"15","description":"Required for bth only","disabled":true},{"key":"baseload","value":"3000","description":"The constant baseload (representing non-weather-related energy usage)","disabled":true},{"key":"hdd_coefficient","value":"1.1","disabled":true},{"key":"cdd_coefficient","value":"1.5","disabled":true},{"key":"dataset_id","value":"36a6aa8f-aa4c-4d84-aaf9-3e9cd574143c","description":"Calculation method. Accepted values: integration, mean, minmax"},{"key":"key","value":"{Your API Key}","description":"API key provided to the user"},{"key":"method","value":"mean","description":"optional","disabled":true}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[{"key":"Server","value":"nginx/1.24.0 (Ubuntu)"},{"key":"Date","value":"Fri, 07 Mar 2025 06:35:09 GMT"},{"key":"Content-Type","value":"application/json"},{"key":"Content-Length","value":"20813"},{"key":"Connection","value":"keep-alive"},{"key":"Access-Control-Allow-Methods","value":"GET, POST, PUT, DELETE, OPTIONS"},{"key":"Access-Control-Allow-Headers","value":"Authorization, Content-Type, Accept"}],"cookie":[],"responseTime":null,"body":"{\n \"message\": \"Data fetched and normalized successfully.\",\n \"metadata\": {\n \"api_version\": \"2.0\",\n \"dataset_id\": \"norm-36a6aa8f-aa4c-4d84-aaf9-3e9cd574143c-hc9fc\",\n \"raw_dataset_id\": \"36a6aa8f-aa4c-4d84-aaf9-3e9cd74143c\",\n \"start_date\": \"2023-01-01\",\n \"end_date\": \"2024-12-31\",\n \"total_periods\": 24,\n \"total_degree_days\": 7080.3,\n \"parameters\": {\n \"lat\": \"60.1927487436804\",\n \"lon\": \"11.0695615332356\",\n \"kind\": \"hdd\",\n \"unit\": \"metric\",\n \"base_temp\": \"15\",\n \"base_temp_hdd\": null,\n \"base_temp_cdd\": null,\n \"baseload\": 0,\n \"hdd_coefficient\": 0,\n \"cdd_coefficient\": 0\n },\n \"project_name\": \"Example Monthly Raw Dataset\",\n \"usage_unit\": \"kWh\",\n \"notifications\": []\n },\n \"normalized_data\": [\n {\n \"period_id\": \"1\",\n \"begin_period\": \"2023-01-01\",\n \"end_period\": \"2023-01-31\",\n \"usage\": 152710,\n \"degree_days\": 557.8,\n \"energy_intensity\": 273.77,\n \"normalized_usage_regression_based\": 152710,\n \"normalized_usage_ratio_based\": 152710,\n \"normalized_usage_annual_ratio_distribution\": 152710\n },\n {\n \"period_id\": \"2\",\n \"begin_period\": \"2023-02-01\",\n \"end_period\": \"2023-02-28\",\n \"usage\": 134450,\n \"degree_days\": 464.9,\n \"energy_intensity\": 289.2,\n \"normalized_usage_regression_based\": 134450,\n \"normalized_usage_ratio_based\": 134450,\n \"normalized_usage_annual_ratio_distribution\": 134450\n },\n {\n \"period_id\": \"3\",\n \"begin_period\": \"2023-03-01\",\n \"end_period\": \"2023-03-31\",\n \"usage\": 156040,\n \"degree_days\": 538.1,\n \"energy_intensity\": 289.98,\n \"normalized_usage_regression_based\": 156040,\n \"normalized_usage_ratio_based\": 156040,\n \"normalized_usage_annual_ratio_distribution\": 156040\n },\n {\n \"period_id\": \"4\",\n \"begin_period\": \"2023-04-01\",\n \"end_period\": \"2023-04-30\",\n \"usage\": 59560,\n \"degree_days\": 330.5,\n \"energy_intensity\": 180.21,\n \"normalized_usage_regression_based\": 59560,\n \"normalized_usage_ratio_based\": 59560,\n \"normalized_usage_annual_ratio_distribution\": 59560\n },\n {\n \"period_id\": \"5\",\n \"begin_period\": \"2023-05-01\",\n \"end_period\": \"2023-05-31\",\n \"usage\": 51870,\n \"degree_days\": 140.1,\n \"energy_intensity\": 370.24,\n \"normalized_usage_regression_based\": 51870,\n \"normalized_usage_ratio_based\": 51870,\n \"normalized_usage_annual_ratio_distribution\": 51870\n },\n {\n \"period_id\": \"6\",\n \"begin_period\": \"2023-06-01\",\n \"end_period\": \"2023-06-30\",\n \"usage\": 31600,\n \"degree_days\": 8.9,\n \"energy_intensity\": 3550.56,\n \"normalized_usage_regression_based\": 31600,\n \"normalized_usage_ratio_based\": 31600,\n \"normalized_usage_annual_ratio_distribution\": 31600\n },\n {\n \"period_id\": \"7\",\n \"begin_period\": \"2023-07-01\",\n \"end_period\": \"2023-07-31\",\n \"usage\": 37010,\n \"degree_days\": 13.8,\n \"energy_intensity\": 2681.88,\n \"normalized_usage_regression_based\": 37010,\n \"normalized_usage_ratio_based\": 37010,\n \"normalized_usage_annual_ratio_distribution\": 37010\n },\n {\n \"period_id\": \"8\",\n \"begin_period\": \"2023-08-01\",\n \"end_period\": \"2023-08-31\",\n \"usage\": 33420,\n \"degree_days\": 