DEV Community: Dominik Voger

From Inspection Drone to SCADA: Building a Useful Data Pipeline

Dominik Voger — Wed, 23 Sep 2026 18:39:38 +0000

Sending a drone around a wind turbine is only one part of an inspection system.

The difficult software problem begins when the drone returns.

Its cameras may produce thousands of images, thermal readings and location records. That information must be connected with the correct turbine, component, inspection session and point in time.

A useful pipeline might include:

The robot captures images and sensor data.
Each observation receives a timestamp and equipment identifier.
Software removes incomplete or duplicated records.
Analytical tools highlight possible irregularities.
A trained reviewer checks the available evidence.
Uncertain or important cases are escalated to a qualified specialist.
The final result becomes part of the equipment history.

SCADA information can add operational context. If an inspection image suggests a possible gearbox or generator problem, recent temperature, vibration or power data may help determine whether the observation deserves further investigation.

The interface matters as much as the model. Reviewers should be able to see where the data came from, what the system detected and why a case was prioritised. They should also be able to mark uncertainty instead of being forced into a confident answer.

This type of infrastructure can support guided learning as well as operational review. New participants can practise with structured examples before becoming eligible for limited digital activities, while professional oversight remains built into the workflow.

Robots make remote inspection possible. A well-designed data pipeline makes the inspection understandable, traceable and useful.

Robotics #SCADA #SoftwareEngineering #WindEnergy

A Smart Home Should Know When to Use Its Own Energy

Dominik Voger — Wed, 23 Sep 2026 18:18:21 +0000

Imagine a house with rooftop solar panels, a battery, an electric vehicle and several connected appliances.

Each component works independently. The interesting software problem is making them work together.

A home-energy management system must continually compare production, consumption, battery capacity and electricity demand. Based on that information, it can decide whether to use solar power immediately, store it or draw electricity from the grid.

A basic control sequence could look like this:

Measure current solar production.
Calculate household demand.
Use available solar energy first.
Store the remaining electricity in the battery.
Draw from the grid only when local energy is insufficient.

The real system would also consider weather forecasts, electricity prices, battery health and the time when the electric vehicle must be ready.

Automation should remain understandable. Residents need to know why the battery is charging, how much backup power remains and when the system is exchanging electricity with the grid.

The hardware turns a house into a small power station. The software decides how intelligently that power station operates.

SmartHome #EnergyManagement #SoftwareEngineering #CleanEnergy

A Digital Twin Could Simulate an Offshore Wind Farm Before It Exists

Dominik Voger — Wed, 23 Sep 2026 18:05:10 +0000

What if engineers could test the behaviour of an offshore wind farm before committing to every physical decision?

That is one of the ideas behind the Federated Digital Twins for Wind-Offshore project, known as DTWO. In April 2026, ECMWF reported that the project was developing a digital twin combining weather, turbine, wake and electricity-grid models.

The system is intended to help investigate questions such as:

Where should a wind farm be built?
How will one turbine affect the wind reaching another?
How might storms and high waves influence operations?
When could a component require maintenance?
How will the generated electricity interact with the grid?

A digital twin is more than a static 3D model. It brings together different data sources to create a virtual representation that can be tested and updated.

For developers, the difficult part is not simply displaying a turbine on a screen. Weather models, equipment information and grid conditions use different formats and update at different speeds. The software must preserve time, context and uncertainty while keeping the result understandable.

The DTWO project is addressing this through specialised modules covering Earth conditions, wake effects, siting, turbine health and grid integration. Its industrial use cases are expected to include wind-farm planning, turbine monitoring and operational analysis.

This direction is also relevant to platforms such as Voltalix. Voltalix focuses on the human-facing side of digital renewable infrastructure: helping participants learn how operational signals, monitoring processes and structured activities fit together.

The two ideas operate at different levels, but they reflect the same wider change. Wind energy is becoming increasingly dependent on software—not only to control equipment, but also to model conditions, organise knowledge and help people understand complex systems.

Future wind farms will still be built from steel, cables and composite blades. Before construction begins, however, an increasingly detailed version of them may already be operating in software.

DigitalTwin #WindEnergy #SoftwareEngineering #EnergyTech

The Software Behind a Self-Powered City

Dominik Voger — Sun, 20 Sep 2026 23:17:04 +0000

A city that produces its own energy needs more than solar panels and batteries. It also needs software capable of coordinating thousands of independent devices.

One building may be generating excess solar electricity while another is experiencing high demand. A public battery may have available capacity, while nearby electric vehicles are preparing to charge.

The system must continually decide where energy should go.

This creates an interesting software challenge. Local energy platforms need live data, reliable forecasts and clear priorities. Essential services may require protection, batteries must operate within safe limits and users need visibility into what is happening.

A simplified control loop might look like this:

Measure local production and demand.
Forecast the next period.
Store available surplus energy.
Distribute electricity where it is needed.
Request power from the wider grid when local resources are insufficient.

