01
Status
Completed
FIELDS
Big Data Analytics
START DATE
Tue, January 2nd 2018
END DATE
Fri, March 23rd 2018
02
Overview
To analysis various types of data concerning solar power plant 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 also reveal some thought-provoking actualities.
03
Abstract
The solar industry has grown considerably in the last few years. This larger scale has introduced more problems as well as possibilities. One of those possibilities is examining the data coming from the sites that are now being monitored, and using the information to answer a diverse of questions that promote the use of renewable energy sources mainly solar energy. Since the data output is massive, we need to use the Big Data Practices to enhance and embraces the data to do that Mongo DB is the right choice and for illustration Microsoft Excel is a flawless tool.
04
Motivation
Most countries around the world have high ambitions in terms of the deployment and integration of renewable energy generation capacities. Such a rapid increase in renewable energy penetration comes with technical, economical and regulatory challenges. Power systems and electricity markets were originally designed for conventional (say, thermal, nuclear and hydro-based) and centralized power generation, while near-future systems are set to rely on distributed and non-dispatchable generation as triggered by the deployment of renewable power generation capacities. these produce energy with nearly-Zero marginal cost according to nature’s will, the inherent characteristics of being highly variable and of limited predictability. This introduces substantial challenges in the operation of power systems and electricity markets and also execution of Data Analysis is hard since it produces a huge chunk of data every second which is the matter in the early ’20s. Since the advent of technology and rapid up-gradation of the hardware market, the resource of computing and analyzing the data produced by the renewable energy source is quite cheap. Hence our motivation is to investigate the huge volume of data that helps us to increase efficiency and safeguarding the future.
05
About Data Set
The Desert Knowledge Australia Solar Centre (DKASC) is a demonstration facility for commercialized solar technologies operating in the arid solar conditions of Alice Springs, Central Australia. A standard and automated metering system has established the performance data from the DKASC as an invaluable source of long-term system-level data. This information is collected at a resolution that confirms the reliability of solar technologies and logs power quality information that is relevant to the growth of large solar power stations in Australia. The system data is available for download from the Historical Data page of the website. It is contributing to the development of solar technologies in Australia and worldwide.
06
Conclusion
These results indicate, that the power generation detailed in the data is affected by major factors like humidity, rainfall and wind speed. Given the multiple and diverse foreseen applications of the dataset, we consider it outside the scope of this manuscript to attempt a full evaluation of the dataset’s efficiency for various applications. Instead, we focused to identify caveats and limitations for their use case, to provide visualization for the people to evolve and understand the importance of renewable energy i.e., Solar Energy and the factors that affect them.
• 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
From the Analysis, we can conclude the following:
• Maximum temperature recorded: 51.26 C
• Maximum Humidity recorded: 102.89 g/m3
• Maximum global horizontal radiation recorded: 2725.60 W/m²
• Maximum diffuse horizontal radiation: 2134.98 W/m²
• Maximum Rainfall recorded: 67.199 mm
• Maximum wind speed recorded:54.39 Kmph
• The active power is 3.67kW which was recorded when the radiation was high.
07
Members
• Pandu Ranga Reddy Konala
• D.Arvind Sai
• K.Sai Chaitanya