of 193 Step 1: Generate the initial state of each system component enforcing that all components

are normal. The initial load state is generated by randomly sampling a starting time in a year and selecting the corresponding load level from the load profile.

Step 2: Sample the transition time from the current state to the next possible state for each component using the transition rate in normal condition. The transition time for the load state is obtained by calculating the time to the next half hour boundary.

Step 3: A HILP event starts when the first fault is identified in the network (recorded as T0). The failure rate and repair time for all components are increased by applying HILP factors. The transition time of each component is then resampled with the increased rates.

Step 4: Evaluate load point curtailment for each system state using the proposed implicit switching model as described in this thesis.

Step 5: Sort the list of transition time and find the next transition state, update transition time list using the method introduced in Chapter 2, section 2.4.2.

Step 6: Repeat step 4-5 until the system simulation time exceeds T0+48h (the 48h can vary for sensitivity study). If at t=T0+48h, there exist failures in the network, the simulation will continue until all faults are repaired.

Step 7: Evaluate and record the reliability indices of the system for the HILP event. Repeat the simulation for statistic results.

Page 100 of 193 TABLE 4-7 CASE STUDY PARAMETERS

Parameters Values

Failure rate for overhead lines (%/km.year) 10

Switching time (minutes) 30

Restoration time (hours) 24

Section length (km) 2

Peak demand of each load point (kW) 500

Loading level N-0

HILP failure factor 10, 50

HILP repair factor 2, 5, 10

Emergency generator preparing time (h) 3, 24

Emergency generator supply rate 25%, 100%

Value of Lost Load (£/MWh) 17,000

HILP event duration (h) 48

The studies have been carried out on a HV distribution network shown in Figure 2-1. The studies assume that each HV section has installed disconnectors on both sides. This allows any single circuit fault to be isolated and supply restored in switching time which reduces the supply interruption. The 11 kV network is designed as a radial network with a normally open circuit breaker (NOP) that connects the two main feeders for back-feeding during contingencies. The part of the network affected by the fault(s) can be isolated by opening the corresponding switchgear and the affected load points can be resupplied by the adjacent branch. At each load point, a distribution transformer is connected.

The studies have been carried out using the year-round load profile with 30-min time resolution.

Results

Time-sequential Monte Carlo method is conducted to model the impact of HILP events on network reliability performances. The results of the studies are presented in Table 4-8. It is worth noting that, the “event” for EENS/cost is referring to the whole period of a HILP situation lasting for 48h or longer until all faults are repaired. Therefore, here the “event” is not an outage or interruption, it is possible to have multiple faults overlapping but also possible that there is no fault/interruption in the network for a short while.

Page 101 of 193 TABLE 4-8 SYSTEM RELIABILITY AND COST PERFORMANCES UNDER VARIOUS HILP AND PROVISION OF EMERGENCY SUPPLY SCENARIOS

Network Reliability _HILP No HILP FRx10 HILP FRx50 HILP MTTR x1 x2 x5 x10 x2 x5 x10 No emergency supply EENS (MWh/event) 1.33 3.2 5.1 11.6 15.4 55.2 157.8 Cost of EENS (k£/event) 22.6 54.4 86.7 197.2 261.8 938.4 2,682.6 25% emergency supply rate 3h EENS (MWh/event) 1.29 2.5 3.3 7.4 9.8 33.4 111.2 Cost of EENS (k£/event) 21.9 42.5 56.1 125.8 166.6 567.8 1,890.4 24h EENS (MWh/event) 1.33 2.9 4.3 9.2 13.2 39.6 126.5 Cost of EENS (k£/event) 22.6 49.3 73.1 156.4 224.4 673.2 2,150.5 100% emergency supply rate 3h EENS (MWh/event) 1.26 1.6 1.8 1.8 3.2 4.7 5.7 Cost of EENS (k£/event) 21.4 27.2 30.6 30.6 54.4 79.9 96.9 24h EENS (MWh/event) 1.32 2.6 3 4.2 11.1 19.2 27.2 Cost of EENS (k£/event) 22.4 44.2 51 71.4 188.7 326.4 462.4

Table 4-8 shows the results of case studies for distribution network reliability with different HILP factors and emergency supply. Expected Energy Not Supplied (EENS) and cost of ENS are computed to summarise the reliability performance and related cost of HILP events. It can be seen that under normal weather conditions, i.e. no HILP event, the EENS for each failure event is relatively low, in the range between 1.26 MWh (with emergency supply) and 1.33 MWh (without emergency supply). The improvement of EENS due to the emergency supply is relatively modest, i.e. 0.06 MWh or £1.2k cost savings. Marginal improvement of the EENS performance and the small benefit obtained indicate that the emergency supply may not be justified in normal conditions.

When a HILP situation happens, the failure rate of network components increases by 10 or 50 times of the original and repair time is prolonged to 2, 5, 10 times of the original as 2 days, 5 days, 10 days (as high impact may cause significant damage to overhead lines that would require long repair times). If no emergency supply is available, the system EENS can be as high as 157.8 MWh/event and the corresponding cost is £2.68m/event for a case with the HILP

Page 102 of 193 failure factor of 50 and the repair factor of 10. The system EENS increases when the failure rate goes up and repair time increases. If emergency supply is available in the HILP event, the system EENS can be significantly reduced. For example, for a case with the HILP failure factor of 10 and the repair factor of 2, the EENS in a case with no emergency supply is 3.2 MWh and with the emergency supply, it can be reduced down to 1.6 MWh, i.e. a reduction of 50%. The improvement is considerably higher for a severe HILP event. For a case with the HILP failure factor of 50 and the repair factor of 10, the EENS with emergency supply is down to 5.7MWh which is merely 4% of the original 157.8 MWh, saving £2.58m for reducing the duration of supply interruptions. Considerable improvement of the EENS performance and the savings obtained indicate that the emergency supply is an effective method to mitigate the impact of HILP situations.

In order to show more clearly the impact of HILP with different severity, the reliability performances of the system for cases with HILP failure factor of 10 and 50 are compared in