16.9,\n \"energy_intensity\": 1977.51,\n \"normalized_usage_regression_based\": 33420,\n \"normalized_usage_ratio_based\": 33420,\n \"normalized_usage_annual_ratio_distribution\": 33420\n },\n {\n \"period_id\": \"9\",\n \"begin_period\": \"2023-09-01\",\n \"end_period\": \"2023-09-30\",\n \"usage\": 36260,\n \"degree_days\": 62.9,\n \"energy_intensity\": 576.47,\n \"normalized_usage_regression_based\": 36260,\n \"normalized_usage_ratio_based\": 36260,\n \"normalized_usage_annual_ratio_distribution\": 36260\n },\n {\n \"period_id\": \"10\",\n \"begin_period\": \"2023-10-01\",\n \"end_period\": \"2023-10-31\",\n \"usage\": 100960,\n \"degree_days\": 332.2,\n \"energy_intensity\": 303.91,\n \"normalized_usage_regression_based\": 100960,\n \"normalized_usage_ratio_based\": 100960,\n \"normalized_usage_annual_ratio_distribution\": 100960\n },\n {\n \"period_id\": \"11\",\n \"begin_period\": \"2023-11-01\",\n \"end_period\": \"2023-11-30\",\n \"usage\": 147560,\n \"degree_days\": 511.9,\n \"energy_intensity\": 288.26,\n \"normalized_usage_regression_based\": 147560,\n \"normalized_usage_ratio_based\": 147560,\n \"normalized_usage_annual_ratio_distribution\": 147560\n },\n {\n \"period_id\": \"12\",\n \"begin_period\": \"2023-12-01\",\n \"end_period\": \"2023-12-31\",\n \"usage\": 181920,\n \"degree_days\": 670.8,\n \"energy_intensity\": 271.2,\n \"normalized_usage_regression_based\": 181920,\n \"normalized_usage_ratio_based\": 181920,\n \"normalized_usage_annual_ratio_distribution\": 181920\n },\n {\n \"period_id\": \"13\",\n \"begin_period\": \"2024-01-01\",\n \"end_period\": \"2024-01-31\",\n \"usage\": 198880,\n \"degree_days\": 728,\n \"energy_intensity\": 273.19,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 260532.8,\n \"normalized_usage_annual_ratio_distribution\": 189386.06\n },\n {\n \"period_id\": \"14\",\n \"begin_period\": \"2024-02-01\",\n \"end_period\": \"2024-02-29\",\n \"usage\": 157080,\n \"degree_days\": 527.8,\n \"energy_intensity\": 297.61,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 179071.2,\n \"normalized_usage_annual_ratio_distribution\": 149581.47\n },\n {\n \"period_id\": \"15\",\n \"begin_period\": \"2024-03-01\",\n \"end_period\": \"2024-03-31\",\n \"usage\": 117470,\n \"degree_days\": 442.1,\n \"energy_intensity\": 265.71,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 96325.4,\n \"normalized_usage_annual_ratio_distribution\": 111862.33\n },\n {\n \"period_id\": \"16\",\n \"begin_period\": \"2024-04-01\",\n \"end_period\": \"2024-04-30\",\n \"usage\": 94820,\n \"degree_days\": 326.8,\n \"energy_intensity\": 290.15,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 93871.8,\n \"normalized_usage_annual_ratio_distribution\": 90293.58\n },\n {\n \"period_id\": \"17\",\n \"begin_period\": \"2024-05-01\",\n \"end_period\": \"2024-05-31\",\n \"usage\": 37150,\n \"degree_days\": 38.4,\n \"energy_intensity\": 967.45,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 10030.5,\n \"normalized_usage_annual_ratio_distribution\": 35376.57\n },\n {\n \"period_id\": \"18\",\n \"begin_period\": \"2024-06-01\",\n \"end_period\": \"2024-06-30\",\n \"usage\": 37570,\n \"degree_days\": 54.3,\n \"energy_intensity\": 691.9,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 229177,\n \"normalized_usage_annual_ratio_distribution\": 35776.52\n },\n {\n \"period_id\": \"19\",\n \"begin_period\": \"2024-07-01\",\n \"end_period\": \"2024-07-31\",\n \"usage\": 38550,\n \"degree_days\": 15.4,\n \"energy_intensity\": 2503.25,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 43176,\n \"normalized_usage_annual_ratio_distribution\": 36709.74\n },\n {\n \"period_id\": \"20\",\n \"begin_period\": \"2024-08-01\",\n \"end_period\": \"2024-08-31\",\n \"usage\": 35100,\n \"degree_days\": 18.4,\n \"energy_intensity\": 1907.61,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 38259,\n \"normalized_usage_annual_ratio_distribution\": 33424.43\n },\n {\n \"period_id\": \"21\",\n \"begin_period\": \"2024-09-01\",\n \"end_period\": \"2024-09-30\",\n \"usage\": 47950,\n \"degree_days\": 114.3,\n \"energy_intensity\": 419.51,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 87269,\n \"normalized_usage_annual_ratio_distribution\": 45661.01\n },\n {\n \"period_id\": \"22\",\n \"begin_period\": \"2024-10-01\",\n \"end_period\": \"2024-10-31\",\n \"usage\": 76900,\n \"degree_days\": 250,\n \"energy_intensity\": 307.6,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 57675,\n \"normalized_usage_annual_ratio_distribution\": 73229.02\n },\n {\n \"period_id\": \"23\",\n \"begin_period\": \"2024-11-01\",\n \"end_period\": \"2024-11-30\",\n \"usage\": 124110,\n \"degree_days\": 423.8,\n \"energy_intensity\": 292.85,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 103011.3,\n \"normalized_usage_annual_ratio_distribution\": 118185.36\n },\n {\n \"period_id\": \"24\",\n \"begin_period\": \"2024-12-01\",\n \"end_period\": \"2024-12-31\",\n \"usage\": 143840,\n \"degree_days\": 492.2,\n \"energy_intensity\": 292.24,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_ratio_based\": 105003.2,\n \"normalized_usage_annual_ratio_distribution\": 136973.51\n }\n ],\n \"monthly_summary\": {\n \"January\": {\n \"2023\": {\n \"usage\": 152710,\n \"degree_days\": 557.8,\n \"normalized_usage_ratio_based\": 152710,\n \"normalized_usage_regression_based\": 152710,\n \"normalized_usage_annual_ratio_distribution\": 152710,\n \"energy_intensity\": 273.77\n },\n \"2024\": {\n \"usage\": 198880,\n \"degree_days\": 728,\n \"normalized_usage_ratio_based\": 260532.8,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 189386.06,\n \"energy_intensity\": 273.19\n }\n },\n \"February\": {\n \"2023\": {\n \"usage\": 134450,\n \"degree_days\": 464.9,\n \"normalized_usage_ratio_based\": 134450,\n \"normalized_usage_regression_based\": 134450,\n \"normalized_usage_annual_ratio_distribution\": 134450,\n \"energy_intensity\": 289.2\n },\n \"2024\": {\n \"usage\": 157080,\n \"degree_days\": 527.8,\n \"normalized_usage_ratio_based\": 179071.2,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 149581.47,\n \"energy_intensity\": 297.61\n }\n },\n \"March\": {\n \"2023\": {\n \"usage\": 156040,\n \"degree_days\": 538.1,\n \"normalized_usage_ratio_based\": 156040,\n \"normalized_usage_regression_based\": 156040,\n \"normalized_usage_annual_ratio_distribution\": 156040,\n \"energy_intensity\": 289.98\n },\n \"2024\": {\n \"usage\": 117470,\n \"degree_days\": 442.1,\n \"normalized_usage_ratio_based\": 96325.4,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 111862.33,\n \"energy_intensity\": 265.71\n }\n },\n \"April\": {\n \"2023\": {\n \"usage\": 59560,\n \"degree_days\": 330.5,\n \"normalized_usage_ratio_based\": 59560,\n \"normalized_usage_regression_based\": 59560,\n \"normalized_usage_annual_ratio_distribution\": 59560,\n \"energy_intensity\": 180.21\n },\n \"2024\": {\n \"usage\": 94820,\n \"degree_days\": 326.8,\n \"normalized_usage_ratio_based\": 93871.8,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 90293.58,\n \"energy_intensity\": 290.15\n }\n },\n \"May\": {\n \"2023\": {\n \"usage\": 51870,\n \"degree_days\": 140.1,\n \"normalized_usage_ratio_based\": 51870,\n \"normalized_usage_regression_based\": 51870,\n \"normalized_usage_annual_ratio_distribution\": 51870,\n \"energy_intensity\": 370.24\n },\n \"2024\": {\n \"usage\": 37150,\n \"degree_days\": 38.4,\n \"normalized_usage_ratio_based\": 10030.5,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 35376.57,\n \"energy_intensity\": 967.45\n }\n },\n \"June\": {\n \"2023\": {\n \"usage\": 31600,\n \"degree_days\": 8.9,\n \"normalized_usage_ratio_based\": 31600,\n \"normalized_usage_regression_based\": 31600,\n \"normalized_usage_annual_ratio_distribution\": 31600,\n \"energy_intensity\": 3550.56\n },\n \"2024\": {\n \"usage\": 37570,\n \"degree_days\": 54.3,\n \"normalized_usage_ratio_based\": 229177,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 35776.52,\n \"energy_intensity\": 691.9\n }\n },\n \"July\": {\n \"2023\": {\n \"usage\": 37010,\n \"degree_days\": 13.8,\n \"normalized_usage_ratio_based\": 37010,\n \"normalized_usage_regression_based\": 37010,\n \"normalized_usage_annual_ratio_distribution\": 37010,\n \"energy_intensity\": 2681.88\n },\n \"2024\": {\n \"usage\": 38550,\n \"degree_days\": 15.4,\n \"normalized_usage_ratio_based\": 43176,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 36709.74,\n \"energy_intensity\": 2503.25\n }\n },\n \"August\": {\n \"2023\": {\n \"usage\": 33420,\n \"degree_days\": 16.9,\n \"normalized_usage_ratio_based\": 33420,\n \"normalized_usage_regression_based\": 33420,\n \"normalized_usage_annual_ratio_distribution\": 