Grid-Enhancing Technologies: Increasing Electricity Network Capacity Without Building New Lines

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Introduction

Electricity networks are under growing pressure from rising demand, renewable energy deployment, electrification of transport and industry, and the increasing connection of distributed energy resources. In many countries, the development of new transmission and distribution infrastructure is not keeping pace with these changes. Planning, permitting, financing and constructing new lines can take several years, while generation projects, industrial loads and electricity demand may develop much faster.

At the same time, existing networks are not necessarily operating at their full potential. Transmission lines, transformers and other grid assets are often operated using conservative capacity limits. These limits are necessary to maintain safety and reliability, but they may not reflect the actual conditions at a particular time or location. Weather, electricity demand, generation patterns, network configuration and equipment condition all influence how much power can safely flow through a network.

Grid-enhancing technologies (GETs) help electricity network operators make better use of existing infrastructure. They combine hardware, software, monitoring, control and operational methods to reveal unused capacity, redirect electricity flows, improve network configuration and respond more effectively to changing system conditions.

Their purpose is not to eliminate the need for new transmission and distribution infrastructure. Rather, they provide additional options for increasing network utilisation, connecting new generation and demand, reducing congestion and potentially deferring selected infrastructure investments.

The International Energy Agency (IEA) identifies dynamic ratings, advanced power-flow control, topology optimisation and real-time remedial actions as important grid-enhancing approaches. These technologies can be combined with digital monitoring, advanced control systems and artificial intelligence (AI) to improve the planning and operation of electricity networks.

Why Existing Electricity Networks Need to Be Used More Efficiently

Rising electricity demand and grid congestion

Electricity demand is increasing as more activities depend on electricity, including cooling, industrial production, transport, digital infrastructure and household appliances. Renewable energy projects and battery storage systems are also creating new requirements for grid connections and power transfers.

The IEA's *Modernising Grids in the Age of Electricity* reports that global grid capacity needs to increase by at least 30% by 2035. It estimates that this would require adding or replacing approximately 25 million kilometres of electricity lines. The report also notes that at least 1,700 GW of advanced-stage renewable energy projects and 600 GW of utility-scale battery projects were awaiting grid connection in 2025.

Grid congestion occurs when the network cannot transfer electricity from one location to another without exceeding operational limits. It can prevent lower-cost generation from reaching consumers, restrict renewable energy output, delay new connections and increase system operating costs.

Building additional transmission capacity remains essential in many locations. However, new infrastructure can be delayed by land acquisition, permitting, environmental assessment, community concerns, equipment supply constraints, financing and coordination between jurisdictions. Grid-enhancing technologies offer additional ways to address certain constraints while longer-term infrastructure projects are developed.

Why electricity networks have unused capacity

Electricity networks are designed to operate within technical limits that protect equipment and maintain reliable service. These limits include:

  • Thermal limits: the maximum current that conductors, transformers and other equipment can carry without exceeding safe temperature limits.
  • Voltage limits: the acceptable range of voltage required to maintain equipment performance and power quality.
  • Stability limits: the conditions required to maintain synchronism, frequency and stable operation following disturbances.
  • Protection limits: the ability of protective devices to detect and isolate faults without causing unnecessary disconnections.
  • Operational security limits: the capacity that can be used while maintaining acceptable performance during equipment outages or other credible contingencies.

In practice, network operators may use fixed or seasonal ratings and conservative operating margins because they cannot continuously observe every relevant condition. This can mean that some capacity remains unused when actual weather, loading or network conditions are more favourable.

For example, an overhead transmission line may be able to carry more current on a cool, windy day than on a hot day with little wind. A fixed rating may not fully reflect this difference. Similarly, electricity may flow through a heavily loaded transmission corridor even when alternative routes have spare capacity.

Grid-enhancing technologies help operators identify and use such opportunities, provided that the entire network remains within its safe operating limits.

What are grid-enhancing technologies?

Grid-enhancing technologies are hardware, software and operational solutions that improve the capacity, flexibility, controllability or efficiency of existing electricity networks.

