This document summarizes a survey on the use of data mining in the electrical field. It discusses how data mining can be used for electricity usage analysis, consumption monitoring, and wastage reduction. The document then outlines several past studies that applied various data mining algorithms like k-means, regression trees, and neural networks to electricity consumption data. It proposes a new idea to control unconsumed electricity using sensors and a fuzzy logic algorithm to adjust light intensity based on parameters like light color, sunlight, and temperature in order to reduce electricity bills.

1. SURVEY ON USE OF DATAMINING
IN ELECTRICAL FIELD
BY:
S. ANMITA

2. AGENDA
 Electricity and its usage
 Datamining
 Datamining in machine learning
 Datamining in electricity usage
 Wastage of electricity
 Consumption of electricity
 Survey on consumption of electricity by datamining
algorithms
 New idea for electrical consumption using datamining
algorithm
 Future scope and conclusion

3. ELECTRICITY
• Electricity is the basic need for live a life shopaticated
• Electricity is a physical phenomena associated with the
presence and motion of electric charge.
• As electricity cannot be stored it need to be generated

4. USAGE OF ELECTRICITY
Theelectricityplaysmajorroleineveryfield
 Public place
 Educational institutions
 Research centres
 Medical science
 Entertainment purpose
 Agriculture
 Space research centres
 Engineering
 Sports etc..,

5. DATA MINING

6. DATAMINING
 In today’s world Data Plays Major role in various field and we mine that data
to get
Useful information for Future use
 Data mining is used to mine these data which in turns give knowledge on
the data and it can give different patterns of data
 Data mining is the step of the "knowledge discovery in databases process”,
or KDD

7. DATAMININGIN MACHINE LEARNING
• Machine learning is the field which raised out of Artificial intelligence.
• Machine learning started to grow since 1990s
• Machine learning borrowed model methods from statistics and probability theory
• It has ability to
 increase digital information
 Transmit data
Understading the concepts soon

8. DATAMINING IN MACHINE
LEARNING
Machine learning, Artificial
intelligence , Data mining are
all leaves of same tree

9. DATAMININGIN
ELECTRICITY USAGE
 Electricity market price forecasting
 Used to manage the meter Data
 Tracking end user usage paten
 Electricity load data characterization
 Electricity theft detection
 forecasting electricity prices.

10. WASTAGE OF ELECTRICITY
 Electrical consumption is proportional to
the usage of electricity
 The wastage of electricity is due to
increase in usage of electricity.
 In an electrical system losses can be
classified in to two categories technical
and non-technical.

11. WASTAGE OF ELECTRICITY
2015
58%
2016
23%
2017
10%
2018
9%
Electricity Wastage
2015
2016
2017
2018
 A day about 6%-20% transmission 4% distribution or 69
trillion buts in the world is said jordan wirfs-broks
 There are many reason to wastage of electricity due to
 Running machine in factories
 Simply switch on lights in morning
 For making foods using electrical appliances
 By charging mobile and laptops full time in a day
 By washing clothes using washing machine
 Make refrigerator on full day to store foods
 Switch on street lights in morning etc..,

12. CONSUMPTIONOF ELECTRICITY
We can consume our electricity in many Tips.
 Turn off unnecessary lights
 Use natural light
 Take shorter showers
 Ditch the desktop computer
 Avoid Use the microwave, crock pot or toaster oven
 Be efficient with refrigeration usage
We can also consume electricity by not using the above mentioned .we
can make use of data minng for efficient usage of electricity. Let move to
some survey on datamining in the field of electricity.

13. SURVEYONCONSUMPTIONOF ELECTRICITYBY DATAMINING
ALGORITHMS
Name of the Author Title of the Paper Algorithm used in
paper
year
1.Bikash sharma Application of data
mining, management of
performance
and power in Data
centres
Nearst neighbour,
Navie Bayes,
CART,
Regression Tree,
k-means and
Logistic
regression
_
2. konstantincs blazakis,
Darazani,Georgios,
Loana -pisica
Lesson learn from
mining meter of
residential consumer
k-means
PDA(Principal
Component Analysis)
2016

14. Name of the Author Title of the paper Algorithm used in
paper
year
3.Ali Darudi Masoud
Bashari
Electricity forecasting
using a new Data fusion
algorithm
Data fusion algorithm 2015
4..Xin -Lu,,Xeu LI,
Zhao yang Dong
Electricity market price spike
fore-Cast with
data-Mining technique
fuzzy neutral auto -
regression ,SDI,RDI 2005
5. Jian deng Modelling and prediction on
china's electricity
consumption using neutral
networking.
Error back-propagation
Algorithm. 2010

15. Name of the
Author
Title of the paper Algorithm used
in paper
year
Noorrollah Karimtabar
and Sadegh
Analysis and predicting
electricity consumption
Using datamining
techniques
Regression mode
prediction 2015
7. Hiroyuki
moki and Akira
Awata
Datamining of
electricity price
forecasting
with regression tree
and normalization
NRBFN.
NRBFN
2007
Many researchers have made their research in this field they have used different data
minig teechniques for mining electricity data

16. NEW IDEA FOR ELECTRICAL CONSUMPTION USING
DATAMINING ALGORITHM
Limitation in survey
they are able only to cluster or classify the data.
The above given survey authors focus only consumed data by different data technique that
is not efficient
Our idea is to controlling unconsumed data by sensor these leads to reduce electricity bill
through bulbs

17. PROBLEMSTATEMENT
can define main three problems for increase electricity bills by bulbs
1. switch on lights in morning or full day
2. switch on the bulb due to darken painting for the wall.
3. absence of windows make to switch on the bulb
We can overcome these by using sensors

18. NEW IDEA FOR ELECTRICAL CONSUMPTION USING
DATAMINING ALGORITHM
• In these concern our ideas is to determine the parameters such as
• Colour of the light
• Amount of sunrays
• Temperature of the room
By using the sensors it determine the intensity of the light by vagueness in fuzzy algorithm
FUZZY data mining algorithm. Fuzzy logic is used in data mining .Fuzzy logic is a form of
many-valued logic in which the true variables are real numbers between 0 and 1 .The values
range between completely true or false.

19. NEW IDEA FOR ELECTRICAL CONSUMPTION USING
DATAMINING ALGORITHM
• Fuzzy logic is used in data mining
• Fuzzy logic is a form of many-valued logic in which the true variables are real numbers
between 0 and 1 .The values range between completely true or false.
Usally,
if(intensity= =high)
room will bright
break
if(intensity= =low)
room will dark
These leads to increase electricity bill,. By sensors using prediction concept in fuzzy logic
algorithm the sensors measure intensity of light and bring output according to paint and
temperature.

20. FUTURE SCOPE
Our idea future scope will work as
These sensor fixed in wall .
It start to passes signals from sensor to bulb.
The bulb blinks according to the sunlight rays, room temperature and colour of
the wall.
These process reduces the electricity bill due to less watt output from the bulb.

21. CONCLUSION
A day a light release many kilowatts in a day
876 kilowatt - per day. The costs
kilowatt hour - 15cents
Hope our idea should reduce electricity bill
through bulbs IN FUTURE