NZ620322B2 - A method for estimating electricity consumption cost based on data received from an electricity meter - Google Patents
A method for estimating electricity consumption cost based on data received from an electricity meter Download PDFInfo
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- NZ620322B2 NZ620322B2 NZ620322A NZ62032212A NZ620322B2 NZ 620322 B2 NZ620322 B2 NZ 620322B2 NZ 620322 A NZ620322 A NZ 620322A NZ 62032212 A NZ62032212 A NZ 62032212A NZ 620322 B2 NZ620322 B2 NZ 620322B2
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- electricity consumption
- consumption cost
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- 230000005611 electricity Effects 0.000 title claims abstract description 84
- 230000002354 daily Effects 0.000 claims abstract description 21
- 230000003993 interaction Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000005265 energy consumption Methods 0.000 description 3
- 238000000034 method Methods 0.000 description 3
- 230000003203 everyday Effects 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000000875 corresponding Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006011 modification reaction Methods 0.000 description 1
Abstract
620322 Disclosed is a device for estimating electricity consumption cost from a current time to an end of a current billing period based on usage data received from an electricity meter. The device comprises a database for storing electricity usage data received from the electricity meter, and a computer processor. The computer processor is configured to calculate, based on the retrieved usage data, an average hourly electricity consumption cost for a predetermined number of previous days. The processor is also configured to calculate, based on the retrieved usage data, an average daily electricity consumption cost for the predetermined number of previous days. The processor then calculates the number of days remaining until the end of the current billing period and multiplies the number of days remaining with the average daily electricity consumption cost to provide an estimate of electricity consumption cost for remaining days of the current billing period. The processor also subtracts the hour of the current time from twenty-four and multiplies the result with the average hourly electricity consumption cost to provide an estimate of electricity consumption cost for remaining hours in the current day. The processor is configured to then add the estimate of electricity consumption cost for remaining hours in the current day to the estimate of electricity consumption cost for remaining days of the current billing period to provide an estimated electricity consumption cost from the current time to an end of the current billing period. This estimated cost may be presented to a user on a display of the device. omputer processor. The computer processor is configured to calculate, based on the retrieved usage data, an average hourly electricity consumption cost for a predetermined number of previous days. The processor is also configured to calculate, based on the retrieved usage data, an average daily electricity consumption cost for the predetermined number of previous days. The processor then calculates the number of days remaining until the end of the current billing period and multiplies the number of days remaining with the average daily electricity consumption cost to provide an estimate of electricity consumption cost for remaining days of the current billing period. The processor also subtracts the hour of the current time from twenty-four and multiplies the result with the average hourly electricity consumption cost to provide an estimate of electricity consumption cost for remaining hours in the current day. The processor is configured to then add the estimate of electricity consumption cost for remaining hours in the current day to the estimate of electricity consumption cost for remaining days of the current billing period to provide an estimated electricity consumption cost from the current time to an end of the current billing period. This estimated cost may be presented to a user on a display of the device.
Description
Complete Specification
Title: A method for estimating electricity consumption cost based on
data received from an electricity meter.
A method for estimating electricity consumption cost based on data
received from an electricity meter.
Technical Field
The invention concerns a method for estimating electricity consumption cost
based on data received from an electricity meter.
Background of the Invention
As energy costs are increasing and growing environmental concerns there is
a desire for energy consumer such as households and businesses to monitor
their energy consumption on a real-time basis and estimate the resultant cost
of such consumption when the next electricity bill is issued by the utility
company. With this information, energy consumers are able to monitor their
energy consumption and intelligently decide various factors such as choice of
electrical products to buy, and the frequency and schedule of using their
electrical products.
Summary of the Invention
In a first preferred aspect, there is provided a method for estimating electricity
consumption cost of electrical appliances in standby mode, the method
comprising:
calculating daily energy usage of electrical appliances in standby
mode by averaging energy usage for a predetermined number of time
intervals having the lowest values in a single day; and
calculating an average daily energy usage of electrical appliances in
standby mode by averaging the calculated daily energy usage of electrical
appliances in standby mode for a predetermined number of previous days.
The predetermined number of time intervals may be 48 half-hourly time
intervals for a single day.