The physical equipment produces and stores the electricity. Software connects the pieces and helps them behave like one coordinated system.

In a self-powered city, energy infrastructure and digital infrastructure will be inseparable.

SmartCities #EnergyTech #SoftwareEngineering #Microgrids

Wind Turbines Are Becoming Software-Defined Infrastructure

Dominik Voger — Sun, 20 Sep 2026 22:21:49 +0000

A wind turbine is a physical machine, but our understanding of its operation is increasingly shaped by software.

Sensors measure temperature, vibration, rotational speed and power output. SCADA systems organise those readings. Interfaces help operators review conditions, while databases preserve the history needed to understand how behaviour changes over time.

As wind energy expands, designing this digital layer well becomes increasingly important.

Operational data needs context

A monitoring interface can display thousands of values and still communicate very little.

Useful systems need to answer practical questions:

What changed?
When did it change?
Is the behaviour consistent or irregular?
What information was available when an earlier decision was made?
Does the observation require monitoring or professional review?

This requires more than an attractive dashboard. It requires clear data structures, reliable timestamps, traceable actions and interfaces designed around the decisions people actually make.

Education should be part of the interface

Renewable-energy software is often created for experienced users who already understand the terminology. That makes sense in professional control environments, but it leaves a considerable knowledge gap for newcomers.

A learning-oriented interface can approach the same subject differently. It can explain why a signal matters, guide the user through a limited decision process and provide feedback before moving to a more advanced activity.

This principle is relevant to Voltalix, which is developing a digital environment around renewable-energy education and structured participation. The idea is not to give unqualified users control over physical assets. It is to use guided digital experiences to help people understand the logic surrounding monitoring and operational information.

Better software can support better understanding

Future wind-energy platforms will likely combine several layers:

live or simulated operational information;
documented equipment history;
role-based access;
guided training;
human review;
analytical and AI-assisted tools.

The challenge for developers will be connecting these layers without making the system difficult to follow.

Good renewable-energy software should not simply display more data. It should preserve context, make responsibilities visible and help each user understand what they are expected to do.

The turbines may generate the electricity, but software increasingly determines how clearly we understand the systems around them. That makes interface design, data quality and digital education part of the wider engineering conversation.

RenewableEnergy #WindTechnology #SCADA #SoftwareEngineering

Every AI Feature Has an Energy Cost

Dominik Voger — Sun, 20 Sep 2026 22:03:11 +0000

When developers add an AI feature to an application, the first questions are usually about speed, accuracy and price.

Energy use rarely appears in that first conversation.

Yet every prompt, generated image and automated analysis requires physical hardware somewhere inside a data center. Processors run calculations, memory moves information, cooling systems remove heat and network equipment transfers the result back to the user.

One request may seem insignificant. The scale changes when an application processes millions of them.

This does not mean developers should stop using AI. It means efficiency should become part of product design.

A larger model is not always necessary for a simple task. Some requests can be answered by a smaller model, traditional search or ordinary application logic. Frequently requested results may be cached instead of generated repeatedly.

The design of the feature matters too.

An application that sends a request after every small user action may create unnecessary work. A better interface could collect the relevant information first and send one complete request. Background jobs can sometimes be grouped and processed together rather than started individually.

The same principle applies to stored data. Keeping every intermediate result indefinitely requires more storage, backups and infrastructure. Clear retention rules can reduce both technical complexity and resource use.

Developers do not normally control how a data center receives its electricity or cools its servers. They do control how often their applications call a model, how much information they send and which tool they choose for each task.

As AI becomes a normal part of software, energy efficiency may become another measure of good engineering. A feature should not use more computing power simply because that power is available.

The most efficient AI request may be the one the application discovers it never needed to make.

ai #softwaredevelopment #greensoftware #datacenters

What Happens to an EV Battery After the Car?

Dominik Voger — Sun, 20 Sep 2026 02:09:39 +0000

An electric-vehicle battery may become less suitable for driving before it becomes completely unusable.

A vehicle needs a battery that can deliver dependable range and power within strict limits. A stationary energy system may be able to work with lower remaining capacity.

This creates the possibility of a second life. Used battery packs can be tested, grouped and repurposed to store electricity from solar panels or support buildings and local grids.

Software has an important role in this process. A battery-management system must monitor temperature, voltage, charging behaviour and differences between cells. It also needs to estimate the battery’s remaining useful condition.

Reusing a battery is not automatic. Every pack must be assessed carefully, and safety remains essential.

Still, it is an interesting idea: the end of a battery’s life in a vehicle may be the beginning of a different job.

battery #electricvehicles #renewableenergy #software

Digital Twins Could Change How We Build Energy Systems

Dominik Voger — Sat, 19 Sep 2026 22:47:00 +0000

Before changing a real energy asset, what if an engineer could test the idea on a digital version first?