33420,\n \"energy_intensity\": 1977.51\n },\n \"2024\": {\n \"usage\": 35100,\n \"degree_days\": 18.4,\n \"normalized_usage_ratio_based\": 38259,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 33424.43,\n \"energy_intensity\": 1907.61\n }\n },\n \"September\": {\n \"2023\": {\n \"usage\": 36260,\n \"degree_days\": 62.9,\n \"normalized_usage_ratio_based\": 36260,\n \"normalized_usage_regression_based\": 36260,\n \"normalized_usage_annual_ratio_distribution\": 36260,\n \"energy_intensity\": 576.47\n },\n \"2024\": {\n \"usage\": 47950,\n 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{\n \"usage\": 124110,\n \"degree_days\": 423.8,\n \"normalized_usage_ratio_based\": 103011.3,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 118185.36,\n \"energy_intensity\": 292.85\n }\n },\n \"December\": {\n \"2023\": {\n \"usage\": 181920,\n \"degree_days\": 670.8,\n \"normalized_usage_ratio_based\": 181920,\n \"normalized_usage_regression_based\": 181920,\n \"normalized_usage_annual_ratio_distribution\": 181920,\n \"energy_intensity\": 271.2\n },\n \"2024\": {\n \"usage\": 143840,\n \"degree_days\": 492.2,\n \"normalized_usage_ratio_based\": 105003.2,\n \"normalized_usage_regression_based\": 0,\n \"normalized_usage_annual_ratio_distribution\": 136973.51,\n \"energy_intensity\": 292.24\n }\n }\n },\n \"yearly_summary\": {\n \"2023\": {\n \"usage\": 1123360,\n \"degree_days\": 3648.8,\n \"normalized_usage_ratio_based\": 1123360,\n \"normalized_usage_regression_based\": 1123360,\n \"normalized_usage_annual_ratio_distribution\": 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\"total_degree_days\": 7080.3,\n \"parameters\": {\n \"lat\": \"60.1927487\",\n \"lon\": \"11.0695615332356\",\n \"kind\": \"hdd\",\n \"unit\": \"metric\",\n \"base_temp\": \"15\",\n \"base_temp_hdd\": \"15\",\n \"base_temp_cdd\": null,\n \"baseload\": 2,\n \"hdd_coefficient\": 1.1,\n \"cdd_coefficient\": 1.5\n },\n \"project_name\": \"Example MOnthly Raw Dataset\",\n \"usage_unit\": \"kWh\",\n \"notifications\": []\n },\n \"normalized_data\": [\n {\n \"period_id\": \"1\",\n \"begin_period\": \"2023-01-01\",\n \"end_period\": \"2023-01-31\",\n \"usage\": 152710,\n \"degree_days\": 557.8,\n \"energy_intensity\": 273.77,\n \"normalized_usage_regression_based\": 152710,\n \"normalized_usage_ratio_based\": 152710,\n \"normalized_usage_annual_ratio_distribution\": 152710\n },\n {\n \"period_id\": \"2\",\n \"begin_period\": \"2023-02-01\",\n \"end_period\": \"2023-02-28\",\n \"usage\": 134450,\n \"degree_days\": 464.9,\n \"energy_intensity\": 289.2,\n \"normalized_usage_regression_based\": 134450,\n \"normalized_usage_ratio_based\": 134450,\n \"normalized_usage_annual_ratio_distribution\": 134450\n },\n {\n \"period_id\": \"3\",\n \"begin_period\": \"2023-03-01\",\n \"end_period\": \"2023-03-31\",\n \"usage\": 156040,\n \"degree_days\": 538.1,\n \"energy_intensity\": 289.98,\n \"normalized_usage_regression_based\": 156040,\n \"normalized_usage_ratio_based\": 156040,\n \"normalized_usage_annual_ratio_distribution\": 156040\n },\n {\n \"period_id\": \"4\",\n \"begin_period\": \"2023-04-01\",\n \"end_period\": \"2023-04-30\",\n \"usage\": 59560,\n \"degree_days\": 330.5,\n \"energy_intensity\": 180.21,\n \"normalized_usage_regression_based\": 59560,\n \"normalized_usage_ratio_based\": 59560,\n \"normalized_usage_annual_ratio_distribution\": 59560\n },\n {\n \"period_id\": \"5\",\n \"begin_period\": \"2023-05-01\",\n \"end_period\": \"2023-05-31\",\n \"usage\": 51870,\n \"degree_days\": 140.1,\n \"energy_intensity\": 370.22,\n \"normalized_usage_regression_based\": 51870,\n \"normalized_usage_ratio_based\": 51870,\n \"normalized_usage_annual_ratio_distribution\": 51870\n },\n {\n \"period_id\": \"6\",\n \"begin_period\": \"2023-06-01\",\n \"end_period\": \"2023-06-30\",\n \"usage\": 31600,\n \"degree_days\": 8.9,\n \"energy_intensity\": 3550.34,\n \"normalized_usage_regression_based\": 31600,\n \"normalized_usage_ratio_based\": 31600,\n \"normalized_usage_annual_ratio_distribution\": 31600\n },\n {\n \"period_id\": \"7\",\n \"begin_period\": \"2023-07-01\",\n \"end_period\": \"2023-07-31\",\n \"usage\": 37010,\n \"degree_days\": 13.8,\n \"energy_intensity\": 2681.74,\n \"normalized_usage_regression_based\": 37010,\n \"normalized_usage_ratio_based\": 37010,\n \"normalized_usage_annual_ratio_distribution\": 