THE USINESS CASE FOR Drones in Energy Resources/Drone_Data_final.pdf · MEASURE.COM 03 The Case for...

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THE BUSINES S C A SE FOR

Drones in Energy Operations

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ME A SUR E INSIGHT S

Putting Drone Data to Work in Energy Operations

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The Case for Drones in Energy Operations

Today, energy companies are using drones to capture data that was previously dangerous, difficult, or expensive to obtain. Drones collect data without the use of bucket trucks or expensive scaffolding, they can cover larger areas and difficult terrain, and they are much faster than manual data collection methods. So, we know we can get lots of data more efficiently and safely than ever, but what for? What’s the benefit of this new treasure trove of data, and how do we put it to use at a large corporation?

In this paper, we’ll cover how drone data can deliver incremental value, and we’ll use the energy industry as our primary example. Measure has a long-standing partnership with AES, a Fortune 500 global power company, with whom we have worked to develop drone solutions and build their drone program from the ground up. Measure has also delivered drone data to a wide range of clients across the energy industry, including more than 1GW of solar inspection data, 2.5GW of wind turbines, 400 utility poles and towers, and countless acres of thermal generation plants and construction sites.

Recognizing that drones can collect more data more easily and safely may be pretty straightforward; however, understanding the incremental value of that aerial data and putting it to good use is an entirely different matter. Drone data may arrive in a different format, it may warrant new processing and analysis techniques, it may need to be integrated with existing systems, and it will need to be stored and referenced going forward.

This paper collects insights from previous Measure publications and adds new information and references that will help you make drone data a valuable part of your business operations.

Introduction


http://www.aes.com/home/default.aspx

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01 Drone Data: A Definition 04

02 Benefits of Drone Data 05

03 Data Program Architecture 08

04 Data in Action 12

05 A Word About Data Security 19

A Data Products Glossary 23

TA BLE OF CONTENT S


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DRONE DATA : A DEFINITION01

What is Drone Data?

Drone data typically starts out as a collection of images (usually a lot of images) that were carefully collected according to a set of specifications particular to the type of job. Those images become the key ingredient for creating something much more and what is ultimately business intelligence (or aerial intelligence in the drone industry). How do we define what makes drone data different? Drone data is:

Processed. Hundreds or even thousands of images are identified, arranged, and /or stitched together to create an organized, usable, and cohesive data set.

Measured. Drone data is often processed into data products that can be accurately geolocated and/or measured, similar to a map or computer model. Thermal imagery also enables temperature measurements.

Analyzed. With drone data, you can derive insights like classifying the severity of damage on a wind turbine blade, the degree of degradation of insulators, and whether solar panel damage is at the string, module, or sub-module level.

Tracked. Collecting data over time can show everything from progress on a construction site to the rate of increasing severity of turbine blade defects or the amount of material usage in a stockpile.

Compared. Owners of multiple energy assets can learn a lot by comparing data sets across their own sites, with other similar data sets, or against plans. Are turbines from a particular manufacturer performing better or worse than others? Does my solar plant under construction match the site plan?

Drone data is also driving advancements in artificial intelligence and predictive analytics. Very large sets of aggregated drone data will allow us to, for example, better predict when your Class 3 wind turbine blade damage will progress to a Class 4. Instead of scheduling inspections and maintenance according to a common schedule, you’ll be able to optimize based on a more detailed set of site and environmental conditions. Drone data will not only give you insights on your energy and infrastructure assets today, but also provide a look into the future.

Drone Data Products

Ultimately, drone data is used to create a drone data product. As we’ll discuss later in this paper, the relevant data product will depend on your particular use case. The variety of data products reflects the wide range of possible use cases. To help you get a better understanding of the types of data products common across the energy industry, we’ve created a data products glossary, which you can find on page 23, at the end of this paper.


Intelligent drone data can save thousands of dollars and hundreds of hazardous man-hours while providing better business information.

BENEFIT S OF DRONE DATA02

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Drone Data Improves Safety and Efficiency

Energy company AES estimates that their drone program saves 30,000 hazardous man-hours each year. That’s time not spent climbing poles, using bucket trucks, traversing difficult terrain, or exposed to extreme temperatures. Measure’s analysis of several solar inspections showed a 97% improvement in inspection time efficiency. Drones collect data faster than manual methods, while reducing risks to workers.

