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Summary – Aging infrastructure and variable flows hamper carbon neutrality: outdated equipment, manual management, and prosumer silos threaten stability and renewable integration. Digitalization breaks down these silos by connecting IoT meters, AI, EMS, digital twins, and aggregators via standardized APIs for real-time monitoring, peak prediction, automated orchestration, and enhanced resilience.
Solution: deploy a modular, scalable architecture (smart meters, IoT/AI, IT/OT, digital twins) with data governance and zero trust security to manage, anticipate, and optimize your network toward Net Zero.
Facing energy infrastructures where nearly 40% are over forty years old, Europe’s carbon-neutrality targets require a thorough overhaul of the system. The challenge isn’t limited to producing “green” electricity but orchestrating a smart grid capable of managing diverse and variable flows. Digitalization emerges as the keystone of this transition, providing the visibility, automation and interconnection needed to ensure stability, resilience and efficiency.
Strained Energy Sector in Europe
Europe’s power grid is under unprecedented load, with often outdated equipment ill-suited to new demands. In this context, digitalization appears to be the only way to effectively integrate renewable energy sources and decentralized flexibility.
Infrastructure Status and Stability Challenges
High-voltage lines, substations and distribution networks were designed when production was centralized and predictable. Today, injection of electricity from thousands of rooftop solar installations and wind farms causes frequency and voltage fluctuations that this equipment wasn’t built to handle.
Without real-time monitoring systems, automatic restarts and instant rebalancing remain slow and manual. This lack of responsiveness can jeopardize service continuity and limit the absorption of new renewable capacity.
Planned load-shedding and safety outages become emergency measures, often poorly received by industrial stakeholders and municipalities, even though predictive management could have prevented these interruptions.
Proliferation of Producer-Consumers
The shift to decentralized energy has given rise to countless prosumers: industrial enterprises, agricultural cooperatives and local authorities now produce electricity. While beneficial to the transition, this trend radically complicates grid management.
Each autonomous producer introduces an additional control point, with its own consumption and production profiles. Traditional siloed management approaches are no longer sufficient to coordinate these actors and ensure a coherent collective response to demand peaks or production drops.
Without a unified platform and standardized exchange protocols, aggregation of these decentralized flows remains ad hoc and fragile, potentially undermining system resilience in the event of a failure or peak demand.
Example: Regional Power Utility
A regional power utility implemented a digital dashboard centralizing measurements from over 2,000 smart meters. Thanks to this granular visibility, it anticipates consumption peaks and adjusts inputs from the local hydroelectric plant in real time.
This project demonstrates that digitalization provides forecasting capabilities that reduce overload risks and the costs associated with emergency interventions on the national grid. The utility increased its ability to integrate new renewable installations by 15% without massive investment in traditional infrastructure.
Why Digitize the Energy System
The digital transformation of the energy sector rests on shifting from manual supervision to automated orchestration of flows. IoT sensors, combined with artificial intelligence, turn every data point into optimized action.
From Periodic Readings to Continuous Measurement
Previously, meter readings were taken on site or via time-stamped batches, with delays of several days in consumption analysis. Today, IoT sensors transmit the status of every energy resource—solar production, industrial consumption or electric vehicle fleet charging—every minute.
This continuous measurement offers unprecedented granularity, enabling instant detection of anomalies, abnormal usage or network losses. Fault detection algorithms intervene upstream, drastically reducing intervention times and associated costs.
Automating data processing frees teams from repetitive tasks, allowing them to focus on performance and service-quality improvements.
AI and Demand Forecasting
AI models leverage consumption histories, weather forecasts and market data to anticipate supply or demand peaks. They enable real-time adjustments of heat pumps, virtual power plants and energy storage.
This forecasting capability improves grid stability by reducing gaps between supply and demand. It also facilitates financial optimization by directing automations toward periods when energy is most available or cost-effective.
Beyond forecasting, some platforms integrate feedback loops that continuously learn from each adjustment, enhancing system accuracy and responsiveness.
Example: Industrial Park
An industrial group deployed IoT sensors in its workshops to monitor production-line consumption and machine performance. A machine-learning algorithm detects periods of high demand and dynamically manages power supply from an on-site micro hydroelectric plant.
