Learn how the energy & utilities industry is adapting to key trends like AI, electric vehicles, renewables, and the challenges they face going into 2026.
Inhaltsverzeichnis
Mit AI data centers, EV charging and renewables on the rise, the energy & utilities industry is facing a surging electricity demand.
Versorgungsunternehmen befinden sich an einem kritischen Punkt, an dem Innovation nicht mehr optional ist - sie ist notwendig, um an der Spitze zu bleiben.
Lassen Sie uns einen Blick auf die Trends werfen, die diesen Wandel prägen, und darauf, wie Versorgungsunternehmen sie effektiv nutzen können.
Advanced Metering Infrastructure (AMI) 2.0
Traditional metering systems often lead to inefficiencies such as billing inaccuracies and delays in accessing consumption data.
This is where AMI steps in to provide smart meters that enable accurate real-time metering.
This results in precise verbrauchsabhängige Abrechnung, avoids revenue leakage and provides insights for customers.
Furthermore, smart meters allow for responding to grid demand. This enables off-peak metering and communicating changes and fluctuations to customers.
AMI 2.0 has gained traction offering more frequent access to voltage values, allowing for near real-time data access.
Additionally, Non-Intrusive Load Monitoring (NILM) identifies appliances which are faulty or inefficient by analyzing their unique electricity signature.
Customers can pair their phones with AMI 2.0 smart meters to gain insights on usage and efficiency.
It’s crucial that energy providers learn from AMI 1.0 mistakes and invest money in upgrading infrastructure and not only focus on buying the hardware.
Improvements in AMI 2.0
- Daten in Echtzeit: Intelligente Zähler liefern Verbrauchsdaten in Echtzeit und ermöglichen es den Versorgungsunternehmen, Ausfälle zu erkennen und deren Standorte für schnellere Reparaturen zu lokalisieren.
- AI & Machine learning: Enables AI predictive maintenance and load forecasting.
- Unterstützung von Demand Response: AMI ermöglicht es den Versorgern, während der Nachfragespitzen Signale zu senden, die die Nutzer dazu anregen, den Verbrauch zu senken. Zusätzlich, gemessene Nutzung enables precise tracking of energy consumption, ensuring fair and transparent billing based on actual usage.
- EV charging: Enables Dynamischer Lastausgleich, intelligentes Laden, demand response automation.
Artificial Intelligence (AI) & Machine Learning (ML)
According to research, 74% of energy companies adopt some sort of AI.
While the energy sector is beginning to adopt AI, many utilities lag in leveraging its full potential.
Wie KI den Betrieb von Versorgungsunternehmen optimiert:
- Forecast demand: AI tools balance supply and demand in real time, preventing grid overloads.
- Vorausschauende Wartung: AI anticipates equipment failures, minimizing downtime and costly repairs.
- Kundenpersonalisierung: Datengestützte Erkenntnisse ermöglichen es Versorgungsunternehmen, maßgeschneiderte Empfehlungen und Abrechnungslösungen anzubieten.
Challenges Companies Face Regarding AI
The emergence of AI data centers poses multiple challenges for energy providers.
Companies must scale infrastructure to respond to the demand of running and cooling servers for training AI models.
Additionally, die U.S DOE warns of “data poisoning”, where attackers might feed the AI false sensor data to shut down crucial components.
Also, since AI is trained on specific scenarios, it might make illogical decisions when faced with scenarios it hasn’t seen yet.
Digital Twin Technology
“Digital twin” software (real‐time virtual replicas of plants, grids, pipelines, or water systems) is maturing in utilities.
These virtual replicas allow for simulating changes or failures and how systems react to these factors without real-world risks.
Innovationen und wichtige Herausforderungen in der Energie- und Versorgungswirtschaft
Die EY Future of Energy Survey reveals that 62% of utility companies claim to be utilizing digital twins, only 11% feel that these technologies are meeting their expectations.
Developments in Digital Twin Software
- AI and ML: Newer software uses AI to more accurately simulate environments by being trained on real-world data.
- Real-time access to IoT devices: This allows DT to access actual sensors and devices instead of simulated ones to construct accurate environments.
- Cloud-native platforms: DT software is being developed on the cloud, allowing for easier integration and lowers time-to-value.
Improving interoperability between systems, introducing standards, increasing shared understating of how digital twins work is the main goal going forward.
Renewable Energy
Renewables are set to surpass coal-fired generation in 2026.
This shifts the market focus away from coal and towards renewables; this is reflected in software trends.
The figure below shows electricity generation from fossil fuels, nuclear energy and renewables by continent in 2024.
| Continent | Fossil | Nuclear | Renewable |
|---|---|---|---|
| Afrika | 75% | 1% | 24% |
| Asien | 70% | 5% | 25% |
| World | 59% | 9% | 32% |
| Ozeanien | 58% | 0% | 42% |
| Nord-Amerika | 56% | 16% | 28% |
| Europa | 40% | 21% | 39% |
| South America | 22% | 2% | 76% |
Quelle: Our World In Data
Renewable energy is unpredictable; we can’t generate wind or switch on the sun on demand, like we can with fossil fuels.
It’s also highly dependent on the location. Transmission of renewables becomes a challenge when plants are so decentralized.
