Netherlands Methodology

Modo Energy provides benchmark data for battery energy storage systems across global energy markets, applying a standardized methodology to ensure consistency and transparency across all produced Indices.

1. Introduction

The Modo Energy Netherlands Methodology Framework outlines how Modo Energy calculates and constructs its battery energy storage Indices in the Netherlands. This document provides detailed insights into:

• the assumptions that define a representative asset;
• the components that make up published revenues;
• the optimisation model that simulates asset dispatch; and
• the data inputs and transformations that feed the simulation

to ensure accurate and reliable benchmarking for the Dutch battery energy storage sector.

1.1 Why the Netherlands requires a simulated index

The Modo Energy Netherlands Index differs from Modo Energy's GB Index in one fundamental respect: it is simulated, not measured.

The Netherlands has no asset-level data regime. Battery operational activity in the wholesale and ancillary markets is not publicly reported per asset.

To produce a benchmark under these conditions, Modo Energy simulates the dispatch of a representative battery asset against publicly available market data, using our Global Dispatch Model, a mixed-integer linear programme (MILP) that optimises battery revenues subject to market participation rules.

1.2 What the Netherlands Simulated Index represents

The Modo Energy Netherlands Index family (the ME vBESS NL Indices) represents the simulated revenue performance of grid-scale lithium-ion battery energy storage systems in the Netherlands. To capture differences in technical characteristics, the Index family includes variants grouped by system duration. This allows comparison of revenues across different types of utility-scale battery systems. The indices reflect the revenues a representative asset could earn.

The Dutch ancillary markets are shallow. The Index simulates the representative asset against realised prices with no market-impact adjustment: it assumes the asset's own bids would not have moved the clearing price. That assumption holds comfortably in the day-ahead and intraday markets. It is weaker in the Dutch balancing stack: the FCR contracted by TenneT is 55 MW, and when the 4-hour aFRR capacity product was released in November 2025, the entire book was 46 MW upward and 50 MW downward.

2. Index Construction

2.1 The ME vBESS NL Indices

Modo Energy currently produces a family of three indices for the Netherlands:

All three indices use the same published methodology, differing only in the duration parameter of the representative asset.

2.2 Representative BESS specification

The representative asset is specified as follows:

2.3 Index calculation methodology

The Index is calculated by:

1. Running Modo Energy's Global Dispatch Model over the assessed period, using the representative asset specification in §2.2 and the input data sources in §4.2.
2. Computing the simulated revenue of the representative asset across each modelled market and direction, in EUR, at 15-minute resolution.
3. Summing revenues per settlement period (15 minutes) and normalising by the rated power of the representative asset (10 MW) to obtain an Index value in EUR/MW per 15-minute settlement period.
4. Aggregating these values into monthly, quarterly, and annual indices as described in §2.4.

The calculation follows a clearly defined, rule-based methodology, with a percentage calibration factor to account for imperfect foresight as a discretionary adjustment (see §5.10).

2.4 Index value representation

All Index values are reported as net revenues per unit of rated power. Revenue and Index values can be represented using the following units:

• EUR/MW (period): total Index revenue for the assessed period (e.g. EUR/MW/month, EUR/MW/year).
• EUR/MW/year (annualised): total Index revenue for the assessed period divided by the number of days in the period and multiplied by 365.

2.5 Publication cadence and revisions

The ME vBESS NL Indices are updated daily. Modo Energy ingests source data from all markets listed in §4.2 daily and publishes Index values for delivery day D-2 every calendar day. The two-day publication lag allows settlement, late submissions, and backfills to complete before computing that day's Index.

Previously published Index values may be revised if upstream data providers issue corrected values for periods already covered by a published Index, if additional source data becomes available that materially improves the accuracy of a historical Index value, or if a methodology change under §7 is applied with retrospective effect. Revisions are logged with the affected period and the reason, and are communicated to users in line with §7.3.

2.6 Market evolution reflected in the Index

The Index reflects each market structure only for periods in which its native mechanism and data were in force. The key milestones are:

3. Revenue Components

3.1 Revenue components included in the Indices

The Modo Energy Netherlands Indices capture the primary revenue opportunities available to a representative BESS in the Dutch wholesale and ancillary markets. The table below details each component, the market from which it is modelled, and the price signal used.

