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Mission Statement

The mission of the iGrids research group is to conduct research with the aim to ensure reliable, stable, secure, smart and active energy networks, which integrate high penetration of distributed generation units, energy storage and a high number of flexible loads across different energy sectors. The systems are based on intelligent control, coordination and operational strategies - increasingly enabled by artificial intelligence, digital twins and large-scale data analytics - that contribute to ancillary services, increased network flexibility and asset management, and that facilitate improved and novel business models for social, economic and environmental sustainability.

Mission Statement

The mission of the iGrids research group is to conduct research with the aim to ensure reliable, stable, secure, smart and active energy networks, which integrate high penetration of distributed generation units, energy storage and a high number of flexible loads across different energy sectors. The systems are based on intelligent control, coordination and operational strategies - increasingly enabled by artificial intelligence, digital twins and large-scale data analytics - that contribute to ancillary services, increased network flexibility and asset management, and that facilitate improved and novel business models for social, economic and environmental sustainability.

Research Objectives

Focus Areas

Trends

European Union is focusing on integrating smart grid technologies in energy systems to achieve system adequacy, energy efficiency, low-carbon and sustainability, circular economy and user comfort.

Its 2026 strategic roadmap for digitalization and AI in energy explicitly targets electricity grid optimiZation, energy efficiency, and demand-side flexibility, alongside accelerated smart meter rollout across member states.

Power system’s architecture and its operation is changing due to large share of renewables and distributed energy resources (DERs).

Grid-forming inverter technology and the loss of system inertia from retiring synchronous generation are emerging as central technical concerns for system stability.

More interaction between different energy sectors, new storage possibilities and new loads like electrical vehicles, heat pumps, and electrolysers are expected.

Large, fast-growing loads such as AI-driven data centres are adding a new category of demand that grid planning, connection processes and flexibility products must now accommodate.

Enabling energy flexibility and efficiency for economic savings in integrated energy systems using ICT tools and big data from advanced metering infrastructures.

Advanced distributed management systems (ADMS) for smartening active distribution grids are highly essential.

Flexibility markets are maturing rapidly: faster (15-minute) market settlement, mandatory national flexibility assessments and targets, and coordinated DSO-TSO flexibility procurement are reshaping how flexible resources are valued and dispatched.

Challenges

  • New load flow patterns in distribution grids, power quality compliance, and power system protection and control require new approaches.
  • Handling big data from smart meters and devices for flexibility estimation, and for enhanced controllability and observability of energy networks, including the design of trustworthy AI-based forecasting and decision-support tools.
  • Coordinating sequential flexibility markets, in which DSOs first procure local flexibility for congestion management before remaining flexibility is forwarded to TSO-level system services- a process complicated by TSOs having incomplete visibility of distribution-grid constraints.
  • Most energy vectors remain disaggregated and active only in specific markets, with varied time scales and capacity allocation rules governing the operation and control of energy assets and networks.
  • The need for active consumer engagement, effective incentive mechanisms for consumers and prosumers, and their adaptability in responding to variable tariffs, emerging energy market platforms, policies and regulations.
  • A lack of operational mechanisms and decision-support systems enabling different energy vectors to expand into other energy markets, and a lack of standardized methods for quantifying and certifying flexibility against new national flexibility targets.
  • The integration of AI and digital technologies into critical energy infrastructure introduces new cybersecurity and resilience risks that must be managed alongside the operational benefits they bring.