The term is used differently across the energy sector. Some definitions include advanced conductors, voltage uprating, energy storage and demand response. The IEA's 2026 analysis focuses more narrowly on digitally enabled technologies that grid operators can use to reveal available capacity, redirect power flows, optimise network configurations and implement corrective actions.

This article uses that operational focus while also explaining related infrastructure upgrades that are sometimes grouped under the broader GET definition.

The main technology groups discussed are:

  • Dynamic line rating and dynamic transformer rating.
  • Advanced power-flow control.
  • Topology optimisation.
  • Real-time remedial action schemes.
  • Active network management and associated digital monitoring and control systems.

These technologies address different network constraints. Their value depends on the specific problem being solved, the physical characteristics of the network and the operator's ability to monitor and control the system.

1. Dynamic Line Rating and Dynamic Transformer Rating

Dynamic line rating

Dynamic line rating (DLR) is a method of determining the amount of electricity an overhead transmission line can safely carry under changing operating and environmental conditions.

Conventional transmission lines are commonly assigned static or seasonal ratings. These ratings are calculated using assumptions about ambient temperature, wind speed, solar radiation, conductor characteristics and other operating conditions. They are designed to provide safe limits across a range of expected conditions.

However, the actual ability of a conductor to carry electricity changes with the weather.

When electricity flows through a conductor, electrical resistance generates heat. The conductor also gains heat from sunlight and loses heat through convection and radiation. If its temperature becomes too high, it may expand and sag, reducing clearance from the ground, vegetation or nearby structures. Excessive temperature can also affect the mechanical properties and long-term performance of the conductor.

DLR uses actual or forecast environmental and operating data to calculate a more representative thermal limit.

Important variables include:

  • Ambient air temperature.
  • Wind speed and direction.
  • Solar radiation.
  • Conductor type, diameter and material.
  • Electrical current and conductor temperature.
  • Line condition and clearance requirements.

On a cool or windy day, a conductor may be able to carry more current because it can dissipate heat more effectively. During hot, still weather, its safe capacity may decrease.

DLR can be implemented using weather-based calculations, direct conductor-temperature or sag measurements, or a combination of approaches. Weather-based systems estimate conductor conditions from meteorological data and engineering models. Sensor-based systems measure relevant conditions directly at selected locations on the line.

The appropriate method depends on the accuracy required, the characteristics of the transmission corridor, the availability of weather data and the cost of installing and maintaining sensors.

Dynamic transformer rating

Dynamic transformer rating (DTR) applies a similar principle to power transformers.

A transformer's loading capability depends partly on the temperature of its internal components, particularly the windings and insulating oil. Transformer temperature changes in response to electrical loading, ambient conditions, cooling performance and the condition of the equipment.

Static transformer ratings may not fully reflect the ability of a transformer to accommodate short periods of higher loading when its thermal condition allows it.

DTR uses information such as load current, oil temperature, winding temperature estimates, ambient temperature and cooling-system performance to assess the transformer's available operating capacity.

Transformers have thermal inertia: their internal temperature does not change instantly when electrical loading changes. This can allow a transformer to carry a temporary increase in load, depending on its initial temperature, expected loading profile, cooling system and insulation ageing limits.

Dynamic transformer assessment must therefore consider both immediate operating conditions and the cumulative effect of temperature on equipment life. It should not be interpreted as permission to overload a transformer without appropriate thermal and asset-health analysis.

Applications and benefits

Dynamic ratings can be particularly useful where:

  • Existing transmission corridors are congested.
  • Renewable energy projects are waiting for grid connection.
  • Weather conditions create significant variation in line capacity.
  • New transmission construction is difficult or expensive.
  • Existing transformers experience short-duration peaks rather than continuous overloading.

Potential benefits include increased transfer capacity during favourable conditions, reduced renewable energy curtailment, improved use of existing assets and the deferral of selected network reinforcements.

However, dynamic ratings do not automatically increase the capacity of every part of a transmission path. The usable capacity between two points is constrained by the most limiting relevant component. A line may have additional thermal headroom while a transformer, substation connection or another section of the route remains the bottleneck. For this reason, ratings should be assessed across the complete electrical path rather than at one isolated asset.