3.2 Excluded revenues

Revenues from the following sources are excluded from the Modo Energy Netherlands Indices:

• Imbalance settlement: positions are assumed fully closed out in the intraday continuous market; the Dutch imbalance price is not applied.
• Grid fees and transport tariffs: set to zero for the representative asset. Dutch transport tariffs are levied per MW of contracted transport capacity, not per MWh of energy, so a tariff does not change the merit order of any individual trade. Grid fees will be made available in Custom Benchmarks.
• mFRR capacity and activated energy: not currently modelled. Modo Energy will review incorporation in a future methodology version if we see major market participation from batteries.
• Congestion management products (GOPACS, capaciteitsbeperkingscontracten): asset- and location-specific; not modelled.
• Bilateral contracts (PPAs, tolls, floors): not modelled, as they don't affect the optimal battery dispatch dynamics apart from in some co-located cases.
• Battery operator fees, warranty costs, and O&M: the Index reports gross market revenue, not net-of-opex.

4. Data Inputs and Use of Discretion

4.1 Data visibility and quality

The Modo Energy Netherlands Index is constructed exclusively from publicly available market data, with the exception of the representative asset parameters in §2.2, which are set by Modo Energy rather than observed. The modelling choices that sit on top of that data are defined in the section of §5 that covers the product they apply to.

4.2 Data inputs and sources

FCR activation data is not currently ingested for the Netherlands; FCR activation throughput is modelled as zero (§5.6).

5. Modelling Methodology

5.1 Overview of the Global Dispatch Model

The NL Index is produced by simulating the dispatch of the representative assets described in §2.2 against historical market prices using Modo Energy's Global Dispatch Model (GDM). For each day in the assessed period, the GDM determines how the representative asset would have scheduled its power across the markets in §3.1 to maximise revenue, given the battery's physical limits and the rules governing each market.

5.2 What the model is solving for

At its core, the GDM answers a single practical question: given the prices observed on a given day and the asset's physical and regulatory limits, what is the highest revenue a well-run battery could have earned?

To answer this, the model allocates the battery's power and stored energy across two families of market opportunities:

• Energy markets: day-ahead, intraday auction (IDA2), intraday continuous (ID3), and aFRR activated energy.
• Ancillary capacity markets: FCR and aFRR, in which the battery is paid to hold capacity available for TenneT.

Revenue is the sum of these streams, net of charging cost. Internal consistency rules prevent schedules that look profitable on paper but that a physical battery cannot execute (§5.4).

5.3 Three-step optimisation sequence

A real BESS trader in the Netherlands does not make all decisions at the same moment. Capacity products are procured the day before delivery, day-ahead energy clears shortly after, the intraday auction clears at a fixed point, and the continuous intraday market runs up to near real time, with aFRR energy bids repriced until shortly before each ISP. Each market gate closes before the next, and traders have to commit at each gate using only the information available at that point.

The model reflects this by solving the dispatch problem in three sequential steps:

1. Day-ahead step: sets capacity commitments (FCR and aFRR) and day-ahead energy positions.
2. Intraday Auction step: rebalances those positions through IDA2.
3. Intraday Continuous step: determines the final rebalancing in ID3 and the aFRR activated-energy positions.

Each step takes the positions committed in earlier steps as fixed: once a decision is locked in, the model cannot unwind it retroactively. This sequencing is what makes the simulation directionally realistic rather than a single idealised all-markets optimisation.

5.3.1 Day-ahead step

• Granularity: 60 minutes before 2025-10-01; 15 minutes from 2025-10-01 onward (reflecting the SDAC transition to a 15-minute day-ahead auction).
• Foresight: perfect foresight of day-ahead energy prices and the marginal FCR capacity prices, and the volume-weighted average capacity prices for aFRR over the full day.
• Markets optimised: day-ahead energy, FCR capacity, aFRR capacity.

5.3.2 Intraday Auction step

• Granularity: 15 minutes.
• Foresight: perfect foresight of intraday auction prices across the full day.
• Markets optimised: intraday auction (IDA2) only. Inactive before 13 June 2024.
• Commitments carried in: day-ahead energy positions, FCR capacity, aFRR capacity from Step 1 are fixed.

5.3.3 Intraday Continuous step

• Granularity: 15 minutes.
• Rolling horizon: 2-hour windows, advanced sequentially.
• Foresight: imperfect price foresight.
  • The underlying ID3 continuous-intraday series is replaced by a centred 2-hour rolling mean, representing a trader's blended view of near-term prices without perfect look-ahead.
  • aFRR energy prices beyond the window are instead taken from the aFRRE merit order published by TenneT, explained in §5.7.
• Markets optimised: intraday continuous (ID3) energy, aFRR activated energy (aFRRE), positive and negative.
• Commitments carried in: all prior steps' positions are fixed.

