# Solar Power Generation Data¶

https://www.kaggle.com/anikannal/solar-power-generation-data
There are a few areas of concern at the solar power plant:

• Can we predict the power generation for next couple of days? -> this allows for better grid management
• Can we identify the need for panel cleaning/maintenance?
• Can we identify faulty or suboptimally performing equipment?
Exploration of this dataset with several weird data values, and other oddities, that lead to finding some issues with the hardware of a plant. Further digging leads us to a conclusion: plant X has systemic problems.

### Features:¶

• SOURCE_KEY -> Source key in this file stands for the inverter id.
• DC_POWER -> Amount of DC power received by the inverter (source_key) in this 15 minute interval. Units - $kW\left(h/4\right)$$kW(h/4)$.
• AC_POWER -> Amount of AC power generated by the inverter (source_key) in this 15 minute interval. Units - kW(h/4).
• DAILY_YIELD -> Daily yield is a cumulative sum of power generated on that day, till that point in time.
• TOTAL_YIELD -> This is the total yield for the inverter till that point in time.
• AMBIENT_TEMPERATURE -> This is the ambient temperature at the plant.
• MODULE_TEMPERATURE -> There's a module (solar panel) attached to the sensor panel. This is the temperature reading for that module.