ENERGY MANAGEMENT SYSTEM

Client Overview

The Client is a Microgrid developer Company which aims at creating a sustainable and economic ecosystem for developing micro-grids. Rising Energy prices are a major deterrent to developing economic microgrids. They were looking for an Energy Management System that can lower Energy Prices. As a pilot project, the client entrusted us with a Big Data Analytics solution for a specific area comprising of 2 Lakh LED lights. The aim was to find ways to save energy and monitor power consumption made by these light poles and also some ATM counters in the same vicinity. By leveraging the crucial information thus collected from this analytical solution, the company will be able to reduce power wastage.

Business Solution

To help combat this problem we developed a Big Data Analytics Solution. To collect the required data each of these 2 Lakh poles are fitted with four sensors each, and these sensors send 168-bitstreams. All put together these sensors are sending 8-10 GB of data every day, regarding power consumption. This string from server store needs to be transferred to the Database to be analyzed.

We further break the string into our format and need to pass this string to calculate which energy unit is working unnecessarily. All this data once stored and collected on the Hadoop Data Storage is processed to conduct 250 jobs per day. Each job takes about 2-5 hours.

This Big Data Analytics platform provides the client with:

Real-Time Analytics

Light units that are functioning during the day
Air Conditioning Units running inside ATM counters beyond necessary hours.

Predictive Analytics

Which light units will need to be replaced in near future
Which light units will consume more electricity than others based on the result of this Analytics, this Solution helped the Client take required actions to Reduce Energy Consumption

Technological Solution:
The solution consists of 6 nodes:

18 Computers
4 Servers with 64 GB RAM, 6 GB Hard Disk and Octa Core Processor
2 Client-Side server with 24 GB RAM, 2 TB Hard Disk and Quad Core Processor

Predictive Analytics
In just one year the client could save 25-30% Energy
Rs. 10 Crore was saved regarding Energy Costs
Overhead Costs for the client came down by 9.48%
The Client now wishes to implement this solution over a broader geographic base.

The Client now plans to implement this project on a large scale all over the State.