5.4 Market stacking and physical limits

Dutch market design permits a battery to hold simultaneous positions across day-ahead energy, intraday energy, FCR capacity, aFRR capacity, and aFRR energy, subject to physical limits on the battery and the grid connection. The model enforces stacking via the following families of constraints:

1. Sufficient SOC for ancillary delivery: the battery's state of charge at each timestep must be enough to deliver all simultaneously held discharging-direction ancillary products over their product-specific delivery horizons, and to absorb all charging-direction products. The horizons are set out in §5.4.1.
2. Sufficient power for ancillary delivery: held FCR and aFRR capacity is a power reservation: every MW committed is withheld from the energy markets in that period, so it stays available if TenneT calls. The one exception is aFRR energy against aFRR capacity, where activation delivers the reservation rather than adding to it, so aFRRE is netted out rather than stacked on top. FCR has no equivalent, since its activation is not modelled (§5.6).
3. aFRR vs aFRRE double-counting prevention: aFRR (capacity reservation) and aFRRE (energy activation) are distinct products. The model applies a pair of parallel constraints so that each physical limit (grid, battery, SOC) is checked once including aFRR and once including aFRRE, but never double-counted in a single inequality.
4. No cross-direction wholesale and activation in the same ISP: the model blocks holding aFRRE upward together with an ID3 downward position in the same settlement period, and the reverse. These would net out on paper due to the 15-minute granularity, while representing two contradictory physical instructions.

5.4.1 SOC delivery horizons

Both aFRR horizons are Modo Energy modelling assumptions and are stated as such. TenneT's published position is that no separate rules apply to limited energy resources. The horizon is applied at 1 hour through the day-ahead and intraday auction steps, and at 40 minutes in the intraday continuous step.

Why 40 minutes? An aFRR energy bid can be repriced until roughly 25 minutes before each ISP. Once that gate passes, the offered capacity must stay deliverable across the 15-minute ISP itself plus the 25 minutes of lead time already elapsed (40 minutes total), regardless of what happens in the market in between.

Why 1 hour at commitment? The day-ahead step is where the capacity volume is chosen, and that is the decision the asset cannot revisit. The commitment tier therefore carries the 40 minutes of exposure plus a margin, because activation can still reach the asset even when it is positioned at the far end of the aFRR energy merit order, and because the asset commits before it knows how deep the ladder will run on the day.

5.5 Battery physical model

The representative asset is modelled as a single lumped battery whose behaviour is governed by four technical characteristics:

• Round-trip efficiency of 88%. Efficiency losses are applied to the charging flow — 1 MWh drawn from the grid stores 0.88 MWh of usable energy.
• Continuous state of charge. The battery's stored energy in each timestep equals the previous timestep's level plus charging (net of efficiency) minus discharging. Energy delivered through aFRR activation moves SOC on the same basis as any other energy trade.
• State of charge boundaries. To allow for day-by-day solving of the model, SOC is assumed to be 50% at midnight of each day. This is to allow for participation in ancillary markets in the first 4h block of the day, in line with SOC requirements for FCR and aFRR positive.
• Cycling limit per day. Total discharge throughput per day is capped at 1.5 times the battery's usable capacity. Both wholesale-market discharge and aFRR activation count toward this limit, reflecting that warranties are typically written on total throughput rather than on the market into which the energy was sold.

Cell-level degradation is intentionally disabled in the published Index (§2.2) to keep the asset's duration constant throughout the full history, preserving comparability across years.

5.6 Ancillary services: capacity vs activated energy

The Dutch balancing stack distinguishes between reserving capacity (capacity payments) and being called to deliver energy (activation payments). The model treats these as two separate but coupled products, bid into different gates.

Capacity in both markets is bid in the day-ahead step, paid at the cleared capacity price (EUR/MW/h) over each delivery block, and reduces the power and SOC available to the energy markets.

• FCR capacity market: no throughput assumed. The product is symmetric, so expected activation nets out, and the activated energy is not compensated. There is no Dutch FCR activation feed either.
• aFRR capacity market: 10% throughput per leg, held in state of charge from the day-ahead step onward. Unlike FCR, aFRR has a remunerated energy market attached to it, and it is asymmetric: upward and downward are procured separately, so an upward commitment has to be covered by energy bought elsewhere. The downward leg is divided by the round-trip efficiency so that an equal upward and downward position nets out rather than draining the battery.
• aFRR energy market: a separate 15-minute directional product, bid in the intraday continuous step. The battery is paid, or pays, at the Dutch marginal activation price for energy actually delivered, which moves SOC and counts toward the daily cycling limit.

aFRRE activation volumes are capped by the active merit order. Because aFRRE is only valuable if activated, the held aFRRE volume in a given settlement period is capped at the share of the active merit order that TenneT activated, multiplied by the most aFRR energy the asset could still offer in that direction:

The numerator is the aFRR energy TenneT activated from Dutch bids in that quarter-hour for direction d. The denominator is the active merit order: the aFRR energy bids offered in TenneT's merit order list for that quarter-hour, multiplied by k, the share of the merit order that is frequently activated. A battery either wants to be activated and bids inside that share, or prices itself out of it.

k is the 99.9th percentile of activated over offered across the 365 days before each day, set per direction and fixed for the whole day. Activation is measured as a 15-minute average: TenneT can reach the full bid ladder for moments, but almost never uses it for a whole quarter-hour.

