Name: Solar Output Prediction Using Weather Data
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Solar Output Prediction Using Weather Data

Using the weather data, predict solar output

By [source]

About this dataset

This dataset consists of solar output predictions using weather data. The data was collected from various sources and contains information on solar output, weather, date, and time. The solar output predictions are based on historical weather patterns and data

How to use the dataset

This dataset can be used to predict solar output using weather data. The data was collected from various sources and contains information on solar output, weather, date, and time. The dataset can be used to train a model that predicts solar output based on weather conditions

Research Ideas

The dataset can be used to predict solar output for a given location.

The dataset can be used to study the relationship between weather and solar output.

The dataset can be used to develop a new approach to predicting solar output

Acknowledgements

Data Source

License

> License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
> No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: rawWeatherDataStanford.csv

Column name	Description
WBAN	Weather Bureau Air Force Navy (Column Type: Integer)
Date	The date of the observation (Column Type: Date)
Time	The time of the observation (Column Type: Time)
SkyCondition	The sky condition at the time of the observation (Column Type: String)
Visibility	The visibility at the time of the observation (Column Type: Integer)
Temperature	The temperature at the time of the observation (Column Type: Integer)
DewPoint	The dew point at the time of the observation (Column Type: Integer)
WindSpeed	The wind speed at the time of the observation (Column Type: Integer)
StationPressure	The station pressure at the time of the observation (Column Type: Integer)
Altimeter	The altimeter at the time of the observation (Column Type: Integer)

File: Erle_zipcodes.csv

File: example_config.csv

Column name	Description
zip5	The zip code of the location where the data was collected. (String)
start_date	The start date of the data collection. (Date)
end_date	The end date of the data collection. (Date)

File: weather_dev.csv

File: weather_test.csv

Column name	Description
11;1;10;8.63;6.21;83;16.32;28.91;29.69;1293.75

File: weather_train.csv

File: solar-output_hourly.csv

File: weather_test_timeline.csv

Acknowledgements

If you use this dataset in your research, please credit the original author.

Tables

Erle Zipcodes

@kaggle.thedevastator_solar_output_prediction_using_weather_data.erle_zipcodes

1.27 MB
43,193 rows
7 columns

CREATE TABLE erle_zipcodes (
  "zip" BIGINT,
  "city" VARCHAR,
  "state" VARCHAR,
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "timezone" BIGINT,
  "dst" BIGINT
);

Error Pca5–12hour

@kaggle.thedevastator_solar_output_prediction_using_weather_data.error_pca5_12hour

4.74 kB
54 rows
5 columns

CREATE TABLE error_pca5_12hour (
  "n_12" BIGINT  -- 12,
  "n_20" BIGINT  -- 20,
  "n_2" BIGINT  -- 2,
  "n_2016" BIGINT  -- 2016,
  "n_0_31639" DOUBLE  -- 0.31639
);

Error Pca5–16hour

@kaggle.thedevastator_solar_output_prediction_using_weather_data.error_pca5_16hour

4.92 kB
67 rows
5 columns

CREATE TABLE error_pca5_16hour (
  "n_16" BIGINT  -- 16,
  "n_11" BIGINT  -- 11,
  "n_2" BIGINT  -- 2,
  "n_2016" BIGINT  -- 2016,
  "n_4_8897" DOUBLE  -- 4.8897
);

Error Pca5–8hour

@kaggle.thedevastator_solar_output_prediction_using_weather_data.error_pca5_8hour

4.79 kB
59 rows
5 columns

CREATE TABLE error_pca5_8hour (
  "n_8" BIGINT  -- 8,
  "n_29" BIGINT  -- 29,
  "n_2" BIGINT  -- 2,
  "n_2016" BIGINT  -- 2016,
  "n_0_47614" DOUBLE  -- 0.47614
);

Error Wlr 12hour

@kaggle.thedevastator_solar_output_prediction_using_weather_data.error_wlr_12hour

4.74 kB
54 rows
5 columns

CREATE TABLE error_wlr_12hour (
  "n_12" BIGINT  -- 12,
  "n_20" BIGINT  -- 20,
  "n_2" BIGINT  -- 2,
  "n_2016" BIGINT  -- 2016,
  "n_0_28133" DOUBLE  -- 0.28133
);

Error Wlr 16hour

@kaggle.thedevastator_solar_output_prediction_using_weather_data.error_wlr_16hour

4.92 kB
67 rows
5 columns

CREATE TABLE error_wlr_16hour (
  "n_16" BIGINT  -- 16,
  "n_11" BIGINT  -- 11,
  "n_2" BIGINT  -- 2,
  "n_2016" BIGINT  -- 2016,
  "n_2_685" DOUBLE  -- 2.685
);

