1 Title A method for estimating electricity consumption cost based on data received from an electricity meter 5 Technical Field The invention concerns a method for estimating electricity consumption cost based on data received from an electricity meter. Background of the Invention io 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, 15 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. 20 Summary of the Invention In a first aspect there is provided a method 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 method comprising: 25 retrieving electricity usage data from a database, said electricity usage data being received from an electricity meter; and using a processor to: calculate based on said retrieved usage data an average hourly electricity consumption cost for a predetermined number of 30 previous days; 2 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 5 current billing period; 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 io multiply the result with the average hourly electricity consumption cost to provide an 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 15 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. The predetermined number of previous days may be 7. 20 In a second aspect there is provided 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 comprising: 25 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 electricity consumption cost for a predetermined number of 30 previous days; 3 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 5 current billing period; 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 io multiply the result with the average hourly electricity consumption cost to provide an 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 15 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. The device may comprise a touchscreen display to enable user 20 interaction to display the estimated electricity consumption cost from the current time to the end of the current billing period. Throughout this specification, including the claims, the words "comprise", "comprising", and other like terms are to be construed in 25 an inclusive sense, that is, in the sense of "including, but not limited to", and not in an exclusive or exhaustive sense, unless the context clearly requires otherwise. Brief Description of the Drawings 30 An example of the invention will now be described with reference to the accompanying drawings, in which: 4 Figure 1 is a series of images of a touchscreen display of an In Home Display device for displaying electricity consumption to a consumer. 5 Detailed Description of Preferred Embodiments 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 io 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 15 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 20 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: 25 Data Definition: Tperiod is the billing period in terms of number of days Dstart is the start date of this current billing period DToday is the date of today 30 BDate is the estimated bill up to now 5 Scharge is a daily fixed service charge in the unit of cents per day RFeedin is the price that the electricity company buys solar generated electricity from consumers 5 CAppliancesis the estimated cost up to now by standby appliances Then, the estimated bill to date is calculated as: 10 BDate = ((DToday - Dstart) * Scharge) + A(Ui * Pi) i=1 ... now 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 15 the In-Home Display device. For determining standby appliances cost CApplances following process is performed: 20 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. 25 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 Uk (Day 1) = Min (Day 1(U;)) where k= 1..10 and j=1..48 30 CAppliances(Day 1) = (2 Uk(Day 1) * Pk(Day 1)) * 24/5 CAppliances(Day 2) = (2: Uk(Day 2) * Pk(Day 2)) * 24/5 6 CAppliances(Day 7) = (I Uk(Day 7) * Pk(Day 7)) * 24/5 5 Step 3: Calculate the average daily cost used by the standby appliances as; Av (CAppliances) = C CAppliances(Day i)/7 where i 10 =1.. 7 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. 15 Step 4: Calculate the estimated cost of the electrical appliances in standby mode during the billing period as: CAppliances = A v (CAppliances) * Tperiod 20 To determine the estimated cost up to now, the following is changed: Tperiod to (DToday - Dstart). The estimated bill, Bperiod, to the end of billing period is predicted by: 25 Bperiod = BDate + Bpredict + (Tperiod * Scharge) where Bpredict is the predicted bill from now to the end of the bill period which is determined by a bill prediction algorithm. The 30 predicted bill is displayed on a second screen 11 of the In-Home 7 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: 5 Av. Bhourly = (2:j 2i (Ui * Pi) ) / (7*24) i = 1.. 48 and j = 1..7 A v. Bdaily = (2j 2i (Ui * P) )/7 i = 1.. 48 and j 10 =1..7 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. 15 Then Bpredict= (Tperiod - Ttoday) * Av. Bdaily + (24 - The Current Hour) * Av. Bhourly Turning to Figure 1, the various views of estimated bill and usage are 20 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 25 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.
8 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 5 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 io 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 15 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 20 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 9 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 10:00 0.25 kwh 10:30 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 10 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 calculate the average consumption of 5 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 io 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 15 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. 20 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 25 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.
11 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. Bhourly = (0.30+0.25+0.10+0.09+ ...... + 0.30+0.28_0.28) / 5 48 - 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. Bhourly values. These 7 io different Av. Bhourly values are then averaged to provide an average hourly consumption cost which will be used to calculate Bpredict. Assuming that the time period from the current day to the end of billing period is 3 days and 10 hours, then 15 Bpredict = ((24 X 3) + 10 hours) * Bhourly Bpredict includes standby appliances cost + non-standby appliance cost. 20 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 25 illustrative and not restrictive.