Training course · n8n · Energy & Utilities

n8n for the Energy Sector

Workflow automation with n8n and AI: master nodes, the AI Agent node, integrations and GDPR-friendly self-hosting in practice.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“n8n for the Energy Sector” is a hands-on course for roles such as Staff at municipal utilities and energy suppliers, Grid operators in planning, connections and operations and Customer service and billing teams. Rather than learning n8n in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Energy & Utilities.

n8n is a flexible workflow automation platform that combines visual flows with language models and hundreds of integrations. Unlike many cloud services, n8n can also be self-hosted, so your data can stay in your own data centre or with a European hosting provider. Over two days you will learn how triggers, nodes and data flows fit together, how to transform data between applications and how to automate recurring tasks from your day-to-day work reliably.

The core of the course is the combination of automation and AI. Using the AI Agent node, chat models, memory and tools, you build workflows that classify emails, summarise documents, enrich records or answer enquiries. You learn to catch errors, test workflows and document them properly. Finally, you look at hosting options, credential management and data protection, so that your automations run stably, securely and in line with GDPR once they go into everyday operation.

The energy sector is undergoing a deep transformation: distributed generation, grid expansion, sector coupling, new market roles and dense regulation are reshaping municipal utilities, grid operators, suppliers and energy service providers alike. Generative AI helps above all in managing complexity. It summarises regulatory decisions and legislative changes, answers customer enquiries about billing, tariffs or grid connections efficiently, unlocks technical documentation and prepares project documents for permits. AI agents can support market communication processes, pre-sort fault reports or automate reporting. Because critical infrastructure is involved, requirements for IT security, data quality and traceability are especially high.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Staff at municipal utilities and energy suppliers
  • Grid operators in planning, connections and operations
  • Customer service and billing teams
  • Regulatory affairs and energy trading
  • Renewable energy project developers

Typical challenges we address

  • Dense regulation that changes frequently
  • Growing numbers of customer enquiries on tariffs, bills and grid connections
  • Extensive technical and permitting documentation
  • Skills shortages alongside rising investment volumes

What you will be able to do

  • You can build n8n workflows independently using triggers, logic nodes and data transformations.
  • You can connect n8n to the applications you use every day and fall back on the HTTP Request node where needed.
  • You can use the AI Agent node and other AI building blocks for classification, extraction and summarisation.
  • You can safeguard workflows with error handling, validation and human approval steps.
  • Navigate regulatory requirements and technical documents faster and more reliably with AI.
  • Relieve customer service and grid connection processes through AI-supported pre-checks and draft replies.
  • Assess AI use cases with due regard to IT security and critical infrastructure requirements.

Course outline

Day 1

Module 1 Fundamentals: workflows, triggers and nodes
  • Getting to know the n8n interface, canvas and execution view
  • Trigger types: schedules, webhooks, incoming email and app events
  • Understanding items and JSON data and working with expressions
  • Using core nodes such as Edit Fields, IF, Switch, Merge and Loop Over Items
Module 2 Integrations and data processing
  • Connecting common applications: email, spreadsheets, CRM, collaboration and cloud storage
  • Using the HTTP Request node for APIs without a ready-made integration
  • Creating, managing and sharing credentials securely within the team
  • Filtering, merging and reshaping data and writing it to target systems
Module 3 AI in n8n: the AI Agent node and LLM building blocks
  • Connecting chat models from different providers as well as locally hosted models
  • Configuring the AI Agent node with a system prompt, memory and tools
  • Automating classification, structured data extraction and summarisation
  • Using your own documents via vector stores for retrieval-augmented generation
Module 4 Error handling, testing and maintainability
  • Setting up error workflows, retries and failure notifications
  • Validating AI output and defining fallbacks for unusable responses
  • Working with pinned test data and tracing past executions
  • Modularising, naming and documenting workflows for colleagues