Drone Data is Highly Accurate

To test the accuracy of Measure’s drone inspection data, we conducted an experiment. We took the results of a solar inspection by drone and sent out manual inspection crews to run the same inspection on the same plants. The results the crews came back with from the manual inspection mirrored the results from the drone data with 99 percent accuracy, but the manual inspection took two days for each site compared to two hours with the drone.

Drone Data is More Detailed

In Wind and Transmission & Distribution (T&D) applications, drones can capture close-up, detailed imagery of potential defects that enable maintenance personnel to really see what’s going on – is the apparent damage at the surface level, or is it structural? Drones can also capture tower, pole, and turbine images from most any angle, which is often not possible with other inspection methods. In solar applications, drones spot sub-module defects that manual inspections typically miss. These improvements help asset managers make better decisions about needed repairs, thus optimizing their maintenance budgets and minimizing downtime.

Fig. 1.1 Top-down image for T&D inspections

Drone Data Can Be Manipulated for Analysis

Unlike manual inspection data which generally sits inside an inspector’s head or lives in a spreadsheet somewhere, drone data can be manipulated and analyzed from different angles. For example, with a single drone mission, you can get a clear understanding of the shading conditions of a solar site at any time of the year. During construction, you can overlay actual construction progress imagery with site plans to gauge whether construction is proceeding according to specifications.

Fig. 1.2 Measure site shading analysis


https://www.measure.com/news-insights/solar-inspection-drones-case-study

https://www.measure.com/news-insights/solar-inspection-drones-case-study

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Drone Data is Easily Consumable

For the amount of data that is processed with a typical inspection (e.g. 300 images or 3GB per wind turbine), reading and consuming the information is surprisingly easy. “The reports are pretty consolidated,” states Nick McKee, Solar Operations Manager at AES. “I have a PDF snapshot and a digital snapshot that I can move around and customize depending on what I want to look at.” Data can even be delivered through a smart phone app, allowing field maintenance personnel to proceed directly to the location of identified defects.

Drone Data Lives Forever

What many find to be the most valuable part of drone data is that it is documented and lives forever. This allows energy plants to perform year-over-year analysis and gives operations the ability to reference prior inspection data to make smart decisions about future work. Asset managers can even compare the health of equipment across multiple sites.

Documentation is especially relevant where employee turnover is prevalent. In developing industries such as Wind and Solar, the employee who performed the inspection in years prior may not still be with the company by the next time an inspection is required. With drone data, you don’t have to reference a person, only a database, to know what the last inspection picked up.


When you integrate drone data into your business operations, you’ll reap the transformative benefits of drone technology.

DATA PROGR A M A RCHITEC TUR E03

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Analyze Existing Data Architecture and Determine How Drone Data Fits In

The energy industry has always been a leader in utilizing Geographic Information Systems (GIS) and remote sensing data to monitor infrastructure and make decisions. From mapping out critical infrastructure to right-of-way management, utilities have built extensive databases of geographic information.

“We want to be a more digital and data-oriented company. The data behind drone technology supports our goal to improve overall company asset management.”- Assel Ayapova, Global Drone Program Manager, AES

One of the best ways to maximize the return on your drone inspections is to integrate drone data into your existing workflow. This requires first compiling an inventory of your existing data architecture so you can identify if you have the tools to store, process, analyze, and visualize data. Some important questions to ask when preparing to use drone data are:

• Is my organization currently using some type of remote sensing data (e.g. from satellites, manned planes, or helicopters)?

• Does my organization currently have a GIS system that can make use of drone data?

• What upgrades need to be made to accommodate this influx of new data or types of data?

Because drone data is inherently geospatial – meaning it is associated with a geographic location – often the most logical home for the data is an organization’s GIS department. However, the capability to store, process, analyze, and visualize drone data will vary significantly by organization. Even if you choose to outsource data processing and analysis, it is still imperative to determine how you will integrate the resulting data products into your business systems and workflows.

While analyzing how drone data will fit into your existing infrastructure, it is also important to determine what type of data you will be collecting, which is directly related to which applications you are looking to use drone data for. Will you be collecting data for creating maps or 3D models? Or will you be identifying defects for inspection purposes? Answering these questions will better prepare you for the next step, determining the right software for processing, analysis, and visualization.

Finding the Right Data Processing, Analysis, and Visualization Tools

Once you have evaluted your existing data architecture and determined what type of drone data you will be using, the next step is to determine what types of software or tools you need to turn that data into actionable aerial intelligence. With the proliferation of commercial drones in the marketplace in recent years, there have been many significant advances in software that can be used to process, analyze, and visualize drone data.