This ratio is a ceiling on the volume that could be activated, not an expectation of what will be. It caps how much aFRRE the asset may hold in that quarter-hour; the optimiser is free to hold less, or none. No floor is applied in the other direction, because a battery can always price itself high enough in the merit order that its activation probability is very low.

$v_d^{\text{aFRRE,max}}\left(t\right)$ is how far the asset's setpoint can still travel in that direction: its grid limit, net of the day-ahead and intraday position it already holds and of the FCR it is holding. It is not scaled to the aFRR capacity already won: aFRR (capacity) and aFRRE (energy) are bid and priced independently, and batteries can participate in aFRRE with more capacity than they have bid in the aFRR capacity market. Only one direction of aFRRE can be held in any given settlement period.

5.7 Foresight on aFRR energy

Inside the 2-hour rolling window of the intraday continuous step (§5.3.3), the model has perfect foresight of the realised Dutch marginal settlement price, the price the asset is actually paid on the energy it delivers.

Beyond the rolling-horizon window, the model needs a price for aFRR energy in case the battery is activated. aFRR energy is settled pay-as-cleared. In each quarter-hour, the price is set by the last bid the system activates in the merit order. The battery is only activated when the system reaches deep into that ladder. Those are the most expensive quarter-hours.

The forecast is therefore priced at the depth the system reaches in its 20% most extreme quarter-hours, the 80th percentile of activation depth. That is 260 MW upward and 240 MW downward. The two directions are calibrated separately, from 1 January 2025 to 31 August 2026.

5.8 aFRR capacity price ceiling (bid discipline)

Dutch aFRR capacity is procured pay-as-bid, and the published price can be pulled well above what a typical BESS operator would bid when a small number of very high bids are accepted, as bidding high risks losing the capacity entirely and earning nothing.

The Netherlands applies a rolling ceiling: prices are clipped to the trailing 30-day 95th percentile of the volume-weighted average price, computed separately for the positive and negative directions.

The Index prices a single 10 MW asset and assumes it is selected in full at that price. A bid of this size takes a small share of the volume TenneT procures, so the volume-weighted average is a fair representation of what it earns. A large portfolio bidding at a single price carries a real risk of partial or full non-selection, bids defensively as a result, and should expect to capture less. This is a selection effect from bid size rather than a gap between the model and reality, so it is not carried in the calibration factor in §5.10.

5.9 FCR-specific rules

Dutch FCR is procured through the FCR cooperation and cleared on the Regelleistung platform, so the product rules follow the cooperation's rather than a Dutch-specific design.

• Symmetric product: positive and negative capacity are contracted in equal volumes. The cooperation publishes one clearing price for the symmetric MW, which the model attributes to the positive leg only.
• Symmetric derating: the total (positive + negative) held FCR capacity is capped at 80% of the battery's rated power, consistent with the pre-qualification rules.
• aFRRE opportunity cost: every MW held as FCR is a MW that cannot earn aFRR energy. The optimiser therefore values FCR at its market price less that forgone revenue, floored at zero. Revenue is still settled at the market price, so the discount changes which product the asset chooses, not what it is paid.

where $\alpha$ is the expected aFRR throughput of 10% (§5.6), and ${\overline{p}}^{\text{aFRRE}}$ are volume-weighted aFRR energy prices over the trailing 30 days, taken per 4-hour block $b$.

5.10 Revenue calibration

To bridge the gap between theoretical maximum and what a real BESS fleet can earn, we apply a calibration factor that can be interpreted as “percent of perfect” (PoP). Three residual gaps remain between real market conditions and a simulated revenue model:

• Foresight gap: within the day-ahead and intraday steps, the model sees intra-window prices that a real trader does not know at gate closure.
• Availability gap: real assets are not available 100% of the time. Scheduled and unscheduled outages, maintenance windows, and prequalification re-tests all reduce the hours in which a battery can actually earn revenue.
• Execution gap: residual trading frictions and slippage not already reflected in the above.

The Index bridges this with a flat calibration factor applied to all simulated per-timestep revenues.

