Storm recovery data acquisition

Storm recovery data acquisition

William Lowder
Florida Power & Light

Jerry Cooley
Datria Systems, Inc.
7211 South Peoria Street, #260
Englewood, CO 80112

Storm recovery data acquisition

The Objective
Provide an acceptable means for storm survey (easier than paper or menu based systems)

Get the right answers faster. The right answer means less wasted effort and crew expense. The faster you get the answer the sooner your customers can be back on line.

The Problem
The timeliness and quality of damage estimates have a significant affect on outage recovery times and costs.

Paper surveys require hours of subsequent data entry. Traditional menu-based surveys are difficult to use in the field. Both provide very limited information due to the time constraints imposed by the emergency.

These limitations cause damages to be over-estimated costing millions in unnecessary manpower and equipment imported from surrounding areas.

The sooner accurate information is known the sooner crews can be requested, assembled, transported, staged and deployed.

Once deployed crews must relocate damages when accurate locations are unknown.

The Question
Would speech-enabled data collection capabilities allow surveyors capture vital information faster than filling out paper forms or navigating menus? Can real-time DGPS allows surveyors to see where they are and where they've been so they don't get lost and don't miss sections of data? Are post processing data entry delays eliminated?

The Answer
The objective in the SRR is to determine as quickly and accurately as possible the types and locations of facilities that are damaged.

Current method:

The SRR patrol person receives a paper map of the area he is to survey.
Next finding his patrol area can be a significant challenge. He may not be from the area, he may not have any street signs to work from and devastation may have eliminated most landmarks. After Andrew one FPL employee searched over two hours for his own house.
The patrolman then walks or drives the feeder making notes on the paper map of what needs to be replaced or repaired. The notes are located on the map relative to their real world positions, but specific damage locations do not get transferred when the data is transcribed at the control center.
Upon completing his patrol, he returns to the control center and turns in his paper notes. These notes go into a stack of notes to be entered along with every other patrol person's. It may take up to 24 hours before this data is available on line.

Proposed method:

The patrolman has an area map overlaid with his feeder map loaded into his VoCarta unit
Using the interactive map and GPS, the patrolman would drive to the area he needs to survey. He would know his current position and the position of the feeder while driving to the area. This will eliminate many problems caused by lack of local area knowledge or missing street signs and landmarks.
The patrolman then walks or drives the feeder voicing in the items that need to be replaced. VoCarta picks up a GPS location for each of these items and automatically measures the length of down feeder.
While the patrolman is returning to the control center, VoCarta processes the data he has collected. At the control center he checks the data and uploads it into the master database. His data is available for immediate use.

Results
After two days were spent simulating a Storm Recovery patrol, walking and a driving collection metric are displayed below. Each collection covers the entire distance between two switches.

Collection Type	Time (Hr)	Distance (M)	Distance (Mi)	# Of Facilities to be replaced	Length of Conductor Down (Ft)
Walking	0.75	1,583.70	0.98	12	560
Driving	0.17	2,780.00	1.73	15	1708

The next table is from the walking collection and is an example of what would be imported into the existing SRR Lotus Notes application. This data would be available for import within 30 minutes of the field computer returning to the office. The software would be configured to import this data automatically once the field unit is connected to the network.

Underground Riser	Single Phase Three Phase	1 1
Services Completely Replaced	N/a	1
Poles	45/2	4
Fuse Blown	N/a	1
Transformer	25 KVA Single Phase	4

The pilot of the speech-to-data method demonstrated the feasibility speech enabled data collection for Storm Recovery.

Summary
Storm Recovery can be transformed to a much more efficient process as shown by the results verified in the pilot:

Paper Storm Recovery	VoCarta Storm Recovery
1. SRR forms are difficult to learn	Prompts & teaches the form as you go.
2. SRR forms are difficult to use	No writing required. Just see it and say it.
3. Difficult to locate the correct section.	GPS highlights the section next to you.
4. Not familiar with area, no signs, lost.	Never lost, always see where you are on map.
5. Rain and wind interfere with collection.	No wet papers to deal with.
6. The second man in the truck can't keep up.	You can call data out 3-5x faster to VoCarta.
7. Dozens of people entering data all night.	This step and its inaccuracies are eliminated.
8. No discreet locations of specific damages.	Damaged equipment shown on map and tallied.

These efficiencies have the following economic value for FPL:

Accurate SRR information in 36 hours instead of 5 days allows SRR to be utilized as a crew forecasting tool which can save FPL $50,000,000 in crew and equipment over-reaction costs.
With the GPS locations of specific damages SRR data can be used by GIS to generate best routing for repair crews to expedite truck loading, arrival at feeders and order of repairs along the feeder. Better preparation and routing improves productivity by 15-30% in most cases.
A 15% productivity improvement shaves 5 days off 33 days of repair. A 10% damage area hurricane disrupts FPL's $18,000,000 daily cash flow by $1,800,000 per day. Five days represent $9,000,000 in cash flow.

Conclusion
FPL has the opportunity to utilize new technology to change the rules and the paradigm it was previously constrained by. The new capabilities made possible by this technology allow FPL to make leaps forward in its four areas of focus:

Cost
VoCarta reduces daily costs by improving field inspection crew productivity today while improving FPL's asset maps to dramatically reduce future maintenance response times.

Economical streetlight location and verification reduce collection costs by $450,000 while accelerated collection of unbilled revenue produces an extra $7,500,000 in the next two years

Storm recovery costs may be reduced by $50,000,000 based on greater speed and more accurate/mapped data from SRR providing better damage estimates earlier with better response routing of repair crews.

Better deployment and routing of repair crews after a category 4 hurricane could reduce repair time by a week, reducing repair costs while reestablishing cash flow sooner. A one week improvement could save FPL $10,000,000 in repair and $9,000,000 in cash flow.

Quality
Better location and accounting of assets in the field allow FPL to better respond to its own growth needs as well as its emergency outage needs.

Customer Orientation
Better response times and maintenance improve customer satisfaction with FPL's ability to deliver services that satisfy their electricity-related needs.

Speed & Flexibility
With accurate GPS location of vault access, pads, poles, transformers and lights FPL crews can locate and deploy maintenance crews faster. With accurate maps of damaged assets included with SRR information provided days earlier FPL has the flexibility to tailor its response rather than gross overestimation which is the only alternative without good timely field data to ground-truth estimates.