Day 2

Module 5 Self-hosting, data protection and operations
  • Cloud versus self-hosted: effort, control and licensing model compared
  • Assessing data flows to AI providers against GDPR requirements
  • Managing access rights, logging and retention of execution data
  • Adding human-in-the-loop approval steps to automated processes
Module 6 Practice lab: Energy & Utilities
  • Making regulation understandable
  • Relieving customer service
  • Pre-checking connection requests
  • Unlocking technical documentation
  • Permitting and project documents
  • Reporting and market analysis
Module 7 Data protection, quality & transfer to daily work
  • As operators of critical infrastructure, utilities and grid operators face heightened IT security requirements, for example under NIS2 and sector-specific security catalogues; grid and asset data must not flow uncontrolled into external AI services. Consumption and metering data is personal data under the GDPR and metering regulations, and unbundling rules must also be observed.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Making regulation understandable

Regulatory decisions, legislative changes and industry guidelines are summarised, their impact on internal processes derived and prepared as task lists for departments – reviewed by regulatory affairs.

Relieving customer service

Enquiries about instalments, annual bills, tariff changes or registering wallboxes and PV systems are classified, draft replies created and missing documents requested specifically. Recurring issues feed into FAQs and self-service content.

Pre-checking connection requests

Incoming applications are checked for completeness, technical details extracted and passed to grid planning in a structured format, with follow-up questions to installers drafted. Processing times shrink noticeably.

Unlocking technical documentation

Operating manuals, maintenance logs and excerpts from standards are made searchable so teams quickly get answers to technical questions, including a reference to the source.

Permitting and project documents

For wind, solar or grid projects, application documents are structured, comments from authorities and the public analysed and project reports prepared for boards. Deadlines and conditions are tracked clearly.

Reporting and market analysis

AI helps write commentary on sales, generation and grid KPIs, summarises market reports and drafts mandatory disclosures and internal reports. Figures always come from verified source systems, never from the AI.

Prerequisites

You should be confident with common office applications and have basic experience with AI assistants. No programming is required, although a basic grasp of structured data is helpful. Professional experience in an energy sector company; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser. We provide an n8n environment for the exercises, or you can use your own instance; API keys for a language model are set up together during the course.

Data protection & compliance

As operators of critical infrastructure, utilities and grid operators face heightened IT security requirements, for example under NIS2 and sector-specific security catalogues; grid and asset data must not flow uncontrolled into external AI services. Consumption and metering data is personal data under the GDPR and metering regulations, and unbundling rules must also be observed.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Mon, 23 November 2026 – Tue, 24 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Augsburg Request
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Online Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Kaiserslautern Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Online Request

Frequently asked questions

Do I need to code to work with n8n?

No. Most workflows are built visually by connecting nodes. During the course you also learn simple expressions to reference and reshape data precisely. A Code node is available for special cases but is not essential. A logical understanding of processes and data fields is entirely sufficient to get started.

Why is n8n attractive from a European data protection perspective?

n8n can be self-hosted, for instance on your own servers or with a European hosting provider. This keeps you in control of where workflow and execution data is stored. What still matters is which data you send to external AI services. On the course you learn to assess these data flows and, where appropriate, connect locally hosted models.

How does n8n differ from Make or Power Automate?

All three automate processes across applications. n8n stands out for its self-hosting option, its fair-code licensing and particularly flexible AI building blocks such as the AI Agent node. Make offers a very approachable cloud interface, while Power Automate excels at deep Microsoft integration. The course puts these differences into context for typical scenarios.

May a grid operator use cloud AI services?

In principle yes, but only for suitable data and after approval by IT security and data protection. Operational and grid data from critical assets does not belong in external services. In the course we carefully distinguish non-critical use cases such as text work from sensitive areas that require special safeguards.

Can AI reliably interpret regulatory changes?

AI summarises regulatory decisions and legislation well and helps identify affected processes. Binding interpretation, however, remains the job of regulatory affairs or the legal department. The course shows how to back up AI summaries with source references and avoid misinterpretation.

How much does “n8n for the Energy Sector” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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