2. Advanced Power-Flow Control

Understanding power-flow constraints

Electricity does not always flow along the route that appears shortest or most convenient. In an interconnected alternating-current (AC) network, power flows according to the electrical characteristics of the network, including line impedance, voltage and phase-angle differences.

This can result in some transmission lines becoming heavily loaded while other parallel routes have available capacity.

Advanced power-flow control technologies help operators influence how electricity moves through the network. Their purpose is to redirect power away from congested circuits and make better use of underutilised transmission paths.

Technologies used for power-flow control

Several technologies can influence power flows:

  • Phase-shifting transformers: adjust the phase angle between connected parts of a network to influence the distribution of active power across parallel transmission paths.
  • Flexible alternating-current transmission systems (FACTS): use power-electronic and other technologies to control voltage, impedance and power flows. Examples include thyristor-controlled series capacitors (TCSC), static synchronous compensators (STATCOM) and unified power-flow controllers (UPFC).
  • High-voltage direct current (HVDC): transfers electricity between network areas using direct current. HVDC links can provide more direct control over the power transferred between their terminals than conventional AC connections.
  • Advanced power-flow controllers: newer modular devices can be installed on existing lines to influence power distribution without necessarily requiring major substation reconstruction.

These technologies differ in cost, complexity, application and the type of constraint they address. Some are established components of large transmission systems, while newer modular devices are intended to make targeted power-flow control more accessible.

Applications and limitations

Advanced power-flow control is useful where an interconnected network contains alternative transmission paths and the operator can redirect electricity towards circuits with available capacity.

For example, two parallel transmission corridors may connect the same generation and demand regions. If one corridor becomes congested while the other has spare capacity, power-flow control equipment may help redistribute electricity between them.

However, redirecting electricity does not make the underlying demand for transmission disappear. The alternative route must have sufficient capacity, and the resulting flows must remain within thermal, voltage, stability and protection limits.

Power-flow control may be less effective in radial networks without alternative paths. It may also transfer congestion from one circuit to another if the receiving route does not have sufficient headroom.

3. Topology Optimisation

What is network topology?

The topology of an electricity network describes how its components are electrically connected. It is determined by the arrangement and operating status of lines, circuit breakers, busbars, transformers and switching equipment.

Network operators can sometimes change the configuration of an existing grid by opening or closing selected circuit breakers and switches. These changes alter the paths through which electricity flows.

Traditionally, network reconfiguration has relied substantially on established operating procedures, engineering analysis and operator experience. Topology optimisation uses mathematical optimisation and network models to identify configurations that can reduce congestion or improve operating performance while maintaining security requirements.

How topology optimisation works

A topology optimisation system uses information about the network, including:

  • The electrical characteristics of lines, transformers and other equipment.
  • Current network configuration and breaker status.
  • Electricity generation and demand.
  • Thermal, voltage and stability constraints.
  • Protection settings and operational security requirements.
  • Planned outages and credible equipment contingencies.

An optimisation model evaluates possible switching configurations and estimates their effects on power flows and system security. It can then identify configurations that reduce loading on constrained equipment or improve the utilisation of available network capacity.

Modern computing and optimisation techniques have made it possible to assess many possible configurations more quickly than would be practical through manual analysis alone.

The IEA's 2026 report describes topology optimisation applications that can identify recommended network reconfigurations within seconds or minutes. It cites case studies in several United States system-operator regions where recommended configurations have increased effective grid capability by approximately 5–25% while meeting reliability requirements. These results are case-study findings, not a universal performance guarantee.

Conditions for successful implementation

Topology optimisation requires more than a mathematical model. Operators need accurate network data, reliable information about the actual status of switching equipment and procedures for implementing approved configurations.

Important requirements include:

  • Accurate network models that represent relevant equipment and substation connections.
  • Real-time or sufficiently current information on breaker and switch positions.
  • Remotely operable switching equipment where remote execution is required.
  • Protection systems that remain correctly coordinated after reconfiguration.
  • Operational procedures for approving, implementing and reversing switching actions.
  • Verification that the proposed configuration remains secure under relevant contingencies.

Topology optimisation can be particularly valuable in meshed transmission networks, where several alternative routes exist. Its application in distribution networks requires attention to radial operating arrangements, voltage regulation, fault levels and protection coordination.

