Australian Solar Data Analysis

Analysis Project
FieldsBig Data Analytics
TimelineJanuary 2, 2018 - March 23, 2018
StatusCompleted
TeamPandu RR KonalaD.Arvind SaiK.Sai Chaitanya
ToolsMongoDBMicrosoft Excel

Overview

To analyze various types of data concerning solar power plants and the factors which affect them. Through Big Data procedures this is made possible to break down the causes of uproar in the services of the solar power plant and reveal some thought-provoking actualities.

Motivation

Most countries around the world have high ambitions in terms of the deployment and integration of renewable energy generation capacities. Power systems and electricity markets were originally designed for conventional and centralized power generation, while near-future systems are set to rely on distributed and non-dispatchable generation. This introduces substantial challenges in operation and data analysis.

Key Findings

  • Power Generation is Proportional to Wind Speed
  • Power Generation is Proportional to Radiation
  • Power Generation is Inversely Proportional to Humidity
  • Power Generation is Inversely Proportional to Rainfall

Data Statistics

  • Maximum temperature recorded: 51.26°C
  • Maximum Humidity: 102.89 g/m³
  • Maximum global horizontal radiation: 2725.60 W/m²
  • Maximum Rainfall: 67.199 mm
  • Maximum wind speed: 54.39 Kmph
  • Active power peak: 3.67kW

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