The predetermined number of previous days may be 7.
In a second aspect there is provided a method for estimating electricity
consumption cost from the current time to the end of the current billing period
based on usage data received from an electricity meter, the method
comprising:
calculating an average hourly electricity consumption cost for a
predetermined number of previous days;
calculating an average daily electricity consumption cost for the
predetermined number of previous days; and
calculating the number of days remaining until the end of the current
billing period and multiplying the number of days remaining with the average
daily electricity consumption cost, and subtracting the hour of the current time
from twenty-four and multiplying with the average hourly electricity
consumption cost.
The predetermined number of previous days may be 7.
In a third aspect there is provided a device for estimating electricity
consumption cost of electrical appliances in standby mode, the device
comprising:
a computer processor configured to perform:
calculating daily energy usage of electrical appliances in
standby mode by averaging energy usage for a predetermined number of
time intervals having the lowest values in a single day; and
calculating an average daily energy usage of electrical
appliances in standby mode by averaging the calculated daily energy usage
of electrical appliances in standby mode for a predetermined number of
previous days; and
a memory to store the estimated electricity consumption cost of
electrical appliances in standby mode.
The device may comprise a touchscreen display to enable user interaction to
display the estimated electricity consumption cost of electrical appliances in
standby mode.
In a fourth aspect there is provided a device for estimating electricity
consumption cost from the current time to the end of the current billing period
based on usage data received from an electricity meter, the device
comprising:
a computer processor configured to perform:
calculating an average hourly electricity consumption cost for a
predetermined number of previous days;
calculating an average daily electricity consumption cost for the
predetermined number of previous days; and
calculating the number of days remaining until the end of the
current billing period and multiplying the number of days remaining with the
average daily electricity consumption cost, and subtracting the hour of the
current time from twenty-four and multiplying with the average hourly
electricity consumption cost; and
a memory to store the estimated electricity consumption cost from the
current time to the end of the current billing period.
The device may comprise a touchscreen display to enable user interaction to
display the estimated electricity consumption cost from the current time to the
end of the current billing period.
Brief Description of the Drawings
An example of the invention will now be described with reference to the
accompanying drawings, in which:
Figure 1 is a series of images of a touchscreen display of an In-Home
Display device for displaying electricity consumption to a consumer.
Detailed Description of the Drawings
Referring to Figure 1, an In-Home Display device for displaying electricity
consumption to a consumer is connected to an electricity meter of a house.
The electricity consumption and the electricity price are collected at a regular
time interval and stored in the internal database of the In-Home Display
device. Other data stored in the internal database of the In-Home Display
device are user defined and can be changed to suit the needs of the
household. For example, the user can set the bill period to either Monthly or
Bi-Monthly or Quarterly to monitor their usage history. Other user defined
variable charges include the Supply Charge and the Feed-in Charge.
The standby appliances cost refers to the electricity charges consumed by
electrical appliances in the house that are in always-on mode. These
electrical appliances include: the refrigerator, the television set, computers
and network routers. Several sets of data with minimum consumption are
taken, which are then used to compute the estimated standby appliances
cost.
For bill prediction, the following process is performed:
Data Definition:
T is the billing period in terms of number of days
Period
D is the start date of this current billing period
Start
D is the date of today
Today
B is the estimated bill up to now
Date
S is a daily fixed service charge in the unit of cents per day
Charge
R is the price that the electricity company buys solar generated
Feedin
electricity from consumers
C is the estimated cost up to now by standby appliances
Appliances
Then, the estimated bill to date is calculated as:
B = ((D - D ) * S ) + ∑(U * P ) i=1… now
Date Today Start Charge i i
where U and P are the power consumption and price of electricity at each
half hourly interval. This is displayed on a first screen 10 of the In-Home
Display device.
For determining standby appliances cost C following process is
Appliances
performed:
Step 1: Retrieve the past 7 days consumption (U ) and price (P ) data from
the database of the device. Since the In-Home Display device records
consumption data at every half an hour interval, there are 48 consumption
and price data points every day.