4. Real-Time Remedial Actions

What are remedial action schemes?

Electricity systems must remain within acceptable operating limits not only during normal conditions but also when equipment fails or other disturbances occur.

Operators therefore assess credible contingencies, such as the loss of a transmission line, transformer or generator. They maintain sufficient operating margins and prepare actions to prevent a disturbance from developing into wider instability or cascading outages.

A remedial action scheme (RAS), also known in some systems as a special protection scheme, uses predefined automatic actions to respond to specified system conditions.

Depending on the design and operating requirements, these actions may include:

  • Tripping selected generation or transmission equipment.
  • Adjusting generator output or power-transfer setpoints.
  • Changing the configuration of network components.
  • Activating other approved corrective controls.

Real-time remedial action allows selected responses to be executed rapidly when defined conditions are detected. This can help operators manage certain contingencies without relying exclusively on large preventive operating margins.

Role of automation and advanced analytics

Modern monitoring and control systems can provide more detailed information about network conditions. Faster computation can also help operators evaluate potential disturbances and identify appropriate corrective responses.

AI-based tools may support contingency screening, risk assessment and the ranking of possible actions. However, automated or AI-assisted recommendations in safety-critical grid operations require rigorous validation, clear accountability, auditability and human oversight appropriate to the application.

The decision to execute a remedial action must be based on validated system conditions and approved operating logic. An incorrectly configured action can create additional disturbances rather than protect the network.

Safety considerations

Real-time remedial actions should be designed around clearly defined operating scenarios. Important considerations include:

  • The disturbances the scheme is intended to address.
  • The reliability and redundancy of detection and communication systems.
  • The response time required.
  • The consequences of incorrect operation or failure to operate.
  • Coordination with existing protection systems.
  • Testing, maintenance and periodic review of operating settings.

The use of automatic corrective actions does not remove the need for sound network planning, adequate protection and sufficient physical capacity.

5. Active Network Management and Distribution Grid Applications

Grid-enhancing approaches are relevant to both transmission and distribution networks, although the constraints and technologies differ.

Transmission systems generally focus on transferring large volumes of electricity over long distances, managing congestion between regions and maintaining system stability.

Distribution networks face increasing complexity as rooftop solar, electric vehicles, battery systems, heat pumps and other distributed energy resources connect at different locations. Distribution system operators may have limited visibility of low-voltage networks and need better ways to manage voltage, local congestion and connection capacity.

Active network management (ANM) coordinates the operation of network equipment and connected resources to make better use of available distribution capacity.

Depending on the network and control platform, this may include:

  • Monitoring feeder loading and voltage.
  • Managing transformer and feeder constraints.
  • Coordinating distributed generation and storage.
  • Applying flexible connection limits.
  • Controlling voltage-regulation equipment.
  • Automating switching and fault restoration.
  • Coordinating demand response and other flexible resources.

Distribution management systems (DMS) and advanced distribution management systems (ADMS) provide monitoring, analysis and control functions. Distributed energy resource management systems (DERMS) support the coordination of distributed generation, storage and flexible demand.

These platforms depend on reliable communication, accurate network models, appropriate cybersecurity and clear operational responsibility.

6. Digital Monitoring, Data and Artificial Intelligence as Enablers

Grid-enhancing technologies depend on the ability to understand network conditions and make operational decisions based on reliable information.

Digitalisation provides the monitoring and control foundation for many GET applications. It includes sensors, communications infrastructure, data platforms, supervisory control and data acquisition (SCADA), energy management systems (EMS), distribution management systems and other operational tools.

Monitoring and measurement

Relevant monitoring technologies include:

  • Line and transformer sensors.
  • Weather stations and meteorological data services.
  • Smart meters and advanced metering infrastructure.
  • Phasor measurement units (PMUs).
  • Substation monitoring and digital protection systems.
  • Remote terminal units and communication equipment.

PMUs provide time-synchronised measurements of electrical quantities such as voltage and current phasors. When deployed across a network, they can help operators understand system dynamics and identify conditions that may not be visible through conventional monitoring alone.

Network models and digital twins

Accurate network models are essential for evaluating power flows, identifying constraints and testing proposed operational changes.

