Smart Meters and in-home display units are used to identify the critical house loads for possible adjustments. It helps customers to easily identify the loads and take actions to minimize their electricity cost and help retailers to protect the network from overload and voltage violations. The in-home display unit will have a panel of eight indicative lamps representing selected eight controllable appliances such as water heaters (WH), Air Conditioners (AC), swimming pool pump (PP), electric vehicles (PEV), dish washers (DW), clothes washers (WA), and dryers (DR). The detailed appliances model used during the simulations are in Appendix A. The loads which can be adjusted will be indicated when the price goes higher than the normal consumption level. So, customers can easily spot the loads to be disconnected.The appliance selection procedure for indication is shown in the algorithm as in Fig. 4.7 which is discussed in detail at the end of this section. It is easier for the customers to manually control their appliances based on the indication. Initially the three parameters such as adjustability, operational characteristics and preferred order of the
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controllable appliances are calculated for five minute time interval. Then the appliances are arranged in ascending order according to the choice list and then the algorithm will indicate the appropriate appliances for possible load adjustments. 4.4.1. Adjustability (X1ij)
The parameter adjustability for each appliance in a house will depend on their characteristics. Some appliances can be shifted any time during the day and it has the highest adjustability. A normalized value is obtained for the adjustability of jth appliance in ith house as in (4.5). The dish- washer, clothes washer and dryer have a very low adjustability because they cannot be stopped during operation and if it is stopped, it should start again from the beginning to complete the cycle. The calculation of adjustability is in Table 4.1.
ij X hrs time available total time of range adjustable ity Adjustabil 1 ) 24 ( (4.5)
4.4.2. Customer preferred order of appliances (X2tij)
Customer preferred order (X2tij) specifies the need of appliance at a particular
time t according to the priority of appliance usage. A normalized value is obtained by using the total number of loads.
Table 4.1 Adjustability and Preferred Order of Appliances
Appliances SW PEV AC WH DW WA DR
Adjustable range (hrs) 21 17 17 12 5 5 5
Adjustability 0.9 0.7 0.7 0.5 0.2 0.2 0.2
Priority order 7 3 6 1 2 4 5
Preferred Order 0 0.57 0.1 0.85 0.71 0.43 0.29 For example, water heater has the highest priority in ith house at tth time. So, 0.85(=1-1/7) is the preferred order of the water heater as shown in Table 4.1. Desired values of adjustable range of time and preferred order of appliances (as in Table 4.1) can be obtained from a customer survey and values are fixed for each peak day. The authors of [110] show that electricity consumption exhibits strong cyclic patterns over time. Hence, customer given data can be used for deciding load curtailment for a specific season. Further, customer data can be validated by observing power
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consumption profile of each customer appliance before implementing this scheme. The power consumption profile of each appliance in a house exhibits priority of them during peak hours. It also shows time range of appliance usage. Fig. 4.6 illustrates the preferred order of three selected houses for all appliances.
Fig. 4.6 Appliance Preferred order House 1, phase A, feeder 1 at 1900hrs 4.4.3. The operational state of appliances (X3tij)
Operational state of appliances depicts actual state of appliance compared to desired state of it at a certain time instance. It is different for each appliance and changes with time. Operating statuses of each appliance are calculated based on Table 3.5 in Chapter 3.
The price signals are sent to the houses every five minutes. Selection of appliance for indication should depend on the above three parameters. A customer choice value is calculated as in (4.6) for this purpose. (i.e. the selection should happen with maximum adjustability, minimum preferred order and minimum operational state. Details of appliance selection algorithm are shown in Fig. 4.7.
,(1
),(1
)
average
1ij 2tij 3tijt
ij
x
x
x
Choice
(4.6)The choice value is used in the algorithm for appropriate load indication. The load indication in each house in the network can happen as shown in the algorithm in Fig. 4.7. Initially, the appliance list is prepared automatically according to the choice value at each house and at each time interval, when the price goes above the limit. If the first price signal goes high due to excess power consumption, the loads in the
1 2 3 0 0.2 0.4 0.6 0.8 1 House number P re fe rr e d O rd e ra t 0 7 3 0 h rs SW PEV AC WH DW WA DR
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choice list is selected to match the excess power in that house (i.e. the appliances resulting excess power in a house will be indicated in the order of choice list). When the wholesale price increases, the total excess load in the network is recognized and divided among those houses which are consuming above the average of 1.5kVA. Furthermore loads relevant to voltage violations are identified using (4.7) as an offline process.
Start
Observe Price
Is price of this ith house is above a threshold value?
Observe Choiceit for all appliances Yes
Time t=0
Arrange appliances at house i according to order
House i=1
Eti exc=max (Eti exc1, Eti exc2, Eti exc)
Yes End No t i Choice
Indicate appliances whose power is close to
Eti exc in choice order for ith house
House i=i+1
No Is t<24*60
minutes? No
Calculate excess energies by
Eti exc1={(Eti-Ei lim) (if L>Lcapacity),else 0} Eti exc2={(Eti-Ei avg)(if P2it>0),else 0} Eti exc3={ΔEit(if P3it>0),else 0}
Is House i=N? Yes
t=t+5
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(4.7) Where, Nv is the number of houses with voltage violations; ΔVk is the voltage
violation below the limit of 0.94 p.u. in kth house. ΔPit is the excess power in ith house
at tth time.