37010\n },\n {\n \"period_id\": \"8\",\n \"begin_period\": \"2023-08-01\",\n \"end_period\": \"2023-08-31\",\n \"usage\": 33420,\n \"degree_days\": 16.9,\n \"energy_intensity\": 1977.4,\n \"normalized_usage_regression_based\": 33420,\n \"normalized_usage_ratio_based\": 33420,\n \"normalized_usage_annual_ratio_distribution\": 33420\n },\n {\n \"period_id\": \"9\",\n \"begin_period\": \"2023-09-01\",\n \"end_period\": \"2023-09-30\",\n \"usage\": 36260,\n \"degree_days\": 62.9,\n \"energy_intensity\": 576.44,\n \"normalized_usage_regression_based\": 36260,\n \"normalized_usage_ratio_based\": 36260,\n \"normalized_usage_annual_ratio_distribution\": 36260\n },\n {\n \"period_id\": \"10\",\n \"begin_period\": \"2023-10-01\",\n \"end_period\": \"2023-10-31\",\n \"usage\": 100960,\n \"degree_days\": 332.2,\n \"energy_intensity\": 303.91,\n \"normalized_usage_regression_based\": 100960,\n \"normalized_usage_ratio_based\": 100960,\n \"normalized_usage_annual_ratio_distribution\": 100960\n },\n {\n \"period_id\": \"11\",\n \"begin_period\": \"2023-11-01\",\n \"end_period\": \"2023-11-30\",\n \"usage\": 147560,\n \"degree_days\": 511.9,\n \"energy_intensity\": 288.26,\n \"normalized_usage_regression_based\": 147560,\n \"normalized_usage_ratio_based\": 147560,\n \"normalized_usage_annual_ratio_distribution\": 147560\n },\n {\n \"period_id\": \"12\",\n \"begin_period\": \"2023-12-01\",\n \"end_period\": \"2023-12-31\",\n \"usage\": 181920,\n \"degree_days\": 670.8,\n \"energy_intensity\": 271.2,\n \"normalized_usage_regression_based\": 181920,\n \"normalized_usage_ratio_based\": 181920,\n \"normalized_usage_annual_ratio_distribution\": 181920\n },\n {\n \"period_id\": \"13\",\n \"begin_period\": \"2024-01-01\",\n \"end_period\": \"2024-01-31\",\n \"usage\": 198880,\n \"degree_days\": 728,\n \"energy_intensity\": 273.18,\n \"normalized_usage_regression_based\": 802.8,\n \"normalized_usage_ratio_based\": 260532.8,\n \"normalized_usage_annual_ratio_distribution\": 189390.51\n },\n {\n \"period_id\": \"14\",\n \"begin_period\": \"2024-02-01\",\n \"end_period\": \"2024-02-29\",\n \"usage\": 157080,\n \"degree_days\": 527.8,\n \"energy_intensity\": 297.61,\n \"normalized_usage_regression_based\": 582.58,\n \"normalized_usage_ratio_based\": 179071.2,\n \"normalized_usage_annual_ratio_distribution\": 149585.01\n },\n {\n \"period_id\": \"15\",\n \"begin_period\": \"2024-03-01\",\n \"end_period\": \"2024-03-31\",\n \"usage\": 117470,\n \"degree_days\": 442.1,\n \"energy_intensity\": 265.7,\n \"normalized_usage_regression_based\": 488.31,\n \"normalized_usage_ratio_based\": 96325.4,\n \"normalized_usage_annual_ratio_distribution\": 111865\n },\n {\n \"period_id\": \"16\",\n \"begin_period\": \"2024-04-01\",\n \"end_period\": \"2024-04-30\",\n \"usage\": 94820,\n \"degree_days\": 326.8,\n \"energy_intensity\": 290.14,\n \"normalized_usage_regression_based\": 361.48,\n \"normalized_usage_ratio_based\": 93871.8,\n \"normalized_usage_annual_ratio_distribution\": 90295.75\n },\n {\n \"period_id\": \"17\",\n \"begin_period\": \"2024-05-01\",\n \"end_period\": \"2024-05-31\",\n \"usage\": 37150,\n \"degree_days\": 38.4,\n \"energy_intensity\": 967.4,\n \"normalized_usage_regression_based\": 44.24,\n \"normalized_usage_ratio_based\": 10030.5,\n \"normalized_usage_annual_ratio_distribution\": 35377.48\n },\n {\n \"period_id\": \"18\",\n \"begin_period\": \"2024-06-01\",\n \"end_period\": \"2024-06-30\",\n \"usage\": 37570,\n \"degree_days\": 54.3,\n \"energy_intensity\": 691.86,\n \"normalized_usage_regression_based\": 61.73,\n \"normalized_usage_ratio_based\": 229177,\n \"normalized_usage_annual_ratio_distribution\": 35777.44\n },\n {\n \"period_id\": \"19\",\n \"begin_period\": \"2024-07-01\",\n \"end_period\": \"2024-07-31\",\n \"usage\": 38550,\n \"degree_days\": 15.4,\n \"energy_intensity\": 2503.12,\n \"normalized_usage_regression_based\": 18.94,\n \"normalized_usage_ratio_based\": 43176,\n \"normalized_usage_annual_ratio_distribution\": 36710.68\n },\n {\n \"period_id\": \"20\",\n \"begin_period\": \"2024-08-01\",\n \"end_period\": \"2024-08-31\",\n \"usage\": 35100,\n \"degree_days\": 18.4,\n \"energy_intensity\": 1907.5,\n \"normalized_usage_regression_based\": 22.24,\n \"normalized_usage_ratio_based\": 38259,\n \"normalized_usage_annual_ratio_distribution\": 