This is why Virtual Power Plants (VPP) und Distributed Energy Resources Management Systems (DERM) are shifting towards cloud-native SaaS solutions tailored for renewables.
The focus is to make renewable energy storage and transmission reliable and efficient.
This is mostly done with AI and digital twins to predict demand, scale power plants and simulate changes and disasters.
Additionally, Energy as a Service (EaaS) and Utility as a Service (UaaS) are on the rise.
Dynamische Preisgestaltung
Pauschale Preismodelle sind in der heutigen Energielandschaft nicht mehr zeitgemäß. Deshalb dynamische Preisgestaltung is a win-win for utilities and consumers.
It reflects real-time conditions, creating a more balanced and efficient system.
Dynamische Preismodelle für Versorgungsunternehmen:
- Preisgestaltung in Echtzeit: Adjusts rates based on grid capacity and renewable energy availability.
- Time-of-Use-Preise: Encourages off-peak energy usage by offering lower rates.
- Gestaffelte Preisgestaltung: Rewards efficient energy consumption with reduced costs.
Die wichtigsten Vorteile der dynamischen Preisgestaltung:
- Reduces grid strain during peak periods.
- Helps consumers save money with smarter energy choices.
- Promotes efficient energy use und grid stability.
The introduction of dynamic pricing opens up new market opportunities.
Smart Grid Modernization
The rise of distributed energy (solar panels, batteries, EVs, etc.) is leading utilities to adopt sophisticated grid-management software and Virtual Power Plant (VPP) platforms.
Modern smart grid software integrates demand response, inverter controls, storage dispatch, and microgrids to keep the grid balanced.
Smart Grid-Funktionen für moderne Versorgungsunternehmen:
- IoT-Sensoren: Provide real-time grid performance data for proactive management.
- Fehlersuche: Quickly identify and resolve issues, minimizing outages.
- Demand Response Systeme: Dynamically adjust energy supply to meet changing demands.
- Artificial Intelligence: Forecasting weather events, power spikes and outages.
Die Auswirkungen von intelligenten Stromnetzen:
- Seamless integration of renewable energy sources into the grid.
- Enhanced reliability and reduced operational disruptions.
- Greater energy efficiency and sustainability.
Integration von Elektrofahrzeugen (EVs)
Mit der zunehmenden Verbreitung von Elektrofahrzeugen steigt auch die Belastung der Netzinfrastruktur. Energieversorger müssen sich darauf einstellen EV charging solutions und gleichzeitig die Netzstabilität zu erhalten.
Trends in EVs are indirectly affecting the decisions that energy and utility providers make.
The question for utility providers has shifted from “How do we survive this demand?” zu “How can we utilize this demand to our advantage?”.
On the one hand, technologies like V2G pose a challenge when it comes to regulatory compliance and grid compatibility.
On the other hand, however, they also provide benefits like grid stabilization und peak load management to grid operators.
Furthermore, EVs are the perfect testbed for next-gen electricity pricing.
Die ChargeWise California pilot project found that dynamic price signals, combined with automated charging management, achieve up to 98% EV charging load delivered off-peak.
Above 60-70% typically achieved by time-of-use (ToU) tariffs.
Pricing engines like Tridens Monetization enable effortless configuring of complex tariffs.
Strategien für eine wirksame Integration von EV:
- Ladungsmanagement-Systeme: Ausgleich der Netzlasten durch Optimierung der Ladepläne
- Dynamische Preismodelle: Fördern Sie das Laden außerhalb der Spitzenzeiten mit variablen Stromtarifen
- Netzanbindung: Nahtlose Integration der EV-Infrastruktur mit Energiesystemen, um Überlastungen zu vermeiden
IoT im Energiemanagement
Die Internet der Dinge (IoT) verändert die Versorgungsunternehmen, indem es die Überwachung und Kontrolle des gesamten Betriebs in Echtzeit ermöglicht.
Wichtige IoT-Anwendungen im Energiemanagement:
- Intelligente Geräte: Thermostate und Energiemonitore ermöglichen es den Verbrauchern, den Energieverbrauch zu optimieren
- Überwachung in Echtzeit: Versorgungsunternehmen erhalten verwertbare Erkenntnisse, um die Effizienz zu steigern und Verschwendung zu reduzieren
- Integration erneuerbarer Energien: IoT hilft bei der Steuerung der Variabilität erneuerbarer Energiequellen
IoT-Vorteile für Energie- und Versorgungsdienstleister:
- Reduces carbon footprint by optimizing resource management and energy consumption
- Reduces energy waste and operational costs
- Increases transparency and control for both utilities and consumers
- Supports sustainability goals through better resource management
Choosing a Modern Monetization Provider
At Tridens Technology, we empower energy and utility companies with Tridens Monetization.
Durch die Integration von fortschrittlicher Rechnungsstellung, KI-Analytik und dynamischen Preismodellen helfen wir Versorgungsunternehmen, ihren gesamten Meter-to-Cash-Prozess mit einer vollständig konfigurierbaren Multi-Service-Abrechnungsplattform zu automatisieren.
Our customers benefit from real-time charging and invoicing, enabling instant billing based on usage or time.
Advanced rate management tools let you create and manage complex pricing structures with ease, including usage-based and dynamic pricing models.
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