Help us get to know you better by answering these four short questions

This is the easiest way to get a sense of which module is the right fit for your network and to learn how to optimize your expenses

Step 1
Step 2
Step 3
Step 4
Result

What are you most interested in?

Increasing network reliability

Reducing maintenance and operational expenses

Better planning for new equipment deployment, replacement, or upgrades

How 'smart' is your network?

Fully deployed AMI and SCADA System automation of large portions of the network

Somewhat completed AMI and SCADA systems, but still completing a few projects

Just getting started on the smart grid journey

What is the primary focus for your network over the next few years?

Preparing for new grid edge technologies, e.g. EVs, more local renewable generation, more at-home storage, etc.

Maintaining and upgrading our existing infrastructure

Bringing new large generation sources online

Other

What is the most difficult problem or problems with using your data currently?

The data is stored in too many places and hard to retrieve

Data is of poor quality or incomplete

The volume of data is too large for our existing systems to fully utilize

We are using the data somewhat, but applications are scaling poorly

Based on your inputs, we suggest

Transformer Module

Please select all the data types you are currently collecting ^required

DGA

Power Readings

Voltage Readings

Maintenance Records

Asset Data (make, model, install date)

Annual planned maintenance cost ^required

.00

Annual unplanned maintenance cost (additionally to planned) ^required

.00

Average engineering salary ($/yr)^required

.00

Hours of total engineering time/week spent on this analysis ^required

Current reliability metrics (SAIDI, SAIFI, etc) ^required

What maintenance approach do you use 1^required

Cost Savings:
Improved Metrics:
Expected Savings: ^*
* Estimated Savings of Implementing this Module on Your Network.

These are the expected results based on the answers you provided:

We’ve calculated the average improvement of your results based off your current maintenance approach compared to the results we’ve achieved with other similar utilities.
Some data is more valuable than other data; the type and quality of data significantly impacts our predictive model.
We expect that you will reallocate your current resources for predicting asset failure to other valuable projects.

Assets are maintained on a fixed schedule
Asset maintenance is prioritized by reading(s) taken as a proxy for condition or inspection
Asset maintenance is prioritized by incorporating available information into a risk algorithm driven by machine learning

Cable Predictive Health Module

Please select all the data types you are currently collecting^required

Line Events (outages, failures, etc)

Circuit Topography

Power Readings

Voltage Readings

Maintenance Records

Asset Data (make, model, install date)

Annual planned maintenance cost ^required

.00

Annual unplanned maintenance cost (additionally to planned) ^required

.00

Average engineering salary ($/yr)^required

.00

Hours of total engineering time/week spent on this analysis ^required

Current reliability metrics (SAIDI, SAIFI, etc) ^required

What maintenance approach do you use 1^required

Cost Savings:
Improved Metrics:
Expected Savings: ^*
* Estimated Savings of Implementing this Module on Your Network.

These are the expected results based on the answers you provided:

We’ve calculated the average improvement of your results based off your current maintenance approach compared to the results we’ve achieved with other similar utilities.
Some data is more valuable than other data; the type and quality of data significantly impacts our predictive model.
We expect that you will reallocate your current resources for predicting asset failure to other valuable projects.

Assets are maintained on a fixed schedule
Asset maintenance is prioritized by reading(s) taken as a proxy for condition or inspection
Asset maintenance is prioritized by incorporating available information into a risk algorithm driven by machine learning

Blink Module

Please select all the data types you are currently collecting^required

Smart Meter Events

Grid Outages Records

Asset Connectivity Data

Hours of total engineering time/week spent on this analysis^required

Average engineering salary ($/yr)^required

.00

Current Spending:
Expected Cost:
Expected Savings: ^*
* Estimated Savings of Implementing this Module on Your Network.

Based on the information you provided, GridCure can help:

The Blink module will greatly simplify identifying previously undetected outages.
Reduce the costs of any existing analytical processes involving blinks.
Completely automate MAIFI reporting work.

Please choose one of the options above

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