Integrating battery energy storage systems (BESS) into a digital representation of the grid allows operators to evaluate storage alongside network conditions and other operational actions. The approach couples distributed battery systems with a digital twin of the distribution grid – a dynamic representation of the physical network, its loads, generation and storage – on which operators can forecast conditions, simulate interventions and assess whether proposed actions can resolve network constraints before deployment.

Batteries may otherwise be optimized primarily against asset or market objectives without explicitly accounting for local network conditions. Integrating storage into the grid model allows the network constraint and potential response to be evaluated together. The same environment that identifies an emerging thermal or voltage constraint can assess whether available flexible resources or network reconfiguration could address it and evaluate the resulting effects across the network.

This capability is becoming more relevant as electrification, distributed energy resources and variable renewable generation increase the complexity of network planning and operation. Coordinating storage with network conditions can enable batteries to support both routine grid operation and preparedness for disruptions, while allowing their potential value to be considered alongside conventional network reinforcement.

The approach can extend the digital twin across operations, preparedness and planning. In operations, it models customer-owned and operator-owned batteries as flexible resources, incorporating operating constraints and network conditions into dispatch and reconfiguration decisions. In preparedness, it allows operators to simulate island operation ahead of an event, testing voltage profiles, load balancing and restoration sequences. In planning, it provides an environment to evaluate candidate battery locations and sizing against network needs and conventional reinforcement options. By modeling the services storage can provide at different locations – from congestion management and voltage support to backup supply during disruptions – operators can assess where storage could defer or avoid network reinforcement.

Main Outcomes of the Solution

• Reliability and Flexibility: Integrating storage into the grid model enables operators to assess batteries for congestion management, voltage support and balancing while accounting for network conditions and operating constraints.
• Affordability: Evaluating battery location and sizing against network constraints can help target storage where it may defer or reduce conventional network reinforcement and improve utilization of existing infrastructure.
• System Resilience: Simulating island operation, backup supply and restoration strategies in advance can support more structured preparedness and help assess how storage can maintain critical supply during network disruptions.

Key Deployment and Scaling Factors

1. Treat battery siting and sizing as network planning decisions, considering the constraints addressed and the combination of services storage is expected to provide.
2. Maintain accurate network models, telemetry and asset data so that the digital twin reflects relevant network conditions, battery availability and operating constraints.
3. Establish interoperable data interfaces between batteries, digital platforms and grid operational systems, with clear responsibilities for dispatch, island operation and restoration.
4. Validate control strategies before field deployment, using simulation and, where appropriate, Hardware-in-the-Loop testing to assess behavior under normal, fault and recovery conditions.
5. Design controls to operate safely under degraded communications, with appropriate local control, fail-safe behavior and physical operating constraints.
6. Establish cybersecurity, authentication and access controls for data exchange and remote operation of distributed storage.
7. Integrate grid and preparedness planning so that resilience benefits and associated availability requirements can be considered alongside conventional network investment.
8. Align deployment with grid codes, connection requirements, market arrangements and regulatory treatment of storage, including rules governing cost recovery and the provision of network and preparedness services.

Case study

B-READY Consortium (2026–2028), Norway

B-READY is a Norwegian research and innovation project developing and testing battery systems for grid operation and emergency preparedness. The project received up to NOK 76 million (USD 8.1 million as of Sep 2026) in public funding through Norway’s Green Platform scheme. Led by SINTEF Energy Research, with Pixii as project owner, the consortium includes technology providers, distribution and transmission system operators, an energy producer, a public transport operator and research institution.

The project is developing approaches to integrate battery systems into grid operation and planning. These include digital-twin-based tools for battery siting, methods for incorporating battery operating constraints into grid management and simulation of island operation and restoration. Falkor  participates in the grid operation and integrated grid and preparedness planning workstreams, alongside grid operators and research partners.

The approaches are being tested through laboratory and field pilots, including island operation and black start, a solar-plus-storage hybrid plant and vehicle-to-grid applications. The project is also assessing whether batteries can provide both routine grid services and emergency preparedness while reducing the need for conventional network reinforcement. Project partners estimate that wider use of battery systems could reduce planned Norwegian grid investment needs by up to NOK 8.5 billion (USD 911 million as of Sep 2026) by 2030, equivalent to 5% of the approximately NOK 170 billion (USD 18.2 billion as of Sep 2026) of planned grid investment used as the project's reference case.

References:

1. B-READY - SINTEF