Step 2: For each day of the past 7 days data, 10 data points are identified
which are the minimum energy consumption out of the entire 48 data points
U (Day 1) = Min (Day 1(U )) where k= 1..10 and j=1..48
k i
C (Day 1) = (∑ U (Day 1) * P (Day 1)) * 24/5
Appliances k k
C (Day 2) = (∑ U (Day 2) * P (Day 2)) * 24/5
Appliances k k
C (Day 7) = (∑ U (Day 7) * P (Day 7)) * 24/5
Appliances k k
Step 3: Calculate the average daily cost used by the standby appliances as;
Av (C ) = ∑ C (Day i)/7 where i = 1.. 7
Appliances Appliances
If the database has less than past 7 days data, for example 3 days, the
calculation will be based on 3 days data rather than 7 days data.
Step 4: Calculate the estimated cost of the electrical appliances in standby
mode during the billing period as:
C = Av (C ) * T
Appliances Appliances Period
To determine the estimated cost up to now, the following is changed:
T to (D - D ).
Period Today Start
The estimated bill, B to the end of billing period is predicted by:
period,
B = B + B + (T * S )
period Date predict Period Charge
where B is the predicted bill from now to the end of the bill period which
predict
is determined by a bill prediction algorithm. The predicted bill is displayed on
a second screen 11 of the In-Home Display device. The predicted usage is
displayed on a third screen 12 of the In-Home Display device. The bill
prediction algorithm is:
Calculate the average hourly and daily bill for the past 7 days as:
Av. B = (∑ ∑ (U * P ) ) / (7*24) i = 1.. 48 and j = 1..7
hourly j i i i
Av. B = (∑ ∑ (U * P ) ) / 7 i = 1.. 48 and j = 1..7
daily j i i i
If the database has less than past 7 days data, for example 3 days, the
calculation will be based on 3 days data rather than 7 days data.
Then
B = (T - T ) * Av. B + (24 – The Current Hour) * Av.
predict period today daily
hourly
Turning to Figure 1, the various views of estimated bill and usage are shown.
The currency of the estimated bill can be adjusted according to the region the
In-Home Display is provided.
The in-home display device shows the total amount of electricity consumed
by the house. The in-home display is connected to the Energy Service
Interface (ESI) which is located into the electricity meter in most
embodiments. The ESI builds up the entire Home Area Network for other
devices to join such as gas meter, and in-home display.
An assumption is made on what appliances is in standby mode by assuming
that the household will not leave appliances in ON/ACTIVE states when the
occupants are not at home or using them. It is assumed that the household
will not actively use all the electrical appliances in their home for all 24 hours
in a day (i.e. sleeping or out of the house). 48 data items are recorded in the
in-home display every day because the in-home display records electricity
consumption at every half an hour interval. Based on the assumption
described, the lowest value in the recorded 48 data items should reflect the
standby appliances electricity usage. However, one data item (i.e. the lowest
value data item) does not provide enough accuracy for the prediction of
standby cost. Therefore, the 10 data items with the lowest values out of the
48 data items are selected and these 10 data items are then averaged to
provide a more accurate estimation of standby appliances cost of a single
day. Also, because electricity consumption may differ on different days (i.e.
public holidays, weekends and weekdays), in order to obtain an ever more
accurate prediction, the standby appliances cost of the past 7 days is
calculated and then averaged to obtain a final prediction cost for the current
day.
A worked example of the 48 data items corresponding to electricity
consumption recorded from yesterday is as follows:
Time electricity Remarks
consumption
00:30 0.30 kwh electricity consumption of the house
from 00:00-01:00 is 0.3 Kilo Watts per
Hour
01:00 0.25 kwh
01:30 0.20 kwh
02:00 0.10 kwh data (1)
02:30 0.09 kwh data (2)
03:00 0.10 kwh data (3)
03:30 0.10 kwh data (4)
04:00 0.09 kwh data (5)
04:30 0.08 kwh data (6)
05:00 0.09 kwh data (7)
05:30 0.10 kwh data (8)
06:00 0.15 kwh
06:30 0.15 kwh
07:00 0.25 kwh
07:30 0.25 kwh
08:00 0.25 kwh
08:30 0.25 kwh
09:00 0.25 kwh
09:30 0.25 kwh
:00 0.25 kwh
:30 0.09 kwh data (9)
11:00 0.09 kwh data (10)
11:30 0.30 kwh
12:00 0.30 kwh
12:30 0.30 kwh
. 0.30 kwh
23:30 0.28 kwh
24:00 0.28 kwh
From above consumption table, we first of all find out the ten lowest 10 min.