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First, let’s define what we mean by processing, analysis, and visualization. At Measure, we refer to these as the three main steps in preparing actionable data. The chart below defines what each step represents.

Measure’s 3 Steps to Actionable Data.

Depending on your application, you may use several different types of software to create a finished data product; there is no one-size-fits all software covering every variation of drone data. Some tools are designed to be used only for raw dataset processing, while others are only useful for analysis or visualization of processed data. Analytical tools in particular are often targeted to a specific industrial application, say, solar panel damage identification. This kind of tool would be of little use when applied to an image set from a

wind turbine inspection.

The type of software you choose may also depend on how much processing power you can access, or whether you have reliable internet. If you have very specific requirements for processing datasets and need custom settings, you will probably have to use a desktop software such as Pix4D. If you have relatively simple requirements, low data security concerns, and a decent internet connection, you may be able to use a cloud-based platform like DroneDeploy.

Since you already evaluated your existing data architecture, you will have a good understanding of your software requirements for delivering data to end users and incorporating it into your business workflows. For many of our energy clients - particularly electric utilities - that answer is ArcGIS.

Figure 3.1 summarizes just a few of the different software products used by Measure’s Data Engineering team.

When choosing software, regardless of whether you or a third-party will be creating the final data products, always keep in mind who the stakeholders of your program are and who will need access to the data. Data that is difficult for asset managers or O&M teams to access and use, for example, is not likely to maximize the return on your investment. Make sure that the processing, analyzing, and visualization of your drone data results in a data deliverable that can drive better decisions for your business operations. We’ll discuss more about how to do that in the next section.


Processing

Analysis

Visualization

Conversion of raw data into processed data products, such as 2D orthomosaics or 3D models.

Interpretation of processed data into actionable data, such as measurements, damage reports, etc.

Final step to combine all data products and analysis into a visual format.

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Finding the Right Data Processing Tools

Software Purpose Stage Type Use Cases

Pix4D Mapper PhotogrammetryProcessing, Analysis, Visualization

Desktop + Cloud

Mapping, solar inspection, 3D modeling, construction, agriculture

HangarPhotogrammetry, Documentation

Processing, Visualization

Cloud Construction

Dronedeploy PhotogrammetryProcessing, Analysis, Visualization

CloudMapping, construction, agriculture

ScopitoInspection Management

Visualization, Analysis

CloudWind turbine inspection, T&D inspection

FlirToolsThermal Image Inspection


Desktop Solar inspection

ArcGIS SuiteGIS Data Manipulation


Desktop + Cloud

Mapping, solar inspection, T&D, agriculture

AutoCAD SuiteCAD Data Manipulation


Desktop Construction

DRONE INSPEC TION SOF T WA R E 2 018

Figure 3.1 - A Guide to Data Software Tools


Figure 3.1 - A Guide to Data Software

Good data in equals good data out. Take the time to plan for quality data collection and set yourself up for success.

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Data Collection Planning

A good understanding of your data needs and use cases leads to a good plan for collecting that data. At Measure, each drone flight plan starts out in the Data Engineering department with a thorough assessment of the data requirements for the flight. Some questions we ask are:

1. What decisions will the end user be making based on this data?

2. What types of data need to be collected for the user to make those decisions?

3. What are the resolution and accuracy requirements?

4. What type of site is being inspected and how large is it?

5. What data product needs to be created?

Answering those questions will help you understand which type of aircraft, sensor, and flight path will be needed to accomplish the mission. That information should be documented in a flight plan, which should then be shared with the operations team that will be conducting the flight. It is important to jointly review the flight plan to make sure the pilots understand the mission and feel comfortable performing it, and to address any safety or regulatory concerns prior to the flight.

Also included in the flight plan should be the procedures to sort, organize, and transfer the raw data to the appropriate location. Keep in mind that data size will accumulate quickly – be prepared to store at least twice as much data as you think you will need.

Data Engineering and Flight Operations teams should work very closely to make sure every mission is properly planned and executed. For

Measure, ensuring that the right data is collected the first time is one of the most important operational considerations – right after mission safety.

Raw Data Handling and Quality Assurance Procedures

After the flight plan has been created, it’s up to the operations team to go out and collect the data. First and foremost, make sure you are following proper safety and security protocols for your organization. If dealing with critical infrastructure, ensure that all data procedures follow NERC/FERC compliance (see more about data security in the next section).