This led to a 10% reduction in its energy bill and a 20% decrease in indirect emissions, while improving predictive maintenance of critical equipment. The project illustrates how intelligent automation turns a factory into an active participant in the energy transition.
Edana: strategic digital partner in Switzerland
We support companies and organizations in their digital transformation
Energy Paradigm Based on Micro-Decisions
The grid of the future won’t rely on a few centralized decisions but on the coordination of millions of production and consumption points. Each micro-decision contributes to the global balance of the system.
Microgrids and Energy Communities
Energy communities bring together localized consumers and producers who share energy close to the point of need. These microgrids can temporarily island a zone in case of main-grid failure and continue operating in island mode.
Decentralized governance of these communities requires data-exchange protocols and collaborative platforms so each participant can view their contributions and usage in real time.
Microgrids strengthen local resilience while relieving long-distance transmission lines, but their integration demands advanced digitalization.
Real-Time Coordination
To synchronize highly diverse uses—office buildings, data centers, charging stations—it’s essential to have a unified repository of statuses and forecasts. Energy management systems (EMS) aggregate this information and control flexibilities via standardized APIs.
Implementing cloud-native services allows infinite data-processing scalability and ensures 24/7 availability. Automatic failover mechanisms preserve continuity even if part of the service goes down.
The resilience of each micro-decision therefore depends on the interoperability of digital components and the robustness of the software layer.
Role of Aggregators
Aggregators act as intermediaries between small producers/consumers and energy markets. They pool flexibilities and negotiate offers on marketplaces while ensuring local balance.
To fulfill this role, they rely on digital platforms capable of collecting, validating and aggregating heterogeneous data in near-real time. Service quality depends as much on software architecture as on flexibility-valuation algorithms.
This third layer of coordination makes the aggregator a key player, requiring a robust and scalable digital infrastructure.
Foundations of the Energy Transformation
Digitalization relies on technological building blocks: smart meters, data governance platforms, predictive-planning tools and IT/OT convergence. These modules form a modular and scalable ecosystem.
Smart Meters and Remote Reading
Deploying smart meters is the first step. Each metering point now continuously transmits its consumption and technical status without manual intervention.
These meters connect to Low Power Wide Area (LPWA) networks or fiber-optic infrastructure, depending on local context. The open architecture of these networks allows selecting the most suitable technology without being tied to a single provider.
Standardized reading protocols ensure interoperability between manufacturers and simplify integration of data into existing information systems.
Data Governance and Cybersecurity
The multiplication of data flows requires a clear data-governance strategy: cataloging, traceability, access controls and encryption. Each metric must be classified by criticality to apply appropriate security measures.
Critical infrastructures demand zero-trust approaches and segmented environments where strong authentication is the norm. IT/OT gateways are protected by dedicated firewalls and anomaly-detection mechanisms tailored to industrial protocols.
Trust in the digital system is essential to guarantee the reliability of automated decisions and regulatory compliance.
Predictive Planning and Digital Twins
Digital twins replicate in real time the state of the grid, production infrastructures and consumption points. They become the basis for predictive planning, enabling simulation of evolutions, failures or the addition of new equipment.
Mathematical models leverage historical data, weather scenarios and growth projections to propose optimized investment plans. Network expansion budgets are thus better targeted, avoiding overcapacity or future bottlenecks.
The agility provided by these tools reduces planning costs and secures the trajectory toward carbon neutrality.
Example: Municipal Cooperative
A cooperative of several municipalities integrated its industrial SCADA with its ERP and an open-source BI solution. Heat-network pressure data and public-building consumption metrics flow in real time to a single portal.
This setup identified leaks and excessive consumption, reducing heat-network losses by 12% and overall energy costs by 8%. The example illustrates the concrete impact of an intelligent, open platform combining existing modules and custom developments.
Transforming Your Energy System into a Sustainable, Data-Driven Pillar
Digitizing the energy system is the foundation of a resilient grid capable of accommodating massive renewable influx and synchronizing millions of micro-decisions. By combining smart meters, AI, IoT, IT/OT integration and digital twins, you build an architecture that is scalable, secure and interoperable.
Whatever your role—CIO, transformation manager, CEO, IT project leader or business manager—our experts support you in defining and implementing your digital roadmap. Together, we’ll design a contextualized ecosystem based on open source and governance best practices to achieve your Net Zero goals.