data which are indicated (i.e. data(1) … data(10) in the remarks
column. Then, we calculation the average consumption of these data,
((0.1*4)+0.09*5+0.08)/10 = 0.093 kwh. We repeat above procedure to
calculate last 2, 3….7 day values. Then make an averages of these data to
predict today’s standby appliances cost. The eKo in-home display device
implements and executes this algorithm. The results are the 3 views
including estimated usage and estimated bill are displayed on the display of
the “in-home display device.
The in-home display device is a standalone device which connects to a
Zigbee Home Area Network. The prediction screens are all shown in a
standalone in-home display devices. However, these algorithms can be
expended to a USB stick in-home display device in which a USB stick is
connected to a PC with an internet connection. In such an embodiment, the
estimated usage and bill can be displayed via an Internet browser.
In the bill prediction, two different costs are predicted: standby appliances
cost and the cost of the entire electricity bill. Standby appliances cost is
subset of the entire electricity bill. The reason of finding the standby
appliances cost is to let users know how much the appliances spend on the
standby mode. Therefore, there are two separate screens to show this
information to customers. The purpose is to let users understand more on
their electricity consumption behaviour.
To estimate the entire electricity bill including standby cost and active
appliances cost using the same worked example above, the average half
hour cost for yesterday is:
Av. B = (0.30+0.25+0.10+0.09+ ……….+ 0.30+0.28_0.28) / 48 –
hourly
Equation 1
This provides an average of the 48 data items from yesterday
Equation 1 is repeated for the 7 previous days. For each of the 7 previous
days, there are 7 different Av. B values. These 7 different Av. B
hourly hourly
values are then averaged to provide an average hourly consumption cost
which will be used to calculate B .
predict
Assuming that the time period from the current day to the end of billing period
is 3 days and 10 hours, then
B = ((24 X 3) + 10 hours) * B
predict hourly
B includes standby appliances cost + non-standby appliance cost.
predict
It will be appreciated by persons skilled in the art that numerous variations
and/or modifications may be made to the invention as shown in the specific
embodiments without departing from the scope or spirit of the invention as
broadly described. The present embodiments are, therefore, to be
considered in all respects illustrative and not restrictive.
WE
Claims (2)
1. A device for estimating electricity consumption cost from a current time to an end of a current billing period based on usage data received from 5 an electricity meter, the device comprising: a database for storing electricity usage data received from the electricity meter; and a computer processor configured to: calculate based on said retrieved usage data an average hourly 10 electricity consumption cost for a predetermined number of previous days; calculate based on said retrieved usage data an average daily electricity consumption cost for the predetermined number of previous days; calculate the number of days remaining until the end of the current billing period; 15 multiply the number of days remaining with the average daily electricity consumption cost to provide an estimate of electricity consumption cost for remaining days of the current billing period; subtract the hour of the current time from twenty-four and multiply the result with the average hourly electricity consumption cost to provide an 20 estimate of electricity consumption cost for remaining hours in the current day; and add the estimate of electricity consumption cost for remaining hours in the current day to the estimate of electricity consumption cost for remaining days of the current billing period to provide an estimated electricity consumption 25 cost from the current time to an end of the current billing period.
2. The device according to claim 1, wherein the device comprises a touchscreen display to enable user interaction to display the estimated electricity consumption cost from the current time to the end of the current 30 billing period.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
NZ620322A NZ620322B2 (en) | 2012-10-25 | A method for estimating electricity consumption cost based on data received from an electricity meter |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
NZ603246A NZ603246B (en) | 2012-10-25 | A method for estimating electricity consumption cost based on data received from an electricity meter | |
NZ620322A NZ620322B2 (en) | 2012-10-25 | A method for estimating electricity consumption cost based on data received from an electricity meter |
Publications (2)
Publication Number | Publication Date |
---|---|
NZ620322A NZ620322A (en) | 2015-07-31 |
NZ620322B2 true NZ620322B2 (en) | 2015-11-03 |
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