Pilots should be trained to organize data as it is collected and to sort it into folders based on flight type. It is also important to review data in the field for quality assurance before leaving the job site - the last thing you want is to have to return to a location to re-fly because of poor or insufficient data. Figures 4.2 - 4.5 are some examples of good data in the solar application.

Measure’s Data Team Processes and Analyzes:

800 Photos per MW for Solar

300 Photos per Turbine for Wind


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Figure 4.2 - Good Solar RGB Image - Panels in focus. Panels at relatively low angles. Clear panel boundaries. No noticeable glare.

Figures 4.3 - Good Solar Thermal Image - White spots represent defects.

Example Inspection Images


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Figure 4.4 -4.5 - Mapping and 3D Modeling - If using data for mapping or 3D modeling, ensure data has proper overlap by using a program such as Pix4D to load images and perform a rapid quality check.

Example Inspection Images


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Data Processing & Analysis

Once data has been captured and transferred, it should be loaded and prepared for processing. This typically involves setting up projects by site and type of data capture. After data has been processed, which can take several minutes to several hours, those data products can then be used to create actionable data insights.

Measure’s Data Processing.

Transfer data to processing

environment.

Create processing projects in

software of choice.

Process dataset from each

sensor using modified

parameters as necessary.

Export data into analysis

software of choice.

Perform analysis.

At Measure, we typically bring processed data into programs like ArcMap or Autodesk Civil 3D to perform analysis. Using software like these allows our Data Engineers to bring together data from multiple sources—access to all relevant information in one system is critical when conducting analysis.

Data Visualization

Once data has been processed and analyzed, it is time to visualize your results and share these with your colleagues, customers, and other relevant stakeholders. There are many ways to visualize data, from online portals to mobile applications. A simple PDF report is one of the most common methods that Measure customers choose to visualize and share data their data. For energy inspections, we often use ArcGIS or Scopito (see Figs 4.7-4.9) to produce an interactive webmap that can be annotated. ArcGIS data can also be delivered through a smart phone app. The most important thing is to make the information as detailed as possible while still being easy to use.

Putting Actionable Data to Use

One of the core competencies of a Data Engineering team is to understand how to make drone data usable for customers, stakeholders, and end users. This process begins at the outset of every project. Sometimes end users have a very clear and realistic idea of how they plan on using drone data, while others are just learning what the capabilities and limitations of drone data are. Our Data Engineering team spends time working with end users up front to understand what the data will be used for. Three questions we ask are:

1. Are you using drones as a replacement for existing remote sensing technologies? If so, how do you use that data?

2. Previously, how did you go about making the decisions or solving the problems that you will now use drones for?

3. Are there any systems or other software that you will be integrating the data with?

Answering these questions can help ensure the data will be of value to end users.


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Figure 4.6 - Screen shot of an interactive webmap for a solar inspection.

Data Delivery: ArcGIS


Figure 4.7 - Screen shots of an interactive webmap and in-field application (inset) for a distribution line inspection.

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Figure 4.8 - Screen shots of an interactive web portal for a wind inspection

Data Delivery: Scopito


Figure 4.9 - Screen shots of an interactive web portal for a T&D inspection.

In a conservative industry, there are naturally concerns around managing data related to critical infrastructure.

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Measure and AES have worked together to provide a data security methodology for AES’s drone program which spans 10 countries and includes more than 100 licensed pilots. Here are some of their best practices for situations where data security is a primary concern.

Data Collection

Data security involves more than behind-the-scenes technology, it also includes the data collection process. While being on the front lines with linemen, technicians, and work crews, we found that drone pilots are the crucial first line of defense with data security as they are collectors of the data. For pilots, we’ve identified these best practices for data collection:

1. Train Pilots on CEII/CIP. Training will make pilots aware if a facility or structure falls under critical infrastructure. Regular training will give pilots a comprehensive understanding of what types of data are subject to NERC/FERC regulations, which have established rules on physical and cybersecurity for critical energy infrastructure. It’s a good idea to train all staff on data security and related regulations that may relate to drone imagery.

2. Fly in Airplane or Local Data Mode. Airplane mode disconnects your device from the internet so you can properly collect and handle sensitive data prior to reconnecting to the internet. Local Data Mode, as it pertains to DJI drones, prevents communication with any DJI-hosted servers. If you do require internet access on your device while collecting drone imagery, it is best to utilize VPN software that routes and prevents or at least limits communication to

the internet via your corporate network.