33425.29\n },\n {\n \"period_id\": \"21\",\n \"begin_period\": \"2024-09-01\",\n \"end_period\": \"2024-09-30\",\n \"usage\": 47950,\n \"degree_days\": 114.3,\n \"energy_intensity\": 419.49,\n \"normalized_usage_regression_based\": 127.73,\n \"normalized_usage_ratio_based\": 87269,\n \"normalized_usage_annual_ratio_distribution\": 45662.16\n },\n {\n \"period_id\": \"22\",\n \"begin_period\": \"2024-10-01\",\n \"end_period\": \"2024-10-31\",\n \"usage\": 76900,\n \"degree_days\": 250,\n \"energy_intensity\": 307.59,\n \"normalized_usage_regression_based\": 277,\n \"normalized_usage_ratio_based\": 57675,\n \"normalized_usage_annual_ratio_distribution\": 73230.8\n },\n {\n \"period_id\": \"23\",\n \"begin_period\": \"2024-11-01\",\n \"end_period\": \"2024-11-30\",\n \"usage\": 124110,\n \"degree_days\": 423.8,\n \"energy_intensity\": 292.85,\n \"normalized_usage_regression_based\": 468.18,\n \"normalized_usage_ratio_based\": 103011.3,\n \"normalized_usage_annual_ratio_distribution\": 118188.17\n },\n {\n \"period_id\": \"24\",\n \"begin_period\": \"2024-12-01\",\n \"end_period\": \"2024-12-31\",\n \"usage\": 143840,\n \"degree_days\": 492.2,\n \"energy_intensity\": 292.23,\n \"normalized_usage_regression_based\": 543.42,\n \"normalized_usage_ratio_based\": 105003.2,\n \"normalized_usage_annual_ratio_distribution\": 136976.75\n }\n ],\n \"monthly_summary\": {\n \"January\": {\n \"2023\": {\n \"usage\": 152710,\n \"degree_days\": 557.8,\n \"normalized_usage_ratio_based\": 152710,\n \"normalized_usage_regression_based\": 152710,\n \"normalized_usage_annual_ratio_distribution\": 152710,\n \"energy_intensity\": 273.77\n },\n \"2024\": {\n \"usage\": 198880,\n \"degree_days\": 728,\n \"normalized_usage_ratio_based\": 260532.8,\n \"normalized_usage_regression_based\": 802.8,\n \"normalized_usage_annual_ratio_distribution\": 189390.51,\n \"energy_intensity\": 273.19\n }\n },\n \"February\": {\n \"2023\": {\n \"usage\": 134450,\n \"degree_days\": 464.9,\n \"normalized_usage_ratio_based\": 134450,\n \"normalized_usage_regression_based\": 134450,\n \"normalized_usage_annual_ratio_distribution\": 134450,\n \"energy_intensity\": 289.2\n },\n \"2024\": {\n \"usage\": 157080,\n \"degree_days\": 527.8,\n \"normalized_usage_ratio_based\": 179071.2,\n \"normalized_usage_regression_based\": 582.58,\n \"normalized_usage_annual_ratio_distribution\": 149585.01,\n \"energy_intensity\": 297.61\n }\n },\n \"March\": {\n \"2023\": {\n \"usage\": 156040,\n \"degree_days\": 538.1,\n \"normalized_usage_ratio_based\": 156040,\n \"normalized_usage_regression_based\": 156040,\n \"normalized_usage_annual_ratio_distribution\": 156040,\n \"energy_intensity\": 289.98\n },\n \"2024\": {\n \"usage\": 117470,\n \"degree_days\": 442.1,\n \"normalized_usage_ratio_based\": 96325.4,\n \"normalized_usage_regression_based\": 488.31,\n \"normalized_usage_annual_ratio_distribution\": 111865,\n \"energy_intensity\": 265.71\n }\n },\n \"April\": {\n \"2023\": {\n \"usage\": 59560,\n \"degree_days\": 330.5,\n \"normalized_usage_ratio_based\": 59560,\n \"normalized_usage_regression_based\": 59560,\n \"normalized_usage_annual_ratio_distribution\": 59560,\n \"energy_intensity\": 180.21\n },\n \"2024\": {\n \"usage\": 94820,\n \"degree_days\": 326.8,\n \"normalized_usage_ratio_based\": 93871.8,\n \"normalized_usage_regression_based\": 361.48,\n \"normalized_usage_annual_ratio_distribution\": 90295.75,\n \"energy_intensity\": 290.15\n }\n },\n \"May\": {\n \"2023\": {\n \"usage\": 51870,\n \"degree_days\": 140.1,\n \"normalized_usage_ratio_based\": 51870,\n \"normalized_usage_regression_based\": 51870,\n \"normalized_usage_annual_ratio_distribution\": 51870,\n \"energy_intensity\": 370.24\n },\n \"2024\": {\n \"usage\": 37150,\n \"degree_days\": 38.4,\n \"normalized_usage_ratio_based\": 10030.5,\n \"normalized_usage_regression_based\": 44.24,\n \"normalized_usage_annual_ratio_distribution\": 35377.48,\n \"energy_intensity\": 967.45\n }\n },\n \"June\": {\n \"2023\": {\n \"usage\": 31600,\n \"degree_days\": 8.9,\n \"normalized_usage_ratio_based\": 31600,\n \"normalized_usage_regression_based\": 31600,\n \"normalized_usage_annual_ratio_distribution\": 31600,\n \"energy_intensity\": 3550.56\n },\n \"2024\": {\n \"usage\": 37570,\n \"degree_days\": 54.3,\n \"normalized_usage_ratio_based\": 229177,\n \"normalized_usage_regression_based\": 