A digital twin is a digital representation of a physical asset or system that can be updated using relevant operational and asset data. In electricity networks, digital twins can support planning, simulation, asset management and the evaluation of possible network configurations.

Their usefulness depends on the quality, completeness and timeliness of the underlying data. A sophisticated model that does not accurately represent the physical network can produce misleading results.

Artificial intelligence

AI can complement GET deployment by supporting:

  • Electricity demand and renewable generation forecasting.
  • Identification of potential congestion.
  • Screening of network connection requests.
  • Asset condition assessment and predictive maintenance.
  • Evaluation of alternative network configurations.
  • Contingency analysis and operational decision support.

AI should not be treated as a substitute for power-system engineering or validated operating procedures. Its recommendations need to be tested against engineering constraints and integrated into accountable operational processes.

The IEA's 2026 analysis identifies data quality, skills, organisational readiness, regulatory arrangements, trust and security as major conditions affecting the wider deployment of digital grid solutions.

7. Combining Grid-Enhancing Technologies

The greatest benefits may arise when several technologies address different constraints on the same network.

For example, a congested transmission corridor may have unused thermal capacity during favourable weather conditions. Dynamic line rating can reveal that additional capacity. If power still flows disproportionately through one circuit, advanced power-flow control may redirect some electricity to a parallel route. Topology optimisation may identify a more efficient network configuration, while remedial action schemes provide approved responses to specific contingencies.

These technologies can complement one another, but their benefits should not simply be added together. Several solutions may rely on the same available headroom, and addressing one constraint may expose another.

A combined assessment should consider:

  • Thermal capacity of lines and transformers.
  • Voltage and reactive-power requirements.
  • Transient and dynamic stability.
  • Short-circuit levels and protection coordination.
  • Substation and busbar limitations.
  • Contingency performance and restoration risks.
  • Communication, control and cybersecurity requirements.

The objective is not to maximise the loading of individual assets in isolation. It is to increase the amount of electricity the network can deliver securely and reliably as a complete system.

8. Planning and Implementing Grid-Enhancing Technologies

Step 1: Identify the actual network constraint

A GET project should begin with a clearly defined network problem, not with the purchase of a particular technology.

The operator should identify where and when the constraint occurs, which equipment limits power transfer, how frequently the constraint arises and what consequences it creates.

Relevant evidence may include:

  • Historical loading and outage records.
  • Power-flow and contingency studies.
  • Renewable energy curtailment data.
  • Grid connection applications and waiting lists.
  • Transformer and conductor condition assessments.
  • Voltage and power-quality measurements.
  • Congestion costs and redispatch requirements.

The assessment should establish whether the problem is primarily thermal, voltage-related, stability-related, operational or associated with insufficient network visibility.

Step 2: Determine whether the network is suitable

Different technologies require different network conditions.

Dynamic ratings may be attractive where thermal limits vary significantly with weather and equipment conditions. Power-flow controllers are more useful where alternative transmission paths exist. Topology optimisation requires reliable network models and switching capabilities. Remedial action schemes require well-defined contingency scenarios and dependable protection and communication systems.

The operator should also assess whether the proposed solution merely moves the bottleneck to another part of the network.

Step 3: Establish the data and digital infrastructure

The operator should determine whether it has sufficient monitoring, communication and control capabilities to implement the proposed technology.

This may involve installing sensors, upgrading communication networks, improving SCADA or EMS functionality, integrating asset-management databases and updating network models.

Data governance should establish who owns, maintains, accesses and validates operational data. Cybersecurity requirements should be considered from the beginning of the project rather than added after deployment.

Step 4: Conduct technical and economic assessment

The technical assessment should test whether the technology can deliver additional usable capacity while maintaining acceptable system performance.

The economic assessment should compare the full lifecycle costs and benefits of the proposed solution with alternatives, including conventional network reinforcement.

Relevant costs include:

  • Equipment procurement and installation.
  • Sensors and communication infrastructure.
  • Software licences and system integration.
  • Engineering studies and testing.
  • Training and operational changes.
  • Cybersecurity and ongoing maintenance.
  • Replacement and long-term support.