3. Delete the flight application and memory cache. Deleting your flight app is good practice after every flight. You should also clear SD cards after data has been uploaded; some even go so far as to reset their device to factory defaults and triple wipe or destroy the SD card after use. Once you are sure all traces of data are removed from your device, it is safe to connect it back to the internet and reinstall your mobile flight application.

4. Avoid common data mishandling pitfalls. Don’t store or process imagery of high voltage trans lines or substation to plant imagery in non-FedRamp approved systems. Don’t snap a picture with your cell phone and text message it to your colleague or post it online.

Data Processing

For data processing, it is best to avoid 3rd party cloud processing. Measure keeps all data and servers in the AWS US – East region. However, we do occasionally have customers that need to keep data in Europe, and we can provision the system to work according to local regulations.

Data Visualization

For data visualization, we use ESRI ArcGIS as our primary map and visualization tool. When security is of utmost concern, whatever you use should be an on-premise GIS solution or should be FedRamp approved.


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Data Storage

When using on-premise data storage, ensure your network is secure. Typical corporate IT networking procedures should be in place, including proper firewalls, encryption, and VPN. As a general rule, Measure follows standards that are used by the US government.

File name is also important from a security perspective. We tackle this with a principle called “security by obscurity.” When dealing with circuits above 250kw, you should use code names to refer to those assets.

“At AES, we are laser focused on ensuring that we protect our sensitive data. Data management is a critical piece of any drone program and through our partnership with Measure, we are confident that we are protecting our data every step of the way.”- Adam Brown, Asset Management, AES

Although it is never possible to achieve 100% security, implementing layers of security at every step in the process greatly reduces risk to a manageable level.


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In this white paper, we have defined drone data and its benefits, discussed data architecture and software solutions, and outlined how a drone data program might work in a large organization. We provided suggestions to address data security concerns and examples of good drone data and easy-to-use data deliverables. Our hope is that this paper has given you a strong foundation for making drone data an integral part of your business. Drones are a new and interesting technology with many possibilities, but the vast amount of data they collect will be of little use if it can’t be distilled into business intelligence that enables better decisions within your particular organization.

If you are ready to add drone data into your business operations, Measure offers a wide range of services to help. With expert data collection, processing and analysis services, as well as turnkey operations and program management software, we can support your drone program in a way that perfectly fits your unique needs. To learn more, request a consultation by visiting www.measure.com/contact and filling out the form.

We wish you success in putting drone data to work for your business and hope you find the results to be truly transformative.

Conclusion



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3D Point Cloud – A 3D, rotatable set of data points representing an object (such as a building). Geolocated, measurable, and compatible with common design software.

As-Built Overlay – Creating 3D models or 2D orthomosaics that are then overlaid with site plans or CAD drawings to identify any discrepancies between plan and actual.

Construction Progress Tracking - Collecting aerial imagery at regular intervals to track changes over time and document milestone completions.

Defect Identification - Identification, classification, and geolocation of defects for a wide array of applications including wind turbine blades, solar panels, utility poles, boilers, stacks, and expansion joints.

DSM / DTM – A digital surface model or 2D representation of a terrain’s surface. Can be used for volumetric analysis and is convertible to CAD formats.

Erosion Assessment - Creation and analysis of topographic models to identify slope degrees and areas prone to premature erosion.

Fencing Infrastructure Review - Analysis of perimeter structures to identify compromised areas such as missing beams, corrosion, vegetation, and miscellaneous damage.

Orthomosaic – A detailed, accurate photo representation of an area, created out of many photos that have been stitched together and

geometrically corrected (“orthorectified”) so that it is as accurate as a map.

Pipeline Mapping - Aerial images stitched together to create visual and GIS data of pipelines and other transport systems.

Thermal Analysis – Using images of the heat given off by an object to identify anomalies such as malfunctioning solar modules, damaged electrical insulators, cracked expansion joints, and faulty substation components.

Topographic Map – A map of a ground area that is true to the shape and features of the surface of the earth to highlight variations in site grading.

Site Shading Assessment – Using the site’s geographical location, nearby obstructions, and seasonal sun positioning to graph potential shading impacts over the course of the year.

Solar Tracker Review - Identification and geo-location of single-axis tracking zones that are misaligned or non-functional.

Vegetation Growth Sampling – Aerial images are used to identify vegetation conditions, typically on a solar farm or along utility lines.

Volumetric Analysis - Using 2D and 3D data to estimate the volume of earthwork, cut and fill, or stockpiles. Repeated volumetric analysis of stockpiles can track inventory usage over time.

Data Products Glossary


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