61.73,\n \"normalized_usage_annual_ratio_distribution\": 35777.44,\n \"energy_intensity\": 691.9\n }\n },\n \"July\": {\n \"2023\": {\n \"usage\": 37010,\n \"degree_days\": 13.8,\n \"normalized_usage_ratio_based\": 37010,\n \"normalized_usage_regression_based\": 37010,\n \"normalized_usage_annual_ratio_distribution\": 37010,\n \"energy_intensity\": 2681.88\n },\n \"2024\": {\n \"usage\": 38550,\n \"degree_days\": 15.4,\n \"normalized_usage_ratio_based\": 43176,\n \"normalized_usage_regression_based\": 18.94,\n \"normalized_usage_annual_ratio_distribution\": 36710.68,\n \"energy_intensity\": 2503.25\n }\n },\n \"August\": {\n \"2023\": {\n \"usage\": 33420,\n \"degree_days\": 16.9,\n \"normalized_usage_ratio_based\": 33420,\n \"normalized_usage_regression_based\": 33420,\n \"normalized_usage_annual_ratio_distribution\": 33420,\n \"energy_intensity\": 1977.51\n },\n \"2024\": {\n \"usage\": 35100,\n \"degree_days\": 18.4,\n \"normalized_usage_ratio_based\": 38259,\n \"normalized_usage_regression_based\": 22.24,\n \"normalized_usage_annual_ratio_distribution\": 33425.29,\n \"energy_intensity\": 1907.61\n }\n },\n \"September\": {\n \"2023\": {\n \"usage\": 36260,\n \"degree_days\": 62.9,\n \"normalized_usage_ratio_based\": 36260,\n \"normalized_usage_regression_based\": 36260,\n \"normalized_usage_annual_ratio_distribution\": 36260,\n \"energy_intensity\": 576.47\n },\n \"2024\": {\n \"usage\": 47950,\n \"degree_days\": 114.3,\n \"normalized_usage_ratio_based\": 87269,\n \"normalized_usage_regression_based\": 127.73,\n \"normalized_usage_annual_ratio_distribution\": 45662.16,\n \"energy_intensity\": 419.51\n }\n },\n \"October\": {\n \"2023\": {\n \"usage\": 100960,\n \"degree_days\": 332.2,\n \"normalized_usage_ratio_based\": 100960,\n \"normalized_usage_regression_based\": 100960,\n \"normalized_usage_annual_ratio_distribution\": 100960,\n \"energy_intensity\": 303.91\n },\n \"2024\": {\n \"usage\": 76900,\n \"degree_days\": 250,\n \"normalized_usage_ratio_based\": 57675,\n \"normalized_usage_regression_based\": 277,\n \"normalized_usage_annual_ratio_distribution\": 73230.8,\n \"energy_intensity\": 307.6\n }\n },\n \"November\": {\n \"2023\": {\n \"usage\": 147560,\n \"degree_days\": 511.9,\n \"normalized_usage_ratio_based\": 147560,\n \"normalized_usage_regression_based\": 147560,\n \"normalized_usage_annual_ratio_distribution\": 147560,\n \"energy_intensity\": 288.26\n },\n \"2024\": {\n \"usage\": 124110,\n \"degree_days\": 423.8,\n \"normalized_usage_ratio_based\": 103011.3,\n \"normalized_usage_regression_based\": 468.18,\n \"normalized_usage_annual_ratio_distribution\": 118188.17,\n \"energy_intensity\": 292.85\n }\n },\n \"December\": {\n \"2023\": {\n \"usage\": 181920,\n \"degree_days\": 670.8,\n \"normalized_usage_ratio_based\": 181920,\n \"normalized_usage_regression_based\": 181920,\n \"normalized_usage_annual_ratio_distribution\": 181920,\n \"energy_intensity\": 271.2\n },\n \"2024\": {\n \"usage\": 143840,\n \"degree_days\": 492.2,\n \"normalized_usage_ratio_based\": 105003.2,\n \"normalized_usage_regression_based\": 543.42,\n \"normalized_usage_annual_ratio_distribution\": 136976.75,\n \"energy_intensity\": 292.24\n }\n }\n },\n \"yearly_summary\": {\n \"2023\": {\n \"usage\": 1123360,\n \"degree_days\": 3648.8,\n \"normalized_usage_ratio_based\": 1123360,\n \"normalized_usage_regression_based\": 1123360,\n \"normalized_usage_annual_ratio_distribution\": 1123360,\n \"energy_intensity\": 307.87\n },\n \"2024\": {\n \"usage\": 1109420,\n \"degree_days\": 3431.5000000000005,\n \"normalized_usage_ratio_based\": 1303402.2000000002,\n \"normalized_usage_regression_based\": 3798.6499999999996,\n \"normalized_usage_annual_ratio_distribution\": 1056485.04,\n \"energy_intensity\": 323.3\n }\n },\n \"year_to_date_summary\": {\n \"2023\": {\n \"usage\": 1123360,\n \"degree_days\": 3648.8,\n \"normalized_usage_ratio_based\": 1123360,\n \"normalized_usage_regression_based\": 1123360,\n \"normalized_usage_annual_ratio_distribution\": 1123360,\n \"energy_intensity\": 307.87\n },\n \"2024\": {\n \"usage\": 1109420,\n \"degree_days\": 3431.5000000000005,\n \"normalized_usage_ratio_based\": 1303402.2000000002,\n \"normalized_usage_regression_based\": 3798.6499999999996,\n \"normalized_usage_annual_ratio_distribution\": 1056485.04,\n \"energy_intensity\": 323.3\n },\n \"metadata\": {\n \"period_start\": \"2024-01-01\",\n \"period_end\": \"2024-12-31\"\n }\n }\n}"}],"_postman_id":"4e01dd9b-326a-4e46-a522-1804d1c34435"}],"id":"49fdc79b-b1be-49c7-b08f-e3f14dbf2e5b","description":"The goal of the normalization process is to adjust energy usage data by accounting for weather differences—measured as degree days—across different periods.