Potential benefits include reduced congestion, lower renewable energy curtailment, faster grid connections, improved asset utilisation, lower operating costs and deferred infrastructure investment.

The analysis should distinguish between a project that creates additional technical capacity and one that produces measurable economic benefits. Additional capacity has value only when it addresses a real network need and can be used without compromising system security.

Step 5: Pilot, validate and scale

A pilot project can help an operator test the technology under actual operating conditions before wider deployment.

A good pilot should define:

  • The network problem and project objectives.
  • Baseline operating conditions.
  • Performance indicators.
  • Testing and validation procedures.
  • Operational responsibilities.
  • Cybersecurity and safety requirements.
  • Criteria for scaling or discontinuing the project.

Results should be documented and compared with the baseline. Lessons from the pilot can inform procurement specifications, operating procedures, regulatory submissions and future investment decisions.

Step 6: Integrate the technology into normal operations

A successful pilot does not automatically become standard practice. Operators need to incorporate the technology into network planning, control-room procedures, maintenance, staff training and investment decisions.

This requires cooperation between planning engineers, system operators, protection specialists, information technology teams, cybersecurity professionals, regulators and equipment suppliers.

9. Economic and Regulatory Considerations

Comparing GETs with conventional grid expansion

Grid-enhancing technologies can often be deployed more quickly than new transmission lines, but the appropriate comparison depends on the network constraint and the expected duration of the benefit.

A GET may be suitable for relieving a temporary or localised bottleneck, improving utilisation while a new line is being constructed, or deferring a reinforcement that would otherwise be required.

However, a network experiencing sustained growth in electricity demand may still require new lines, substations, transformers or major upgrades.

The investment decision should therefore compare alternatives on a lifecycle basis, including reliability, operating costs, asset condition, future demand and the risk of relying on temporary capacity gains.

Utility incentives and regulatory frameworks

Regulatory arrangements can influence whether utilities invest in GETs.

In some regulatory environments, utilities may have clearer financial incentives and approval processes for building new physical assets than for adopting digital or operational solutions. Where revenue models reward capital expenditure more directly than improved network utilisation, operators may have limited incentives to pursue alternatives even when they could be economically beneficial.

Regulators can support GET deployment by:

  • Allowing digital and operational solutions to compete with conventional reinforcement in network planning.
  • Establishing transparent methods for valuing additional capacity and reduced congestion.
  • Providing clear cost-recovery arrangements for eligible investments.
  • Encouraging performance-based incentives linked to measurable network outcomes.
  • Supporting controlled pilot projects and regulatory sandboxes.
  • Requiring utilities to assess appropriate GET options before approving selected infrastructure investments.

Performance measures may include additional transfer capacity, reduction in congestion, renewable energy integration, avoided curtailment, reliability improvements and the cost of delivering network services.

Procurement and market development

Procurement should be based on the network problem and required performance rather than a preference for a particular vendor or technology.

Utilities should consider interoperability, compatibility with existing control systems, technical support, data ownership, cybersecurity, equipment maintenance and vendor dependence.

Open technical standards and transparent procurement processes can help prevent fragmented systems and reduce long-term integration costs.

10. Relevance for Emerging Economies and Developing Power Systems

Grid-enhancing technologies are relevant to both advanced and developing electricity systems, but the investment priorities and implementation conditions may differ.

In many emerging economies, utilities face a combination of insufficient transmission capacity, ageing equipment, high technical and commercial losses, limited operational data, constrained investment budgets and unreliable electricity supply.

GETs may help address specific constraints, but their deployment should be grounded in the condition and capability of the existing network.

Opportunities

Potential applications include:

  • Using weather-based ratings to improve the utilisation of suitable existing transmission corridors.
  • Improving visibility of heavily loaded transmission and distribution equipment.
  • Identifying network reconfiguration options to reduce local congestion.
  • Coordinating distributed renewable generation and storage.
  • Improving the management of voltage and distributed energy resources.
  • Reducing renewable energy curtailment where transmission constraints are a significant cause.

In systems with rapidly growing demand, better use of existing infrastructure can provide additional time for utilities and governments to plan and finance major network investments.

