France 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 France Methodology Framework outlines how Modo Energy calculates and constructs its battery energy storage Indices in France. 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 French battery energy storage sector.

1.1 Why France requires a simulated index

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

France 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 France Simulated Index represents

The Modo Energy France Index family (the ME vBESS FR Indices) represents the simulated revenue performance of grid-scale lithium-ion battery energy storage systems in France. 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.

1.3 Definitions

2. Index Construction

2.1 The ME vBESS FR Indices

Modo Energy currently produces a family of three indices for France:

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 (50 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 §5.9).

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 FR 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.

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 France Indices capture the primary revenue opportunities available to a representative BESS in the French 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 France Indices:

• Continuous intraday trading beyond state-of-charge management: the model uses ID3 only to rebalance after aFRR activation, not to trade it for its own revenue (§5.3.3).
• Imbalance settlement: positions are assumed fully closed out in the intraday market; the French imbalance price is not applied.
• Grid fees and transport tariffs (TURPE): set to zero for the representative asset.
• mFRR and RR capacity and activated energy, and the balancing mechanism (mécanisme d'ajustement): not currently modelled. Modo Energy will review incorporation in a future methodology version if we see major market participation from batteries.
• Capacity mechanism (mécanisme de capacité): not modelled. It is earned per certified MW over a delivery year, not from dispatch.
• 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 France Index is constructed exclusively from publicly available market data, with the exception of the parameters below, which are set by Modo Energy rather than observed. The table lists all of them, with their value, the reason for it and the section that defines it. Modo Energy's market owner for France, currently Emiel Van Vlaenderen, sets and maintains them (§4.3).

4.2 Data inputs and sources

4.3 Use of discretion and consistent judgment

The Index is rule-based. The parameters in §4.1 apply in the same way to every day and every duration, and no value is set by hand for a single day. Judgment is used only when a parameter is chosen or changed, and the market owner makes that call. Every parameter sits in the code of the Global Dispatch Model, so a change is reviewed by a second person before release, is tested by the automated regression tests in §8.1, and follows the change process in §7.3.

5. Modelling Methodology

5.1 Overview of the Global Dispatch Model

The FR Index is produced by simulating the dispatch of 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) and aFRR activated energy.
• Ancillary capacity markets: FCR and aFRR, in which the battery is paid to hold capacity available for RTE.

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

5.3 Three-step optimisation sequence

A real BESS trader in France 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 aFRR energy bids are 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. aFRR energy step: determines the aFRR activated-energy positions, and uses ID3 only to bring the state of charge back after activation.

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 and aFRR capacity prices 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.
• Commitments carried in: day-ahead energy positions, FCR capacity, aFRR capacity from Step 1 are fixed.

5.3.3 aFRR energy step

• Granularity: 15 minutes.
• Rolling horizon: 2-hour windows, advanced sequentially.
• Foresight: imperfect price foresight. aFRR energy prices are realised inside each window; beyond it, they are taken from the French aFRR energy bid ladder, explained in §5.7.
• Markets optimised: aFRR activated energy (aFRRE), positive and negative. From 23 January 2025 the model can also use ID3, for state-of-charge management only.
• Commitments carried in: all prior steps' positions are fixed.

ID3: state-of-charge management, not a market the Index optimises. The model uses ID3 to bring the state of charge back after an aFRR activation, so the battery can keep delivering the aFRR it holds. Every MWh bought or sold on ID3 carries a cost of €50 in the optimisation. A trade therefore only goes ahead when there is an important need for state of charge management. The €50 steers the model only and is not deducted from the published revenue.

5.4 Market stacking and physical limits

French 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 RTE 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 FCR activation can’t be optimised.
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 aFRR energy up and down in the same quarter-hour: the model holds aFRRE in one direction only in each settlement period, so an upward and a downward activation never cancel out on paper.

5.4.1 SOC delivery horizons

The aFRR hold is a Modo Energy assumption based on RTE's scheduling rules: a schedule change takes effect one hour after the next scheduling gate, and until then the battery must keep delivering the aFRR it holds. The hold therefore applies in every step, including the aFRR energy step.

5.4.2 Limit on aFRR up and down held together

Before a battery can offer aFRR, it must pass RTE's certification tests for storage units (Trame aFRR Agrégat/Stockage, version of 23 March 2026). The hardest is test 1b, a 48-hour stress test built from two tense days: RTE keeps the aFRR band at full power 59% of the time, mostly upward, with stretches of up to 6 hours in one direction.

Modo Energy replays this test, and RTE's two other storage tests, for batteries of 1 to 12 hours. For each duration, it finds the largest aFRR up plus down a battery can hold and still deliver at all times, with 50% state of charge at the start and a wholesale position that rebalances every quarter-hour within the power aFRR leaves free. The Index caps aFRR up plus down in each quarter-hour at that share of rated power. Each direction on its own stays capped at rated power.

These limits come on top of the state-of-charge hold in §5.4.1. They mainly affect longer-duration batteries: shorter ones are already limited by the state-of-charge hold.

5.4.3 Limit on aFRR up by charging power, and on aFRR down by discharging power

This limit does not change the published Indices: their representative asset charges and discharges at full rated power (§2.2). It applies to Custom Benchmarks whose import or export connection is smaller than rated power.

After upward activation a battery has to charge back the energy it delivered, and after downward activation it has to discharge the energy it took in. How much aFRR it can hold therefore depends on how fast it can do that. Both limits come from the same replay of RTE's storage tests as §5.4.2.