\nThe process follows these steps:
\nFor method=\"bth\" mode: Each day’s heating degree days (HDD) and cooling degree days (CDD) are collected. The code loops through each day within an energy usage period and sums up the HDD and CDD values.
\n**For Single-Type Modes (e.g., \"hdd\" or \"cdd\"):**Each day’s value for the specified type (HDD or CDD) is added together to form a total for the period.
\nAfter calculating the total degree days for a period, the code subtracts the baseload from the raw usage (if provided) to focus on the weather-sensitive portion. Then:
\nFor \"bth\" mode: The EI is calculated by dividing the adjusted usage by the sum of HDD and CDD.
\nFor single-type modes: The adjusted usage is divided by the total degree days of that type (if the total is above zero).
\nThe method assumes that the relationship between degree days and energy usage is linear. Here’s how it works:
\nStep 1: Remove Baseload: The constant baseload (representing non-weather-related energy usage) is subtracted from the raw usage.
\nStep 2: Normalize the Weather-Sensitive Portion: The remainder is normalized using degree day coefficients. These coefficients—along with the baseload—are typically determined by regression analysis. Regression analysis helps in finding the best-fit line that explains how changes in degree days affect energy usage.
\nStep 3: Add Baseload Back: After adjusting the weather-sensitive part, the baseload is added back to form the final normalized usage.
\n_Annual Ratio Distribution Method_This method normalizes your energy usage to account for weather differences by comparing it to a selected base year.
\nHow it works:
\nCalculate annual totals of your actual energy usage and degree days, and compare them with the annual totals from your chosen base year.
\nDetermine a weather-adjusted annual energy usage based on how weather conditions (degree days) differ between your actual year and the base year.
\nRedistribute this normalized annual energy back into each month, proportionally to your actual monthly usage patterns.
\nThis method smooths out monthly variations, making your energy performance clearer and easier to track, despite varying weather conditions.
\n_Direct Ratio Method_This method normalizes your energy usage month-by-month by directly comparing each month's weather conditions (degree days) in your actual year to the corresponding month in your selected base year.
\nHow it works:
\nCalculate the ratio between degree days in each month of your base year and the same month in your actual year.
\nAdjust each month's actual energy usage using this direct ratio.
\nThis approach gives a straightforward, month-specific normalization. However, keep in mind that months with very low degree-day values can lead to high or unstable ratios, making those months' results less reliable.
\nLinear Relationship:
\nIt is assumed that there is a linear relationship between degree days (weather conditions) and energy usage.
\nConstant Baseload:
\nThe baseload, which represents the energy used regardless of weather (e.g., lighting, always-on equipment), is assumed to be constant across all periods.
\nNo Aging Factor:
\nThe method does not consider any changes in equipment efficiency or energy usage due to aging or wear over time.
\nDetermining Coefficients:
\nBoth the baseload and the degree day coefficients are determined using regression analysis on historical data, which establishes the linear model linking degree days to energy usage.
\nResponse Codes:
\n200 OK: Returns normalized data along with summaries (monthly, yearly, year-to-date).
\n400 Bad Request: Missing or invalid parameters.
\n401 Unauthorized: Invalid or missing API key.
\n429 Too Many Requests: API rate limit exceeded.
\n500 Internal Server Error: Unexpected processing errors.
\n502 Bad Gateway: Issues retrieving dataset metadata.
\nAvailable on request.
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