The factor is 0.80: every simulated revenue is multiplied by 80%. The value is taken from Great Britain, the market where Modo Energy observes both the modelled perfect-foresight revenue and the revenue the operational BESS fleet actually earns. The Germany and Poland Indices use the same factor. Dividing a published value by 0.80 gives the uncalibrated, perfect-foresight revenue.

It is applied as a single scalar rather than a market-by-market calibration, to preserve the internal revenue ratios produced by the optimisation. The factor is reviewed annually by Modo Energy's benchmark oversight function and updated in accordance with the methodology change process (§7).

6. Governance and Compliance

Modo Energy is committed to transparency by providing detailed explanations of calculation methodologies, revenue components, and benchmark updates. All key elements of the methodology are publicly available, ensuring stakeholders can fully understand the benchmark's structure and operation. Transparency measures include:

• Publication of methodology documents outlining calculation processes and revenue components.
• Historical data updates to maintain accuracy and consistency.
• Advance notice of material methodology changes in line with §7.3.
• Documentation of stakeholder feedback and responses, available upon request by emailing team@modoenergy.com.

7. Methodology changes

7.1 Model versioning: the Stable Version

The published industry-wide Indices are computed using a single designated version of the Global Dispatch Model (the "Stable Version"), regardless of when an index was created. Modo Energy updates the Stable Version no more than once per calendar quarter. Market structure changes outside Modo Energy's control may require an update ahead of this cadence.

7.2 Review and update process

The methodology undergoes a structured review process to ensure it remains aligned with evolving market conditions and regulatory requirements. Reviews are conducted:

• Annually by the Benchmark Oversight Function.
• Quarterly manual audits to assess data accuracy and consistency.
• Upon identification of material changes in market conditions or data availability.

Direct back-testing against observed transaction data is not possible because per-asset revenue is not publicly disclosed in the Netherlands. Modo Energy therefore applies a capture rate (§5.10) informed by fleet performance in markets where both perfect-foresight modelled revenues and realised asset earnings are observable, such as Great Britain and ERCOT.

7.3 Notification of changes

Significant methodology changes are communicated to stakeholders in advance of implementation. A Stable Version update is material where the cumulative movement in the Index across all Stable Version updates in that calendar quarter would exceed ±2%. Material updates are announced with not less than 30 days' written notice before implementation, together with an impact analysis. All methodology changes are recorded in Appendix I.

7.4 Recalculation and result versions

When a Stable Version update is implemented, Index values for the preceding 365 days are recalculated under the new Stable Version. Only the current version of results is available at any time.

8. Consistency and continuity

8.1 Quality assurance

Modo Energy employs rigorous quality assurance processes to ensure benchmark integrity. These include:

• Continuous automated validation checks to identify discrepancies in input data.
• Automated regression tests on every change to the Global Dispatch Model.
• Quarterly manual audits to verify data sources and methodology compliance.
• Internal audits to ensure alignment with regulatory standards.

8.2 Data integrity

Data integrity is maintained through:

• Secure data management protocols, including access controls and regular backups.
• Clear traceability from raw source (EPEX SPOT, Regelleistung, ENTSO-E, TenneT) into the model feed.

8.3 Handling data quality issues

Modo Energy has clear procedures to address instances where the quantity or quality of input data falls below the standards required for accurate and reliable benchmark determination:

1. Data issue verification: when data quality issues are identified, Modo Energy confirms the issue with the upstream data provider.
2. Customer communication: customers are informed of any confirmed data issues and corrective actions taken to maintain transparency within 48 hours of confirmation.
3. Data unavailability: in cases where the data provider is unable to supply the required data, Modo Energy notifies customers of impacts and publishes the Index only once finalised data is available.

The aFRR capacity price ceiling in §5.8 sits alongside this process rather than replacing it. It bounds the effect of outliers on the Index, but a confirmed upstream data error is still corrected at source and the affected period revised under §2.5.

8.4 Traceability and verification

Modo Energy ensures all benchmark calculations are fully traceable and verifiable through:

• Maintaining comprehensive records of input data, Stable Version, and calculation outputs.
• Reproducibility: every published Index value can be reproduced from the archived input data and the Stable Version in use at the time of publication.
• Public disclosure of material methodology changes.

Appendix I — Methodology changes

Methodology changes since first publication will be tracked here.

Disclaimer

This document, including the methodologies and indices described herein, is the proprietary work of MODO ENERGY LIMITED (“Modo Energy”) and is provided solely for informational purposes. These indices are designed for use in financial analysis, benchmarking, and decision-making. However, they do not constitute investment advice or a recommendation regarding any specific financial instrument, asset, or strategy.

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