Barriers to deployment

Common barriers include:

  • Limited availability of accurate network data.
  • Inadequate monitoring and communication infrastructure.
  • Shortages of engineers and technicians with combined power-system and digital skills.
  • Weak utility finances and difficulty accessing investment capital.
  • Procurement and regulatory frameworks that do not recognise digital alternatives adequately.
  • Limited capacity for cybersecurity, software maintenance and long-term technical support.
  • Unclear responsibilities between transmission and distribution operators.

These challenges mean that the introduction of sophisticated software or sensors alone is unlikely to produce sustained improvements. Technology investments need to be accompanied by institutional capacity, operational reform and adequate maintenance arrangements.

Priorities for African electricity systems

For many African power systems, an appropriate starting point may be to improve network visibility, asset-condition information, outage records and the accuracy of network models.

Utilities and regulators can then identify congested corridors, overloaded transformers and renewable energy connection constraints where targeted GET deployment may offer measurable value.

Regional power pools and interconnected transmission systems may also benefit from improved coordination of power flows, congestion management and cross-border transfer capacity. However, regional solutions require cooperation between national system operators, compatible operating procedures and reliable communication and protection arrangements.

GETs should be considered alongside investments in new transmission infrastructure, distribution network reinforcement, generation adequacy, maintenance, electricity market development and regional interconnection.

11. Risks, Limitations and Common Implementation Mistakes

Grid-enhancing technologies can improve network utilisation, but they do not remove the physical and operational limits of electricity systems.

Common mistakes include:

  • Treating additional line capacity as equivalent to additional end-to-end network capacity.
  • Installing dynamic line rating without assessing transformer and substation constraints.
  • Redirecting power to alternative circuits without checking their available capacity.
  • Using topology optimisation without accurate network models and protection coordination.
  • Relying on automated remedial actions without adequate testing and safeguards.
  • Assuming AI can compensate for missing or unreliable operational data.
  • Ignoring cybersecurity and communication-system vulnerabilities.
  • Measuring success only by installed equipment rather than actual network outcomes.
  • Treating GETs as a permanent substitute for necessary grid expansion.

A technology may increase the thermal capacity of one component while voltage, stability, short-circuit or protection constraints continue to limit the usable capacity of the network.

The operator must therefore assess the complete system and verify that any additional capacity can be used securely under normal and contingency conditions.

12. Future Outlook

The deployment of grid-enhancing technologies is likely to become increasingly important as electricity systems accommodate more renewable generation, storage, electric vehicles, data centres and other forms of electrified demand.

The development of more affordable sensors, improved weather forecasting, advanced power electronics, digital substations, network modelling and AI-supported decision tools is expanding the range of options available to grid operators.

However, the main challenge is no longer simply whether many of these technologies can work. It is how to integrate them into utility planning, procurement, regulation and day-to-day operations.

The IEA's 2026 analysis identifies skills and organisational readiness, data quality, trust and regulatory frameworks as important barriers to wider deployment. Addressing these issues will require investment in people, digital infrastructure, operational processes and institutional coordination.

Grid-enhancing technologies should therefore be understood as part of a wider strategy for modern electricity networks. Their value lies in helping operators use existing infrastructure more intelligently while ensuring that new network construction remains aligned with long-term demand, reliability and energy-transition requirements.

Conclusion

Grid-enhancing technologies provide electricity network operators with additional ways to increase the capacity and efficiency of existing infrastructure. Dynamic ratings reveal available thermal headroom, power-flow control redirects electricity towards underutilised routes, topology optimisation identifies more efficient network configurations, and real-time remedial actions support secure responses to disturbances.

Their effectiveness depends on accurate data, appropriate network conditions, reliable monitoring and control systems, sound engineering, skilled personnel and supportive regulatory frameworks.

They are not a replacement for grid expansion. Rather, they can complement new infrastructure by relieving selected constraints, improving network utilisation, supporting renewable energy integration and helping electricity systems respond more quickly to changing demand and supply conditions.

See Also

External Links

References

  • Mirzapour, O., Rui, X. and Sahraei-Ardakani, M. (2024). Grid-enhancing technologies: Progress, challenges, and future research directions. Electric Power Systems Research, 230, 110304. https://doi.org/10.1016/j.epsr.2024.110304
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