Modelling Increasing Complexity of the Irish SEM in PLEXOS®

This is a guest blog from ClearPoint Power Consulting. To learn more about ClearPoint, and their services, visit: https://www.linkedin.com/company/clearpointpower.  

A wholesale price forecast alone is no longer enough to understand the commercial value of an asset in the Single Electricity Market (SEM), the wholesale electricity market covering Ireland and Northern Ireland. Where and how an asset connects to and operates on the power system is becoming increasingly important.

The all-island system is already managing instantaneous non-synchronous penetration of up to 75%, alongside geographically dispersed renewable generation, significant HVDC interconnection and rapidly growing concentrations of electricity demand. As these pressures build, network constraints and operational security requirements are playing a greater role in determining whether an asset can generate, charge or discharge when market prices are most attractive.

This can create a material gap between the theoretical value indicated by a wholesale price forecast and what an asset can capture in practice. A price forecast alone cannot account for site-specific exposure to dispatch-down, connection limitations and operational restrictions, or fully reflect the impact of forthcoming auction-based procurement on ancillary-service revenues. Conversely, with the right location and configuration, these same system pressures can create opportunities for an asset.

This article examines how growing system complexity is reshaping site-specific risk and opportunity in the SEM, and why investment decisions increasingly require integrated modelling of market prices, asset operation and the transmission network.

Renewable Volume Risk

For renewable projects, the most immediate impact is dispatch-down: available wind or solar generation that cannot be used because of local network constraints or wider system limitations. In 2025, 13.4% of available wind generation and 12.9% of available solar generation was dispatched down across the island. Looking forward, the latest constraint studies published by EirGrid, the transmission system operator for Ireland, indicate potential dispatch-down levels of 17–30% annually by 2030.

Importantly, dispatch-down will not be distributed evenly. The outcome for an individual project depends on where it connects, its priority-dispatch status, the generation connected behind the same bottleneck and the timing of planned local grid upgrades.

Concentrated Data Centre Loads

Ireland’s thriving digital economy has earned Dublin the “D” in Europe’s Frankfurt, London, Amsterdam, Paris, and Dublin (FLAPD) data centre cluster with data centres now accounting for 23% of national electricity demand annually. This load is heavily concentrated in the greater Dublin region. The system impact, however, extends far beyond simple transmission flow congestion into the capital. During frequency or voltage events, abrupt demand reductions across multiple data centres create unique operational risks. EirGrid is currently managing these through operational measures including restrictions on battery state of charge and, when necessary, limits on interconnector exports. The originating risk may be concentrated around Dublin, but the resulting operational rules can affect participant revenues across the wider market.

System Complexity Is Reshaping Ancillary Services Markets

A power system operating with high levels of non-synchronous generation requires new sources of reserve, frequency response, inertia, voltage support and other system, or ancillary, services.

This requirement is driving a wider reform of the SEM’s ancillary services arrangements under the Future Arrangements for System Services (FASS) programme. Many of the services currently procured under the existing regulated DS3 tariffs are moving towards auction-based procurement via a Day-Ahead System Services Auction (DASSA).

For potential service providers, from conventional generators to battery storage, the move to auction-based procurement changes how ancillary-service revenues must be forecast. Future ancillary service revenues will depend on procured service volumes, auction competition, technical qualification, delivery obligations and interactions with the day-ahead and balancing markets. This requires the co-optimisation of energy and reserve positions. Location also matters: some services are inherently locational, while reserve procurement must reflect requirements within both Ireland and Northern Ireland.

Complexity Also Creates Opportunity

The constraints posed by power system complexity do not necessarily remove value as new challenges are navigated. They are also driving policy and market changes intended to use existing network capacity more efficiently. For developers, that creates new opportunities — but only where technology, configuration and location are assessed together against the fundamentals of an evolving system.

Understanding Dynamic Capacity and New Opportunities

Hybridisation can increase the utilisation of existing grid connections by allowing multiple technologies to share a single export limit. This enables additional generation or storage to connect without a corresponding increase in grid capacity, while maintaining the same overall export limit.

The transmission and distribution system operators in Ireland are launching their implementation plan for dynamic maximum export capacity (MEC) sharing, where different technologies can operate under a common export constraint and optimise their output. The commercial value of such arrangements depends on how the combined assets interact in practice, including their coincident output, charging and discharging behaviour, exposure to network constraints and whether the project is greenfield or the hybridisation of an existing asset.

Locating Storage Where It Provides Network Value

The same constraints that reduce renewable output can create value for storage capable of charging behind a network bottleneck.

EirGrid’s proposed long-duration energy-storage (LDES) procurement mechanism explicitly targets the reduction of renewable dispatch-down. It proposes to provide a revenue floor to participating assets in exchange for operational controls that ensure the storage asset charges and discharges when it benefits the system.

There is an important point recognised here: a megawatt of storage does not provide the same system value everywhere. Its ability to reduce dispatch-down and its exposure to operational restrictions depends on its position within the network.

Bringing Network Intelligence into Investment Decisions

Whilst complex, the evolution towards a more dynamic system is not evidence that things are at breaking point. The challenges facing power system participants are simply the price of progress. The players who will thrive in increasingly challenging power systems are those who accept that complexity is the new baseline and identify new opportunities around it.

For power market modellers, this means integrated modelling of electricity markets, ancillary service auctions and the transmission network on enabling platforms like PLEXOS®. Many traditional market models simulate prices well while assuming the network has only a limited influence on outcomes, but that assumption is becoming increasingly difficult to justify. Answering questions about optimal hybrid asset configurations, expected dispatch down, and strategic network locations requires more than copper-plate market forecasts.

Improving Investment Decisions Before Assets Are Built

Price forecasts will remain central to investment decisions in the SEM. But a forecast price has value only to the extent that an asset can generate, charge or discharge to capture that price. As network and operational constraints become increasingly common, understanding site-specific volume and access risk will become as important as forecasting the price itself.

Integrated modelling at an early stage allows developers to test decisions before committing capital: where to locate an asset, how incremental generation will impact local network congestion, which battery configuration is optimal and how the timing of a network reinforcement changes the business case.

In a system this complex, the assets that win won't just be the ones with the best price forecast, but the ones designed and modelled to actually capture it.