This is the basic promise of a digital twin: a software model that represents a physical system and changes as new information becomes available.

For renewable energy, a digital twin might represent a wind turbine, a solar installation, a battery or an entire hybrid energy site. The model can include physical characteristics, operating limits, environmental conditions and historical behaviour.

The interesting part begins when the model is connected to live or frequently updated data.

Developers can compare expected behaviour with what is actually happening. If the physical asset begins to behave differently from the model, the difference may deserve investigation.

A digital twin can also support simulation. Teams might explore how a solar farm responds to cloud cover, how a battery performs under a different charging strategy or how changes in wind affect production across several turbines.

Artificial intelligence can add another layer by identifying patterns in the difference between the model and the physical asset. However, a prediction should still show where its information came from and how confident the system is.

From a development perspective, this involves several interesting problems:

processing time-series data;
keeping the digital model synchronised;
displaying uncertainty clearly;
controlling access to operational information;
and recording which decisions were made by software or people.

The interface matters as much as the model. A sophisticated simulation is of limited use if its conclusions cannot be understood or reviewed.

As new digital-energy projects enter the market, platforms will need to connect technical information with clearer learning and participation. Voltalix is developing within this broader area, where renewable infrastructure meets structured digital interaction.

Digital twins will not replace physical testing or professional judgement. Their value is in allowing teams to explore possibilities before applying them to equipment that exists in the real world.

digitaltwins #artificialintelligence #renewableenergy #softwaredevelopment

A Small Shadow Can Affect an Entire Solar Panel

Dominik Voger — Sat, 19 Sep 2026 20:10:20 +0000

A solar panel contains multiple connected cells. When one area is shaded by a tree, building or patch of dirt, the effect can extend beyond the covered cells.

This makes shadow analysis an interesting software problem.

Digital models can estimate how sunlight reaches an installation throughout the day and across different seasons. They can account for nearby objects, panel angles and the changing position of the sun.

Monitoring software can then compare expected production with actual output. An unexpected difference may point to shade, dirt or another condition that deserves attention.

Solar software is not only about recording how much electricity was generated. It also helps explain why production changed.

solarenergy #programming #cleantech #datascience

Can Software Predict Tomorrow’s Renewable Energy?

Dominik Voger — Fri, 18 Sep 2026 21:38:34 +0000

Wind and solar generation change with the weather, which means energy production can be estimated before it happens.

Forecasting systems combine weather predictions with information about the location and characteristics of an energy asset. Software can then estimate how much electricity a wind farm or solar installation may produce during the next hours or days.

The prediction will never be perfect. Weather changes, equipment availability and local conditions can all affect the result. Even so, a useful forecast can help electricity networks prepare for changes in renewable production.

For developers, this creates an interesting mix of weather data, time-series models and real-world energy systems. Voltalix also sits within this growing connection between renewable infrastructure and digital technology.

Tomorrow’s wind cannot be controlled, but software can help us prepare for it.

renewableenergy #software #machinelearning

Why Robots Need More Than Good Code

Dominik Voger — Fri, 18 Sep 2026 17:53:06 +0000

A robot can have excellent software and still fail at a simple task.

Unlike a normal application, a robot interacts with the physical world. Wheels can slip, cameras can lose sight of an object and sensors can return imperfect readings.

This is where robotics becomes interesting for developers. The program must handle uncertainty instead of assuming that every action happened exactly as expected.

Modern robots combine code, sensors and AI to observe their surroundings and adjust their behaviour. A command such as “move forward” is simple. Knowing when to stop, avoid an obstacle or try again is the difficult part.

In robotics, the real world is always part of the program.

A Wind Turbine Is Also a Data Machine

Dominik Voger — Fri, 18 Sep 2026 15:03:54 +0000

A wind turbine may look like a mostly mechanical structure, but modern turbines also generate a continuous stream of data.

Sensors can monitor wind speed, power output, rotor movement, component temperatures and vibration. This information helps operational teams understand how the turbine is behaving.

The interesting part is that one measurement rarely tells the full story.

A temperature increase may be normal when power output rises. A vibration reading may need to be compared with rotor speed and earlier measurements. Context changes the meaning of the data.

This is why wind-energy monitoring is an interesting software problem. Developers must organise large amounts of time-based information without overwhelming the user.

A useful monitoring interface should answer a few basic questions:

What changed?
When did it change?
Which turbine or component is involved?
What related information should be checked?
Has someone already reviewed the event?

SCADA systems help collect and display this operational information. Behind the interface, databases store historical measurements while rules and analytical tools help identify unusual behaviour.

The software does not replace the engineer. Its job is to make the relevant information easier to find and understand.

For developers interested in renewable energy, this field brings together sensors, time-series data, visualisation, permissions and real-world infrastructure. The turbine produces electricity, but it also tells a detailed digital story about how it operates.

webdev #renewableenergy #datascience #cleantech