• aFRR up is limited by the battery's charging power: its import connection plus the on-site solar it may store, at most rated power, averaged over the day.
• aFRR down is limited by its discharging power: its export connection, at most rated power, averaged over 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.
• 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 at the start of the day, in line with SOC requirements for FCR and aFRR.
• 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 French 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 markets (FCR, aFRR): the battery is paid by the TSO for holding capacity available, with the bid set in the day-ahead step. Revenue accrues at the cleared capacity price (EUR/MW/h) over each delivery block. Capacity held reduces the power and SOC available for energy-market participation.
  • FCR capacity is modelled with an energy throughput taken from RTE: in each quarter-hour, the battery is activated on the same share of its FCR capacity as RTE activated of the FCR France contracted.
  • aFRR capacity is modelled with zero assumed energy throughput as holding aFRR does not by itself drain SOC or count toward cycling, so the capacity payment is the only revenue stream from aFRR.
• Activated-energy market (aFRRE): a separate 15-minute directional product, bid in the aFRR energy step. The battery is paid, or pays, at the French aFRR energy 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 RTE activated, multiplied by the most aFRR energy the asset could still offer in that direction:

The numerator is the aFRR energy RTE activated from French bids in that quarter-hour for direction d. The denominator is the active merit order: the aFRR energy bids offered to RTE 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.

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 aFRR energy step (§5.3.3), the model has perfect foresight of the weighted-average price of aFRR activated for France, published by RTE per quarter-hour. The Index also settles aFRR energy at this price.

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 50% of the volume offered to RTE upward and 46% downward, a share rather than MW because the offered volume varies widely. The two directions are calibrated separately, from 24 September 2025 to 23 September 2026.

5.8 FCR-specific rules

French FCR is procured through the FCR cooperation and cleared on the Regelleistung platform, so the product rules follow the cooperation's rather than a French-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.
• Derating: held FCR capacity is capped at 80% of the battery's rated power in each direction.

5.9 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, Netherlands and Poland Indices use the same factor. Dividing a published value by 0.80 gives the uncalibrated 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. Any change to the factor follows the change process in §7.3.

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.
• A contact point for questions about the methodology: 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.

7.2 Review and update process

The methodology is reviewed when market rules, market conditions or data availability change, and when inputs or results look out of line. Any change that follows goes through §7.3.

Direct back-testing against observed transaction data is not possible because per-asset revenue is not publicly disclosed in France. Modo Energy therefore applies a capture rate (§5.9) 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 Material and non-material changes

A change is material where it moves the Index by more than ±2% cumulatively in a calendar quarter. Material changes are announced with not less than 30 days' written notice before they take effect, together with an impact analysis.

Other changes are non-material. They may be made without prior consultation and are disclosed as soon as practicable.

Emergency changes needed to protect the integrity of the benchmark or to comply with law may be made without prior consultation, with notice given as promptly as circumstances permit.

All changes are recorded, with their effective date, in the change log (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 uses these checks:

• Automated validation checks to identify discrepancies in input data.
• Automated regression tests on every change to the Global Dispatch Model.

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, RTE) into the model feed.

8.3 Late, missing or distorted data

The Index for a delivery day is published only once the inputs in §4.2 are available for that day; the two-day lag in §2.5 allows for this. Inputs are used as published, including extreme prices. The only adjustments are these:

• Quarter-hours with less than 50 MW of aFRR energy offered are treated as gaps in the activation cap, which then uses the last offered volume for up to one day. After a day without offers, the cap is zero (§5.6).
• Hourly day-ahead prices before 1 October 2025, and 4-hour FCR block prices, apply to every quarter-hour they cover.
• Where RTE's bid ladder does not reach the forecast depth, the realised price is used beyond the optimisation window (§5.7).

If a source corrects data for a period already published, the Index for that period may be recalculated (§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.

9. Limitations

The Index is a simulation. These are its main limits:

• Simulated, not measured. It shows what a representative asset could have earned, not what any real battery earned. Per-asset revenue is not public in France, so the Index cannot be back-tested against real results (§7.2).
• Foresight. The model knows day-ahead, intraday auction and capacity prices when it decides, and aFRR energy prices two hours ahead; it plans its state-of-charge trades on ID3 with prices averaged over two hours (§5.3). The 0.80 calibration factor that corrects for this comes from Great Britain; it has not been observed in France (§5.9).
• aFRR up + down limit. The replay behind the limit lets the wholesale position rebalance from the next quarter-hour, not after RTE's one-hour delay. We see anticipating activation and trading ahead as the optimiser's job. It does not do this perfectly, which is one reason for the 0.80 calibration factor (§5.4.2, §5.9).
• Price taker. The Index assumes the asset's bids would not move prices and are always selected in full.
• aFRR energy. The activation cap reflects how much of RTE's bid ladder was activated, so it represents an average bidder. A real asset's activation depends on its own bid prices (§5.6).
• Concentrated inputs. Each input comes from a single source: RTE for all aFRR data, Regelleistung for the FCR price, EPEX SPOT for wholesale prices. An error or change at that source flows into the Index (§4.2).
• One asset design. 50 MW, full grid connection, no grid fees, no degradation and 50% state of charge at midnight. The revenue streams in §3.2, such as continuous intraday trading beyond ID3, imbalance, mFRR and the capacity mechanism, are not included.
• ID3 for state-of-charge management only. The model does not trade ID3 for its own revenue: a €50 per MWh cost, a Modo Energy assumption, keeps it to bringing the state of charge back after aFRR activation. A real trader may use ID3 more actively (§5.3.3).
• Changing market design. The history spans RTE joining PICASSO, the move to 15-minute day-ahead prices and RTE's quarter-hourly scheduling gates (§2.6), so values before and after these dates are not fully comparable.

Appendix I — Methodology changes

All changes, material and non-material, are recorded here with their effective date.

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