Simulations for Effective Outage Management Utilizing Metering

In this subsection, required information for simulations including distribution system model, presumptions, outage scenarios and visualization approach are discussed for effective outage management utilizing metering data.

Distribution System Model Creation (1)

Figure 5-10 shows the radial distribution system model created to conduct simulations.

Figure 5-10 Distribution System Model

The double circles icon in the left hand side means a distribution substation and HV distribution line starts from the substation to customer areas. The HV line has three load buses and each load bus has pole transformers which supply electric power for households.

The number of connected pole transformers to each load bus and households to each pole transformers were defined referring to the distribution system model for residence in [5-16]. Topologies for cabling from a pole transformer to each household are not defined in this research because more frequent metering data collection should be required in order to recognize this level of failures. Parameters for the model are showed in Table 5-3.

Table 5-3 Parameters for the Distribution System Model

Item Value Description

Area 1 km² 1km 1km

Population 900 Population Density: 900/km²

Households 360 Average people per household: 2.5/household Pole Transformers 60 Households per Transformer: 6

Overview of Simulations and Data Preparation (2)

Assuming that smart meters were fully installed in the area, how data collection fault information would be recognized was simulated. In the simulation, a center system

conducts metering operations regularly for virtual smart meters defined in the system model, and data collection faults would be detected if meters had fault flag in their data.

Each meter has its location and connected pole transformer information, and each pole transformer has its connected load bus information. In addition, the following assumptions were defined for the metering simulations.

Metering interval in each meter: 30 minutes

Data collection (transfer) method from each meter:

Data collections (transfers) from meters are distributed with multiple metering groups in consideration of data traffic leveling.

The number of metering group: 60 (Data collection interval: 30 seconds) Metering group for each meter defined randomly

All data collection (transfer) faults in the simulation are due to outage occurrences.

(Faults due to communication errors do not consider in this simulation.) Table 5-4 shows the part of meter property data.⁴

Table 5-4 Partial Meter Property Data Meter

Number Metering

Group Location Connected

Pole Trans. Connected Load Bus xcoord. ycoord.

1 12 10 10 1 B1

2 20 10 15 1 B1

3 25 10 20 5 B1

4 10 10 25 5 B1

5 38 10 30 9 B1

6 6 10 35 9 B1

7 13 10 40 13 B1

8 42 10 45 13 B1

9 31 10 50 17 B1

10 11 10 55 17 B1

11 60 10 60 41 B3

12 29 10 65 41 B3

13 1 10 70 45 B3

14 26 10 75 45 B3

15 18 10 80 49 B3

16 46 10 85 49 B3

17 54 10 90 53 B3

18 50 10 95 53 B3

19 11 10 100 57 B3

20 7 10 105 57 B3

4 Complete data are provided in Appendices D

Outage Patterns (3)

The followings are outage occurrence patterns discussed in this research in consideration of failure locations.

a. Failures in Low Voltage Distribution Line, Service Line and Consumer-side Because network structures from pole transformers to consumers are not considered in this system model, detailed failure location predictions using topology information for these areas are not conducted. However, about 70 75(%) of trouble calls are single service outages, and over a third of them are customer problems 0, therefore the cause confirmation method for single service outage need to be considered.

b. Failures from Load Buses to Pole Transformers

In this pattern, data collection fault would occur only for smart meters connected to a certain pole transformer. Through simulations, it should be discussed how this type of outage would be recognized by metering fault information.

c. Failures in HV Distribution Line

In failures at HV distribution line, data collection from all smart meters which are located on downstream of the failure point would be failed.

Proposed Visualization Approach (4)

In order to support the prediction of outage occurrence locations, some visualization approaches are proposed.

a. Visualized Icons for Smart Meters, Pole Transformers and Load Buses

Figure 5-11 shows icons for distribution assets and devices used to visualize the status of them on the distribution system model.

Figure 5-11 Smart Meters, Pole Transformers and Load Buses

Small green boxes show smart meters and double circles show pole transformers.

Smart meters in a same color and line type box are connected to the same pole

transformer located in the center of the box. In order to identify data collection fault meters, the color for the smart meter icons would be changed from green to red. Wide lines on HV distribution line mean load buses and each line has the bus name and the same color as connected pole transformers.

b. Visualization of Data Collection Status

If data collections for multiple meters connected to a same pole transformer would be failed, the probability of outage occurrence in the area under the transformer would increase corresponding to the number of data collection fault meters. Therefore, if the number of data collection fault meters connected to the same transformer could be showed on the area map visually, high probability areas of outage occurrence should be apparent and the

Figure 5-12 Visualization Method of Data Collection Status for Smart Meters Connected to the Same Transformer

Figure 5-13 Visualized Distribution System Model

Figure 5-12 shows a visualization image of data collection status for smart meters grouping by each same connected transformer. The color of the box also would be changed from white to red corresponding to the number of data collection fault meters. With this visualization approach, an outage under a pole transformer should be recognized easily and the accuracy of outage prediction might increase. The distribution system model using these icons is showed in Figure 5-13.