Error Wlr 8hour

@kaggle.thedevastator_solar_output_prediction_using_weather_data.error_wlr_8hour

4.79 kB
59 rows
5 columns

CREATE TABLE error_wlr_8hour (
  "n_8" BIGINT  -- 8,
  "n_29" BIGINT  -- 29,
  "n_2" BIGINT  -- 2,
  "n_2016" BIGINT  -- 2016,
  "n_0_45921" DOUBLE  -- 0.45921
);

Example Config

@kaggle.thedevastator_solar_output_prediction_using_weather_data.example_config

2.97 kB
4 rows
3 columns

CREATE TABLE example_config (
  "zip5" BIGINT,
  "start_date" TIMESTAMP,
  "end_date" TIMESTAMP
);

Pcacorrelation

@kaggle.thedevastator_solar_output_prediction_using_weather_data.pcacorrelation

2.88 kB
7 rows
3 columns

CREATE TABLE pcacorrelation (
  "n_0_14" DOUBLE  -- 0.14,
  "unnamed_1" DOUBLE  -- Unnamed: 1,
  "n_6" DOUBLE  -- 6
);

Rawweatherdatastanford

@kaggle.thedevastator_solar_output_prediction_using_weather_data.rawweatherdatastanford

201.69 kB
25,152 rows
11 columns

CREATE TABLE rawweatherdatastanford (
  "wban" BIGINT,
  "date" BIGINT,
  "time" BIGINT,
  "skycondition" VARCHAR,
  "visibility" VARCHAR,
  "temperature" VARCHAR,
  "dewpoint" VARCHAR,
  "relativehumidity" VARCHAR,
  "windspeed" VARCHAR,
  "stationpressure" VARCHAR,
  "altimeter" VARCHAR
);

Solar Output Daily

@kaggle.thedevastator_solar_output_prediction_using_weather_data.solar_output_daily

23.95 kB
713 rows
4 columns

CREATE TABLE solar_output_daily (
  "timestamp" TIMESTAMP,
  "new_nexus_1272_meter" VARCHAR,
  "inverters" VARCHAR,
  "site_performance_estimate" VARCHAR
);

Solar Output Hourly

@kaggle.thedevastator_solar_output_prediction_using_weather_data.solar_output_hourly

57.3 kB
15,072 rows
5 columns

CREATE TABLE solar_output_hourly (
  "month" BIGINT,
  "day" BIGINT,
  "year" BIGINT,
  "hr" BIGINT,
  "inverter_hr_mean" DOUBLE
);

Weather Dev

@kaggle.thedevastator_solar_output_prediction_using_weather_data.weather_dev

31.66 kB
753 rows
10 columns

CREATE TABLE weather_dev (
  "n_8" BIGINT  -- 8,
  "n_0_14" DOUBLE  -- 0.14,
  "n_10" DOUBLE  -- 10,
  "n_24_18" DOUBLE  -- 24.18,
  "n_11_59" DOUBLE  -- 11.59,
  "n_41_36" DOUBLE  -- 41.36,
  "n_9_04" DOUBLE  -- 9.04,
  "n_29_24" DOUBLE  -- 29.24,
  "n_30_03" DOUBLE  -- 30.03,
  "n_2132" DOUBLE  -- 2132
);

Weather Test

@kaggle.thedevastator_solar_output_prediction_using_weather_data.weather_test

31.21 kB
753 rows
10 columns

CREATE TABLE weather_test (
  "n_11" BIGINT  -- 11,
  "n_1" DOUBLE  -- 1,
  "n_10" DOUBLE  -- 10,
  "n_8_63" DOUBLE  -- 8.63,
  "n_6_21" DOUBLE  -- 6.21,
  "n_83" DOUBLE  -- 83,
  "n_16_32" DOUBLE  -- 16.32,
  "n_28_91" DOUBLE  -- 28.91,
  "n_29_69" DOUBLE  -- 29.69,
  "n_1293_75" DOUBLE  -- 1293.75
);

Weather Test Timeline

@kaggle.thedevastator_solar_output_prediction_using_weather_data.weather_test_timeline

3.92 kB
753 rows
3 columns

CREATE TABLE weather_test_timeline (
  "n_27" BIGINT  -- 27,
  "n_4" BIGINT  -- 4,
  "n_2017" BIGINT  -- 2017
);

Weather Train

@kaggle.thedevastator_solar_output_prediction_using_weather_data.weather_train

147.74 kB
6,027 rows
10 columns

CREATE TABLE weather_train (
  "n_12" BIGINT  -- 12,
  "n_1" DOUBLE  -- 1,
  "n_1_85" DOUBLE  -- 1.85,
  "n_6_97" DOUBLE  -- 6.97,
  "n_6_9" DOUBLE  -- 6.9,
  "n_98_24" DOUBLE  -- 98.24,
  "n_10_92" DOUBLE  -- 10.92,
  "n_29_18" DOUBLE  -- 29.18,
  "n_29_97" DOUBLE  -- 29.97,
  "n_449_25" DOUBLE  -- 449.25
);